[HN Gopher] AI is slowing down
___________________________________________________________________
AI is slowing down
Author : crescit_eundo
Score : 480 points
Date : 2026-06-08 15:46 UTC (14 hours ago)
(HTM) web link (www.wheresyoured.at)
(TXT) w3m dump (www.wheresyoured.at)
| ElFitz wrote:
| I find it difficult to separate this piece's tone from its
| content. The tone puts me off and makes it hard for me to judge
| it on its merits, despite some of the arguments seeming sound and
| well supported.
| metadat wrote:
| Agreed. I am open to the possibility of the bubble bursting or
| whatever, but this piece is like 3,000 words and cites
| everything as evidence the sky is falling. It's just as bad as
| the pro-AI grifters, just in the other direction.
|
| Does the truth normally lie somewhere in the middle of it all?
| kunai wrote:
| Probably. Although I feel more inclined to forgive Ed in this
| case because it's sort of fighting fire with fire, the
| insanely hyperbolic and obscenely misleading drivel that's
| coming out of the most ardent AI boosters is continually
| unchallenged in the public eye. In a world where we had a
| more realistic view of AI/ML/LLMs, the limits to its
| capabilities, and the negative externalities of its
| widespread adoption in places where it quite frankly does not
| belong, then I'd be more critical of the Chicken Little sort
| of writing style
| viccis wrote:
| >Does the truth normally lie somewhere in the middle of it
| all?
|
| Usually does when you decide what constitutes extreme.
| marcosdumay wrote:
| At the /. times, there was somebody there with the best
| signature line. It was something like:
|
| "Some people say the Sun sets at East, other people say it
| sets at West. The truth, of course, is certainly on the
| middle."
| techblueberry wrote:
| Given the way tone has been intentionally abused, particularly
| in this industry, I'll take a few f bombs and the truth.
| GaggiX wrote:
| >I'll take a few f bombs and the truth.
|
| Don't want to ruin it but go read some old posts from the
| author about AI, the tone is the same and he is very much
| wrong.
| aoeusnth1 wrote:
| What about all his other articles that had f-bombs and the
| predictive utility of used toilet paper?
| JacobAsmuth wrote:
| https://www.wheresyoured.at/peakai/
|
| "I believe that artificial intelligence has three quarters to
| prove itself before the apocalypse comes, and when it does,
| it will be that much worse, savaging the revenues of the
| biggest companies in tech. Once usage drops, so will the
| remarkable amounts of revenue that have flowed into big tech,
| and so will acres of data centers sit unused, the cloud
| equivalent of the massive overhiring we saw in post-lockdown
| Silicon Valley."
|
| Ed Zitron. Mar 18, 2024
| sumeno wrote:
| Ed's posts are peak preaching to the choir, they're usually
| factually correct but he is really bad at convincing anyone who
| doesn't already strongly agree with him.
| JesseTG wrote:
| Have you seen his recent Bloomberg appearance? He's calm,
| collected, and matter-of-fact -- the complete opposite of how
| he presents himself on his newsletter and podcasts, but with
| the same argument. You wouldn't know from listening to him
| how spicy he usually is.
| d33d wrote:
| I dont really understand the criticism either way.
|
| He's in the media business... its in his interest to amp
| things up.
| JesseTG wrote:
| Yes, of course.
| nyeah wrote:
| It's tuned to the audience. Bloomberg was traditionally for
| people who actually wanted information. People who were
| fallible and had limited knowledge.
|
| Of course that mentality is obsolete. Now we all have
| infinite access to perfectly correct information via the
| internet.
| lowmagnet wrote:
| wow someone tell the philosophers this guy has figured
| out the knowledge problem!
| ElFitz wrote:
| Perhaps that's it. I would tend to agree with his position, I
| think, but don't appreciate being preached to. Even less so
| when I agree with what's being said.
| nyeah wrote:
| Agreed. If the arguments seem sound and well supported, then
| all we can do is attack the tone.
| ElFitz wrote:
| You can disagree. Sarcastically, or otherwise. But I think
| you may be reading more into my comment than I put there.
|
| I'm not attacking the piece. I'm not saying it's right. I'm
| not saying it's wrong.
|
| What I'm saying is, the tone made it hard for me to judge the
| arguments fairly, despite finding some of them convincing.
| And as much as I dislike it, persuasion does partly depend on
| _how_ an argument is made.
| nyeah wrote:
| Thanks, it's very clear what you're saying.
| bpodgursky wrote:
| What's the point of arguing with any of this.
|
| It's like someone arguing that cheese isn't real. Yes I can go to
| the grocery store and take a picture of cheese and show it, but
| what's the point? They can live in their own world. It doesn't
| change any of our lives. The world is what it is.
| happycube wrote:
| Lol... in this case, cheese imports from China are _much_
| cheaper, just not _quite_ as good.
|
| And for those who are all "but dur CCP get all ur data" you can
| use things like AWS Bedrock (at least for earlier versions of
| Deepseek and Qwen for now) and have more familiar people get
| all your data. Or buy (at obnoxiously inflated prices) your own
| HW and not send your data to anyone.
| bayarearefugee wrote:
| > "but dur CCP get all ur data"
|
| The funniest part of this is that people are often talking
| about how LLMs are now writing 100% of their code, then also
| saying that they don't want to expose their code to foreign
| government exfiltration by using foreign models.
|
| But, uh, if an LLM is writing 100% of your code you have no
| actual secret sauce to hide from anyone, so why worry about
| it.
| recursive wrote:
| Perfect for idea people. All the value is in the prompt.
| Ideas are important, not execution. A decade or two ago,
| they would have been looking for a technical co-founder.
| saltcured wrote:
| I think we're going to see a lot of craziness in the future
| in this regard. Not just "secrets", but hypocrites trying
| to copyright and patent all the AI outputs. All kinds of
| rabid attempts at constructing monopolies for every half-
| baked idea they have tried to utter as a prompt.
|
| Meanwhile, like I think you suggest, I would assume
| everyone can generate similar outputs themselves. The idea
| that you can claim priority on your dream prompt and lock
| up the market on prompt responses sounds delusional to me.
| It's not novel invention when you're spit-balling at the
| same level of abstraction as every fantasy/scifi writer who
| ever was.
|
| So I also have doubts about the sustainable business model.
| How long will it take for this fantasy to unravel, as
| people discover they cannot monetize their AI outputs as
| much as they dreamed, and in turn cannot afford to pay the
| AI services they use?
|
| My absolute nightmare is that this becomes a "too big to
| fail" thing and oppressive/fascist governments decide to
| back full regulatory capture. That instead of letting it
| unwind, they grant and support enforcement of an
| increasingly absurd and arbitrary copyright/patent regime
| to support this monetization scheme.
| james2doyle wrote:
| Yeah, so true. There is no moat to your competitors using
| the exact same tools and prompts to generate their apps and
| services. Companies should be hiring/retaining creative
| thinkers that give them that human edge rather than laying
| people off under the guise of "improved efficiency"
| alexashka wrote:
| > What's the point of arguing with any of this.
|
| > It's like someone arguing that cheese isn't real
|
| I agree with your first statement (any being you) because of
| your second statement.
| swader999 wrote:
| I think we need to see Open AI's and/or Anthropic's S1's to
| really know the state of it all.
| dr_robert wrote:
| Totally agree, remember WeWork's S1 and the fall that followed.
| Don't think it's the same case, but it'll clarify a lot of
| things
| dkobia wrote:
| Zitron is begging for a collapse at this point. Yes, his macro
| analysis correctly identifies a massive financial risk but his
| incessant pessimism completely misses the incredible ground-level
| utility that many of us on HN celebrate every day through
| undeniable, massive productivity gains.
|
| At this point I'm trying to believe there's a middle ground where
| the level of individual capability this unlocks, leads to major
| discoveries.
| oudlys wrote:
| Productivity is not value. It's quite possible for you to
| experience productivity improvements, and actual value to not
| be created. That is what I think the most robust data is
| showing.
|
| https://unessays.substack.com/p/talk-is-cheap
| bigstrat2003 wrote:
| Also, supposed productivity gains are dubious. I personally
| experience at best no productivity gains when using LLMs to
| write code, and sometimes it's an active drain on my
| productivity. There was that one study a year or so ago
| showing similar results. People are trying to say the
| productivity gains are there and undeniable, but that is not
| true. It is very much a subject of controversy whether AI
| helps productivity.
| asdfasgasdgasdg wrote:
| I can see an argument that the productivity gains are
| illusory / don't translate to economic productivity. I'm
| not denying the possibility.
|
| However, most of the engineers I respect have gone from
| being skeptics a year ago to convinced today. I don't
| personally know any true holdouts any more. If there are
| studies that disprove productivity gains more than six
| months ago, I'm happy to believe that it was true of the
| AIs that were available at the time. But I'm going to need
| something much more recent before I disbelieve my lyin'
| eyes where it pertains to the AIs available today.
| oudlys wrote:
| There is an observational study that was published in
| March 2026 that followed 4000 teams over 2 years. It
| shows, in my view, exactly that the productivity gains
| don't translate into economic value.
|
| Here is the report:
|
| https://www.faros.ai/blog/ai-acceleration-whiplash-
| takeaways
|
| And my commentary:
|
| https://unessays.substack.com/p/talk-is-cheap
| asdfasgasdgasdg wrote:
| If it was published in March 2026, even if the data was
| collected up to the day the study was published, 7/8ths
| of it would fail my "within the last six months" test.
| But I am looking forward to the results of future studies
| on this topic!
| oudlys wrote:
| I get wanting to wait for more data. And thinking that
| LLMs have improved enough that this will change.
|
| My view is that it's not really about how good the models
| are - it's about how we're using them. Understanding what
| you've built is an important part of value creation, and
| LLMs eliminate that.
| dminik wrote:
| Its funny, I've noticed the same thing, but did not come
| to the same conclusion.
|
| I currently don't have work access to Claude Code, but
| most of my teammates do. Watching from the outside, the
| cycle seems to look like this:
|
| 1. Experience some success, which hooks you into relying
| on AI.
|
| 2. The AI keeps failing at some task, but you don't want
| to stop. Keep trying over and over again.
|
| 3. Run out of tokens and take a break.
|
| Now, sometimes 1 doesn't happen. Sometimes 2 doesn't
| happen. 3 is a certainty though.
|
| Now, if you told me that the productivity gain from 1 is
| enough to offset the loss from 2 and 3, I could believe
| you. But I also wouldn't be surprised if it didn't.
| chillacy wrote:
| As I work with Claude more and gain a feel for its
| capabilities, I tend to run into 2 far less often, as
| I'll decompose my messages more for the current model
| limitations. The threshold also changes each release.
| techblueberry wrote:
| I'm going back to being a holdout, but it's nuanced - My
| theory into why LLMs don't lead to the colloquial
| definition of productivity would be something like - if
| code was never the bottleneck than generating code faster
| doesn't result in more meaningful output.
|
| Even if you take for granted that AI is as good as the
| best people say in writing code. And Ive spent a lot of
| time generating codes, I won't disagree - Then the
| question becomes - does this change your daily incentives
| such that you reach for code as the solution to your
| problems rather than something else (coordinating with
| your colleagues? Product management? Planning and Design?
|
| So from a holistic perspective, I think intentionally
| limiting your own AI usage is the best approach for
| maximum long-term productivity.
| asdfasgasdgasdg wrote:
| I'm not completely closed to your idea but if code was
| never the bottleneck why did so many organizations always
| feel so chronically low on coders? And of course this
| requires the AI to be no help at all with what is
| actually the bottleneck.
| nyeah wrote:
| That's possible, sure. But I think the answer is more likely
| in the numbers, not in just qualitatively saying AI isn't
| worth anything. Like if I pay $30k for an ounce of gold, I
| got value. Gold is worth something. But that amount of gold
| wasn't worth what I spent.
|
| EDIT: In fact, parent comment has a link to some numbers.
|
| [EDIT: Most] people don't want to go through the numbers. Ok.
| But there's a history here. When people don't want to see the
| numbers, certain kinds of things tend to happen.
| oudlys wrote:
| I've posted numbers that indicate that productivity is
| becoming decoupled from value delivery. If you follow the
| link in my comment it reviews a pretty robust study of 4000
| teams over 2 years. There is no product throughput
| increase.
| nyeah wrote:
| Interesting data, thanks.
| d33d wrote:
| Yep.
|
| Code acceleration is great, but.... something precedes
| that. Vision and strategy re. expansion of offerings and
| businesses. Once a firm reaches maturity in what it
| offers and is only touching the edges - this code
| acceleration is literally useless when you factor in all
| of the trade-offs.
|
| This is a good thing - it means fat and slow incumbents
| are sitting ducks to be out-witted by creative and
| imaginative founders, which is healthy for a well-
| functioning economy.
|
| Now the economics of existing frontier models are not
| sustainable - its looking like a mix of the airline
| (supersonic vs subsonic) and EV industry with China in
| the background providing decent offerings at much lower
| prices.
| oudlys wrote:
| I think its worse than that.
|
| I admit that if a small team or an individual uses an
| LLM, it's likely they can create value faster.
|
| I think as soon as you don't own the responsibility for
| the defects you generate with an LLM, their use starts to
| destroy value. Regardless of product maturity.
|
| This is what I think the data says.
|
| https://unessays.substack.com/p/talk-is-cheap
| nyeah wrote:
| Yeah this part scares me a little. I imagine it scares
| everyone who is more than a couple of years out of
| school. I hear that "the solution to LLM tech debt is
| more LLM." That might be true, but it might not be.
| oudlys wrote:
| It scares me too.
|
| I actually think this is precisely the reason LLMs can't
| be the basis for a technological revolution. Because it's
| only one way.
|
| Like, if you have a compiler, and it has a bug. You can
| discover if that bug is influencing your code execution
| and patch it. You can go both up and down the stack.
|
| With LLMs, there is no way to patch it's translation
| function. You have to rely on it to forward process.
|
| I don't think there is any way to avoid us understanding
| our tech stacks.
| d33d wrote:
| You're not really getting it.
|
| If you are producing something that delivers a far better
| experience, irrespective of what's under the hood (see
| Claude Code et al), you will decimate an incumbent who is
| trying to use LLMs in the context of incrementally
| improving a mature product.
|
| LLMs are suited for the development of revolutionary
| innovation, not incremental.
| oudlys wrote:
| I think we mostly agree.
|
| I think I just disagree about the power of the LLM to
| deliver revolutionary innovation. That's something you
| do. Not the machine.
|
| And, pretty soon on your journey to scale, the LLM
| becomes a hinderance rather than a help.
| amatheus wrote:
| From an economic perspective productivity is defined as the
| creation of value isn't it? Then if you "improve
| productivity" and does not create value in the end you're no
| improving productivity at all.
| oudlys wrote:
| It does depend on how you define productivity. But the way
| it's commonly used is "I'm going faster, personally, with
| these tools."
|
| The thing people I think have a hard time seeing is that "I
| go faster" does not mean "more features get finished".
|
| It's a scale issue, and one scale is better than the other.
| People only pay for finished features, they do not pay for
| how much code you emit.
| fl4regun wrote:
| economists define productivity as gdp per hour worked.
| Like a lot of other economic measurements, its mostly a
| bogus number people use as an argument on why their
| politics are better than someone elses politics. You can
| have an efficient business located in a poor country
| making the same product and same quality as that same
| business in a rich country, the rich country will be more
| "productive" because local cost of goods is higher there
| (i.e. a restaurant in NYC is more "productive" than a
| restaurant in bangladesh).
| oudlys wrote:
| Sure. But that's not, in my view, how most people use the
| word productivity when describing LLM use.
|
| In my field - operations - productivity is usually
| described as some rate of production for a specific
| asset. 100 widgets / machine / hour - for example.
|
| "My productivity is 3 PRs / day with the LLM as opposed
| to 1 PR per every three days". That's how I think people
| are thinking about it.
|
| My point is that's not the same thing as value. I.e. what
| people will pay for.
| fl4regun wrote:
| You're correct, I just wanted to add that there is
| another definition that you may see used online, and it
| is very specific, and it's important to be aware it's NOT
| exactly the same thing most normal people mean when they
| say "productivity".
| jurgenburgen wrote:
| I've noticed more gold-plating.
|
| "This random part of the code is slow, I used an LLM to
| generate a PR that speeds it up."
|
| Okay, you optimized the part that's not a bottleneck,
| sped up nothing and cost the company $100 in tokens. Good
| job?
| w29UiIm2Xz wrote:
| Productivity is defined revenue per worker hour. And we
| know worker hours are going down as there are fewer workers
| with the layoffs.
| dzhiurgis wrote:
| That report doesn't match what faros.ai conclude which is
| mostly a paywalled report.
| gdcbe wrote:
| I do not disagree with what you are saying, but I honestly
| still believe that most of the utility we experience are
| honestly gonna become very boring very soon that we can just
| run local... Even if it's a bit more slow who cares, can just
| run in background while you work on other stuff yourself, read
| up on things, review other work...
|
| It's not that the utility of it put in question. What is
| however a giant question mark is how the heck any of the big AI
| companies are ever gonna get that ROI? Given how many of us are
| becoming more and more fine with local models that run just
| fine especially on a good enough computer which most developers
| have anyway...
| cogman10 wrote:
| Even more dangerous to the big 2 AI companies is the fact
| that the 20 different Chinese companies are catching up fast
| and for a lot lower cost.
|
| Why should someone pick Opus 4.8 when Qwen3.7 Plus produces
| similar results for about 1/20th the cost.
|
| That sort of pricing disparity is across the board. But
| further it's becoming more and more apparent that they are
| doing more with less parameters. That's what's giving the
| local models their super powers.
| remich wrote:
| Because it doesn't. Not for the tasks where using Opus
| instead of a lower tier model is appropriate, at any rate.
| Benchmarks show this, as do revealed preferences of actual
| users. To believe that Qwen is as capable as Opus at 1/20
| the cost you have to believe that every person who does not
| make the choice to use Qwen over Opus for a given task is
| some mix of ignorant or delusional. This is certainly an
| opinion you can hold about other engineers, but it's
| definitely a questionable one at best.
| cogman10 wrote:
| The benchmarks between the two are close and the
| engineers that have used both (like myself) can attest
| that the differences aren't so wide as you might believe.
|
| I'd say that yes, ignorance plays a role here because a
| decent number of engineers are looking strictly at the
| benchmarks and choosing Opus just for that reason.
|
| But I'd also say that a major factor for Opus use is
| because Opus is being purchased for the engineers by
| their employers. They don't get to pick which models they
| are using.
| danny_codes wrote:
| I find myself rarely reaching for Opus nowadays, it's
| just too slow. I assume there are tricky use-cases where
| it's really useful though, just not super relevant for my
| day to day. I much prefer a faster, "weaker" model.
| enraged_camel wrote:
| Yes. Zitron has been predicting and begging for collapse since
| 2024. It's not just his brand at this point. It's his entire
| _identity_. As such, he cannot back down, he cannot question
| himself, and he cannot accept any other viewpoint. And he will
| keep moving his goal posts until _something_ happens that can
| make him go "aha! I told you guys!!"
|
| This, combined with his extreme ignorance, makes him
| unreadable. The only reason people read his stuff is because it
| validates and confirms their own anti-AI beliefs. It's why
| every time he publishes an article, it reaches the front page
| in an hour or less.
| nozzlegear wrote:
| > _This, combined with his extreme ignorance,_
|
| Extreme ignorance?
| AlexandrB wrote:
| > undeniable, massive productivity gains
|
| How are they undeniable? They're very deniable. One example is
| the (seemingly) increasing maintenance costs for AI-generated
| code[1]. Another is the cost incurred by everybody reading AI
| slop instead of actual communication.
|
| I don't have hard data as to whether these cancel out the
| benefits, but it's not as rosy as some seem to think.
|
| [1] After years of people understanding that LOC is not only a
| poor productivity metric but also a _negative_ indicator of
| code quality (shorter code for the same thing is better), we
| now have people touting how many LOC their LLM agent is
| generating. It 's like everyone forgot what LOC actually
| represents and what it means for long term maintenance costs.
| elorant wrote:
| Even if we assume that everything you said holds true, how is
| that we as a crowd can make viable a service that eats some
| $300bn annually in infrastructure costs? Where would that money
| come from? Most tech companies these days are cutting their AI
| budgets because the per token pricing is killing them.
| aspenmartin wrote:
| Cite a real source for that last bit, I don't think that is
| true. Also the budgets _should_ be cut the spend at some
| places goes beyond any reasonable amount. The strategy there
| is to hook everything in and find the right processes, then
| cut the rest. Things then get better and better with each
| model release.
|
| The way you make a viable service that eats 300bn annually is
| to have enough demand to service that. Anthropic
| _underbought_ compute. That tells you something.
| elorant wrote:
| https://www.theverge.com/tech/930447/microsoft-claude-
| code-d...
|
| https://finance.yahoo.com/sectors/technology/articles/ai-
| bin...
|
| https://blog.pragmaticengineer.com/the-pulse-token-spend-
| bre...
| jazzcomputer wrote:
| When you say "Things then get better and better with each
| model release."
|
| How far behind are models that can be run locally, and do
| you expect that this will be widespread?
| mawadev wrote:
| I really like some good drama slop that reads like a thriller,
| it is entertaining. I don't take any of it THAT serious, but
| lately with the IPOs that are about to hit the indizes, he has
| gained a lot of attention. If you look around the internet,
| most people publish a negative angle on something and then
| extrapolate it into some grand conspiracy, which is really
| captivating. Its crazy when you enter some echo chamber you
| never engage with (movies, gaming, art/comics) and they have
| their own head cannon for why the world is bad and collapsing.
| It puts your echo chamber into perspective to see the same
| patterns of argumentation and presentation spin out in a
| different way
| frisbee6152 wrote:
| He's been continuously predicting that the collapse was just
| around the corner, that progress was slowing, and that there
| was no market for inference, since 2024.
|
| The fact he's never reflected on the glaring failures in his
| analysis tells what we need to know about his intellectual
| integrity. There's truth in some of his words about financial
| risk, but if you can't acknowledge that there's upside too, you
| can't evaluate risk properly either.
|
| I find it difficult to take him seriously.
| bdangubic wrote:
| anyone that takes him seriously at this point... I don't want
| to say very bad words here...
| solomatov wrote:
| > progress was slowing
|
| Do you think it's not slowing? Do I miss anything really
| important?
|
| My understanding is that we have now is incremental
| improvement on thinking models which appeared more than a
| year ago. Of course, a breakthrough might happen, but I don't
| see one yet.
| frisbee6152 wrote:
| The most important thing I would point to is Mythos et al
| and the wave of vulnerabilities that have been discovered
| in the past couple months. It's a completely unprecedented
| event, brought forth almost entirely by improvements in the
| models themselves. That said. keep in mind, I'm talking
| about over the past two years. With Claude code and the
| capabilities gained since December of last year, there have
| been incredible gains in the capabilities that are now
| available. Demand for inference is higher now than it was a
| year ago, because capability has improved. A specific
| criticism that I would hold is that claiming that progress
| with LLMs is slowing, prior to that point, is
| embarrassingly wrong in my view. One could argue that the
| model capability improvements are slowing, and all the
| improvements were in harnesses. I think that's a stronger
| argument, but I have a few problems with it. 1. Utility is
| utility. Whether that comes from the model or the harness
| is irrelevant when making claims about utility. I don't
| think that's a useful distinction most of the time, but
| especially when talking about the technology as a whole. 2.
| Marginal intelligence gain is different than marginal
| utility gain. It's estimated that intelligence grows
| logarithmically relative to investment. However, the
| utility of a marginally more intelligent model may grow
| exponentially, because once behavior crosses a reliability
| threshold, it unlocks new capabilities. 3. Even on those
| terms, it's not clear to me that frontier capabilities are
| slowing down. With Mythos and its contemporaries, we have
| been seeing a vast change in the security industry as
| vulnerabilities are discovered at an unprecedented rate.
| OpenBSD vulnerabilities, more Firefox vulnerabilities found
| in a single month than the past two years, critical Linux
| vulnerabilities. It's hard for me to look at the effects
| there, a radical new capabilities baked into the model
| itself, and see stagnation. A part of the reason it might
| feel like it's slowing down is because we plebs don't have
| access to the top models.
| slopinthebag wrote:
| Do you have access to Mythos?
| frisbee6152 wrote:
| Nope. Just watching the volume and severity of CVEs
| coming through since it's been running. It's been a busy
| few months.
| lompad wrote:
| The maintainer of curl - who has access to mythos -
| disagrees [0].
|
| I think it's dangerous to rely on claims made by people
| who financially profit from you believing them without
| checking.
|
| [0]: https://daniel.haxx.se/blog/2026/05/11/mythos-finds-
| a-curl-v...
| jsnell wrote:
| That blog post is very clear about the maintainer having
| no access to Mythos.
| IsTom wrote:
| Does that matter that somebody else ran it for him?
| jsnell wrote:
| When it is explicitly an appeal to authority, and the
| basis for the authority is incorrect? Feels like it
| matters.
|
| And presumably the GP thought that saying the maintainer
| had access to Mythos made it a more compelling argument.
| Otherwise why even mention it?
| frisbee6152 wrote:
| The article says in the second section that the author
| did not have access to Mythos. I think it's dangerous to
| rely on claims made by others without even bothering to
| read them first, let alone check.
|
| It found hundreds of vulnerabilities in Firefox,
| according to Mozilla: how does Mozilla benefit? It found
| a 27 year old vulnerability in OpenBSD. How do they
| benefit from that? Is that made up? Are the maintainers
| of those codebases lying for the benefit of Anthropic's
| IPO? Is copy fail a fabrication by big AI? The 12 OpenSSL
| vulnerabilities found in January?
|
| https://venturebeat.com/security/mythos-detection-
| ceiling-se... https://www.wired.com/story/mozilla-used-
| anthropics-mythos-t... https://cyberscoop.com/copy-fail-
| linux-vulnerability-artific...
| https://www.schneier.com/blog/archives/2026/02/ai-found-
| twel...
|
| Im not sure whose claims you think I'm relying on. I
| trust Firefox that they're not overstating the number of
| CVES they've found. Same for OpenSSL. The OpenBSD folks
| definitely don't seem like the types. I've not known
| Linux to fabricate CVEs either. I think my sources are
| fine.
| dofm wrote:
| Progress _is_ slowing, in an important way.
|
| Have a muck about with what Qwen 3.6 or Gemma 4 can do and
| you'll see. I mean this as an illustration but Qwen just
| isn't as far behind as I expected, and compared to the data
| centre hardware it will run on a potato.
|
| The frontier models are losing their undeniable edge over
| that which is unmetered.
|
| And even putting aside my optimism for the smaller open
| weights models, there's a huge amount of scope for the
| larger, hosted open weights models that are only just behind
| the cutting edge and which cost, what, 1/25th of the price on
| opencode go, openrouter etc.
|
| Commodification is coming, and with it slimmer profit
| margins; it's hard to see them making anywhere near the kind
| of money they need to in a commodified market.
| mschuster91 wrote:
| > He's been continuously predicting that the collapse was
| just around the corner, that progress was slowing, and that
| there was no market for inference, since 2024.
|
| Old WSB saying: The market can remain irrational for (far)
| longer than one can remain solvent.
|
| And unfortunately, _a lot_ of the market on the "buyer" side
| has been acting irrationally. When you see CEOs telling their
| employees that they don't care about token cost, only about
| "how much AI do you use" because that is what the stock
| market wants to hear - that's when you know we're all getting
| cooked, the question is how long it takes until the bubble
| bursts.
| freejazz wrote:
| Every day people here debate whether or not there are any
| actual productivity gains from LLM, and it's only in the
| limited context of software development. While I understand
| that this place obviously skews heavily towards the software
| industry, the notion that LLMs are anywhere near as useful in
| other industries is hubristic (at best).
| remich wrote:
| Perhaps they aren't, but not currently viable !== always
| unviable.
| 48terry wrote:
| Just 5 more years and $500 billion more, bro. We're still
| so early.
| freejazz wrote:
| And?
| amlib wrote:
| Is it really worth it to cause a global economical collapse
| and harm society well-being to an unimaginable degree just
| to find out if it is viable?
|
| Why cant it naturally grow and prove it's worth?
| dist-epoch wrote:
| > Zitron is begging for a collapse at this point
|
| No, he's not, he's making tons of money every month from his
| Substack subscriptions. In fact, the AI bubble popping would be
| the worse thing ever for him, he would be out of a job.
|
| Just like the who have predicated the US dollar will collapse
| any-moment-now and which pushed gold for decades.
|
| Funny how people always say "oh, you are an AI lab, of course
| you are going to hype AI", but never "oh, you make sooo much
| money from predicting the collapse of the AI bubble..."
| spmurrayzzz wrote:
| He has also consistently demonstrated, at least to me, that he
| doesn't really understand how inference works from a technical
| perspective, which weakens much of his core thesis for why
| there should be a collapse.
|
| I do value having some naysayers in the mix generally, because
| we do need balanced critique in what is otherwise a very frothy
| hype cycle. I just don't think he's making sound arguments, and
| that's even assuming you even agree with his premises in the
| first place.
|
| My biggest gripe with his napkin math is that he treats
| inference gross margins as something novel that you can't
| compare to normal SaaS margins. He's right in part: the
| constant carousel of R&D costs from model training, related
| infrastructure buildout, and other adjacent costs required to
| stay competitive do change the analysis a bit.
|
| But he takes this way too far when he says this is structurally
| different from normal SaaS margins. The business model
| definitely doesn't look like Dropbox, but it absolutely looks a
| lot like AWS, especially early AWS, CDNs, telecom, etc. I can
| speak to the telecom bit personally, since it's been over half
| of my professional career as an engineer and, in this specific
| case, also as a founder. You can have a brutally capital-
| intensive infra business where profitability depends on
| utilization, oversubscription, peak-capacity planning,
| segmentation, and recovering capex over time.
|
| The math he presents gets even more questionable as we see
| explicit segmentation happening for cost-saving reasons. Many
| forward-thinking orgs are waking up to the fact that they don't
| need to use the best, most expensive model for every task. They
| can route easier tasks to cheaper models, use caching, batch
| non-urgent workloads, and reserve frontier models for the
| subset of work that actually needs frontier intelligence. That
| directly undermines his claim that providers always need to
| chase frontier intelligence in order to maintain current
| demand, utilization, and pricing curves.
| solomatov wrote:
| > that he doesn't really understand how inference works from
| a technical perspective
|
| Could you share what tells about it? I.e. where he was wrong
| about it?
| spmurrayzzz wrote:
| There's examples both in his writing and also in his
| appearances on podcasts, interviews, etc.
|
| I'll cherry pick a couple:
|
| "When these new models 'reason,' they break a user's input
| and break into component parts, then run inference on each
| one of those parts." [1]
|
| This is not at all how test-time compute works. At best,
| this is a very loose metaphor that he may have used out of
| convenience. This might sound a bit pedantic to point out,
| but this is a very basic thing that he's getting wrong
| (presumably at least, again it could be that he just used a
| poor metaphor).
|
| A less pedantic example would be his claims related to
| gpt-5/chatgpt auto-routing. He argued that having a router
| means OpenAI can no longer cache static prompts, because
| the user prompt has to come before the hidden instructions
| [2]. This is just not at all how this works at inference-
| time. There is no evidence that the standard approach of
| system>developer>user instruction hierarchy has changed,
| the public API and caching docs maintain this.
|
| But even more broadly, it suggests he is reasoning about
| kv/prefix caching at the wrong level of abstraction. It's
| true that conventional prefix caching does require a stable
| prefix, so yes, if you literally put variable user content
| before the static prompt, you would destroy the
| cacheability of that static prompt.
|
| But that is exactly why inference systems are designed to
| preserve reusable prefixes where possible (via
| checkpointing or similar), and why serving systems care so
| much about prefix caching. This is also a big part of how
| disaggregated prefill/decode infra works where cache-aware
| routing is critical. His argument treats a bad prompt
| layout as if it were a necessary consequence of routing,
| rather than an avoidable implementation choice.
|
| A router can read the user request, decide which model path
| to use, and then construct a normal downstream model call
| with stable static instructions first and user content
| later. Treating that as impossible implies a fundamental
| architectural misunderstanding.
|
| [1] https://www.wheresyoured.at/how-to-argue-with-an-ai-
| booster/
|
| [2] https://www.wheresyoured.at/how-does-gpt-5-work/
| pluto_modadic wrote:
| I think he doesn't need to understand the technology to point
| out the books are cooked. a business can sink in either way:
| the technology flops or the finances flop. he's arguing the
| /finances/ would flop. he doesn't argue that the /technology/
| would flop, only that they can't come up with the money to
| pay their debters.
| spmurrayzzz wrote:
| There is a piece of this I agree with. That you do not need
| to be a deep technical expert to notice that a company is
| burning cash by overcommitting to capex, or relying on
| heroic revenue projections that may or may not come to
| pass.
|
| But that is not the full argument he is making. If the
| claim is that the labs will not be able to pay their
| creditors because inference is structurally incapable of
| becoming profitable, then he absolutely needs to be right
| about the technical economics of inference.
|
| One part of that is the balance-sheet argument (which
| already shows insanely good margins). But it also depends
| on how inference-time compute actually works: routing,
| batching, kv cache reuse, model segmentation, different
| latency tiers, etc. Much of those details he's just been
| straight up wrong about in his writing, so as a result I
| have to call into question the rest of his reasoning as
| well (in part to avoid Gell-Mann amnesia).
| beepbooptheory wrote:
| Doesn't this kinda imply its own smoke and mirrors
| though? Like if the name of the game with inference is
| already routing things around and caching so you can make
| money, why is the newest biggest model always the most
| important critical thing? How does this square with any
| of their press about it? Also wouldn't that just add
| _more_ inference? Because you need to pre-judge every
| prompt to know where to route it?
|
| Also, if there _is_ significant gains from caching, then
| like.. what are even doing here? Inputting something and
| then reading cached pieces of text based on their
| similarity to the input? Kinda like a search engine?
| dofm wrote:
| > That directly undermines his claim that providers always
| need to chase frontier intelligence in order to maintain
| current demand, utilization, and pricing curves.
|
| But does it also not mean that they will _make less money_
| given that there is already _brutal_ competition for that
| lower tier from openrouter, Deepseek, Amazon, etc.?
|
| You can't on the one hand say "customers are beginning to
| understand they can spend less" and on the other hand suggest
| that this is good for forecasts of revenue.
| cm277 wrote:
| Agreed that he has an extreme POV (or more accurately that he
| trolls for views/subscriptions). But his central argument is
| valid: if AI underdelivers financially, this bubble will burst
| and this bubble is magnitudes larger than what we've seen
| before, so there could be very rough seas ahead.
|
| The question is: what does "underdeliver" mean here? the pro-AI
| arguments I am seeing in this thread are equating mass adoption
| to agentic coding. Er, I dont know of any _trillion_ dollar cap
| companies that sell dev tools. The point is Zitron doesn 't
| have to be 100% right for his central prediction to come true.
| aspenmartin wrote:
| I don't get this. We already have an insane demand. And yes
| exactly, this is primarily _just_ with coding agents, but are
| you aware of what's coming down the pipeline? It's not hard
| to be you just have to find a decent way to keep up with
| literature.
|
| * robotics (need to close data gap and release first viable
| product to get a data flywheel)
|
| * conversational ai (no one is ready for this and we're
| getting closer and closer to natural speech. The quality
| still isn't good enough but it'll be soon).
|
| * other agentic use cases, openclaw adoption was crazy and
| that had a ton of barriers to entry
|
| * ai products, like the one OpenAI is working on with Johnny
| Ive
|
| Anyone thinking it's unreasonable to hit whatever revenue
| requirements is just not that aware of what's happening. Not
| to mention were capacity constrained already!! This is barely
| speculation at this point.
| sterlind wrote:
| I don't think the issue with robotics is a data gap. maybe
| somewhat, but the real issues are that:
|
| - RL is extraordinarily sample-inefficient.
|
| - distribution shift/catastrophic forgetting aren't solved.
| only off-policy learning with giant decorrelated batches
| works.
|
| - the breakout success of transformers as an architecture
| doesn't neatly translate to robot motion policy models.
|
| the field is missing fundamental breakthroughs.
|
| I also find it _very_ interesting that conversational AI
| has taken this long. where are the models with good turn-
| taking? passive listening? the ability not to respond in
| paragraphs? has Anthropic simply _not gotten around to it?_
| aspenmartin wrote:
| All of these points are great. The first one motivates
| world models which lots of labs work on. Not many people
| tend to understand the strategic value of those "open
| world" or interactive generation models: its robotics and
| planning. But also like you say you're right, there are
| complicated problems to solve and it's not totally clear
| the timeline. But where there's data and compute, there's
| a way.
|
| For conversational AI these labs do have lots of things
| to do lol but you're right; it likely also requires some
| architectural improvements but you see the infancy: look
| at the llama4 speech duplex model. Very unimpressive yet
| all of the components are there. Just a matter of pushing
| on them, licensing and commissioning better data, etc.
| takes time and compute is stretched thin.
| themafia wrote:
| > through undeniable, massive productivity gains.
|
| And where are those? They seem particularly hard to actually
| observe and only appear in anecdotes.
|
| > I'm trying to believe
|
| For every exponential increase in compute capacity you see
| linear gains in output accuracy. This is a death spiral.
| Anyways, you see "massive productivity gains" so why is
| "belief" a function of your viewpoint?
| PedroBatista wrote:
| > undeniable, massive productivity gains.
|
| The jury is still out on that.
| deaton wrote:
| Yeah they're very much deniable. Raw LOC/hr is much higher,
| and putting together a MVP, but I've yet to see any evidence
| that an LLM is capable of doing anything unsupervised, and if
| you need a human supervising everything it does... why bother
| having an LLM in the first place?
| aspenmartin wrote:
| Because it can perform much faster? Monitoring allows you
| to multitask more effectively. I would also disagree that
| you can't one shot anything...claims like this are weak and
| I have enough counter examples in my own life that it's
| trivially false. The question is more: can it one shot the
| right things with a low enough failure rate for it to be a
| good replacement. It's hard to figure that out a priori.
| toasty228 wrote:
| > undeniable, massive productivity gains.
|
| Take any stock index, remove AI stocks, what do you see? That's
| right! Nothing...
|
| So where is all the productivity going? Where is the value?
| Where are the massive unemployment stats or the millions of new
| startups making big $$$?
| moritzwarhier wrote:
| Writing about AI, destroying the planet for data centers,
| there's a lot of money to be made.
|
| That being said, AI seems kind of miraculous sometimes.
|
| Similar to cars. So enticing that we make everything else in
| the world worse in order to maximize the profit, make it
| indispensable, subsidize it, and make the dependency on it
| irreversible.
|
| And it's not even something to blame individual people for.
|
| Driving away from all the other cars to spend a weekend feels
| like _freedom_.
|
| Using AI to answer a question feels like a "bicycle for the
| mind".
|
| But in fact it's more like a car. It requires massive
| resources and creates perverse incentives, and the result is
| ineffective and corrupt.
|
| Both cars and AI are amazing technology and extremely useful,
| but using them is not an individual responsibility. It
| requires societal subsidy.
| MSFT_Edging wrote:
| Vonnegut said in his last living work that the greatest
| addiction modern people face is the drug of cheap oil.
|
| We got addicted to the convenience and overuse, and have
| started a mass extinction event because of it.
|
| The perverse incentives will come for us all.
| moritzwarhier wrote:
| It is exactly this thought, in the form of this sentence,
| that could replace almost all of my comments in this
| thread.
|
| It feels depressing, but I think the same. When thinking
| about the larger world, it becomes increasingly hard to
| ignore. And of course it is not new.
|
| There were "doomers" already in the midst of the 20th
| century, but it doesn't mean that they were wrong.
| nfw2 wrote:
| The environmental impact of answering a question on an
| obscure topic with ai model is less than an the impact of
| answering the question with an hour-long google search
| hunting for references or a drive to the public library.
| toasty228 wrote:
| It's like saying if we didn't have cheap commercial
| flights people would travel by foot anyways and would
| consume more resources for food &co. than the plane would
| consume in fuel...
|
| 80% of generative AI queries wouldn't even exist as
| google searches.
| moritzwarhier wrote:
| I do plenty of AI queries, both pragmatic ones and some
| for entertainment: witnessing talktotransformer was mind-
| bending already at the time! And since then, I've tried
| frontier models, local, coding agents, and use plenty of
| them on the regular.
|
| I awe at the capabilites of generative AI.
|
| I also enjoy sitting in or driving a car.
|
| I did not want to make a moral argument, unless you
| consider each and every form of utilitarianism as
| moralism.
| nfw2 wrote:
| To be clear, your position here is that insurmountable
| barriers to information is the preferable state of the
| world?
|
| One claim of the parent comment was that AI is
| ineffective. For the purpose of finding answers to
| questions, it is more resource-efficient than the
| alternatives, and, to your point, capable of answering
| questions that were impossible to answer via other means
| before. In what way is that ineffective?
| 16bitvoid wrote:
| No, they're saying that 80% of genai queries (aka
| anything sent to an LLM; I won't speak on the validity of
| the percentage) are not things someone would search on
| Google. It's things like trial-and-error vibecoding,
| openclaw-like agentic loops, talking to chatgpt like it's
| a person, etc. In other words, most genai queries are not
| for getting "obscure information" or even getting direct
| information at all. It's about either getting it to do
| something you don't want to do yourself, or using it as a
| replacement for someone else (junior dev, therapist,
| friend, significant other, etc).
| nfw2 wrote:
| A request that isn't asking for information isn't a query
| 16bitvoid wrote:
| That's just what some people generally use to refer to
| LLM input string/prompt/message/etc. The only thing the
| LLM _can_ do is return information...in the form of text,
| so every request is one for information.
|
| If we want to get really pedantic, every generated token
| is the answer to the query: what's the next most probable
| token in this sequence of tokens?
| nfw2 wrote:
| If "query" doesn't imply intent by the user, it ceases to
| be a useful word. You can acrobat your way to imagine a
| digital system has agency to ask a question before it
| receives bits, but then any transfer of data could be
| called a query.
|
| When I post this http request containing this reply, you
| could say my machine is querying the server to ask "what
| did you do with the message I just gave you", but then
| query stops having any useful semantic value to
| distinguish it from "request"
|
| Regardless, this is tangential. I don't disagree that a
| lot of LLM use is not in pursuit of knowledge, but enough
| of it is for me to think that preferring LLMs not to
| exist is a hard position to defend, at least without
| making the case for existential doom.
| moritzwarhier wrote:
| That's true, and I am not anti-AI. I was not only
| thinking about the environmental effects of some single
| prompt or a certain amount of tokens.
|
| Neither did I want to say that a car is always more
| wasteful than some alternative.
|
| But defaulting to the behemoth is inefficient, unless
| everyone is driven to do it: then it's in some way
| reasonable.
|
| By adding "corrupt" and "dependent", as well as the
| economic terms, I wanted to offer a broader critique and
| create an analogy, not just talk about energy usage on
| its own.
|
| What I had in mind was: it's easier to go many places
| that are a mile or less from me, by car. Because
| everything is obstructed by cars. And I'm atrophied by
| lack of movement. Best would be to drive somewhere to
| move/walk.
|
| People already do that in masses.
|
| And doing shopping by car, because everything else seems
| unbearable, also takes away your time, apart from wasting
| energy compared to more, smaller shops that would be
| reachable by foot, bycicle etc.
|
| I guess you know the argument.
|
| Today, people's thinking atrophies because their LLM is
| probably right in their summarization of some Wikipedia
| article, plus 2-3 other random sources.
|
| Or so.
|
| Using the Wikipedia search function is not expensive.
|
| But, I mostly had a bigger picture in mind than what is
| the cost of inference.
| nfw2 wrote:
| I think it's a good analogy in many ways, and personally
| I think car-centric society has a lot of flaws. I think
| the ease that AI brings to tasks may erode mental
| capabilities in the same way cars have eroded our
| collective physical health.* That said, it doesn't seem
| to me that we would be better off without cars
| altogether, despite all the related issues.
|
| I am concerned about the environmental impacts that AI
| poses, but they don't seem to me to be so catastrophic.
| Solar and battery tech has made enormous leaps in the
| past couple decades, and we will need to pivot to clean
| energy future irrespective of AI.
|
| *This said, I have become gradually more alarmed over the
| past decade at the lack of epistemological rigor in the
| general public, as made apparent through the rise of
| social media. I don't know that AI becoming a truth-
| seeking crutch for people wouldn't be more good than bad.
| moritzwarhier wrote:
| > it doesn't seem to me that we would be better off
| without cars altogether, despite all the related issues
|
| Oh my god, no. I also want the benefits of automobiles!
| They are strictly more capable than, say, trains. That's
| where I would derail the discussion completely when going
| into details, but no, I am not against cars as a
| technology.
|
| Apart from all the ethical and social arguments
| (logistics, ambulances, the elderly, etc etc). But that's
| not where I wanted to go.
|
| I was making a leap here simply because of the whole
| complex around prisoner's, dilemma, the commons, state
| economy, and so forth.
|
| Since at least ~100yrs ago, I guess cars and streets as
| the primary mode of transportation have also "won the
| vote" / are what the majority wants, so it's also an
| interesting analogy for diminishing returns maybe.
|
| Building out more car infrastructure is certainly not
| controversial where there is absolutely none but there
| are commercial or residential buildings.
|
| Anyway, lots of associations are worth considering here
| IMO. The ultimate limiting capacity here, when
| disregarding all environmental or health concerns, is
| simply space and the positive externalities (cities etc)
| around existing infrastructure.
| RajT88 wrote:
| > I was not only thinking about the environmental effects
| of some single prompt or a certain amount of tokens.
|
| Hand wringing about AI datacenter's environmental impact
| is well and good. We should keep the data centers
| accountable for their consumption and waste.
|
| I just wish the same people had been upset the last 20
| years with poor water resource management in a lot of
| areas (the west US especially) with urban, ranching and
| farming development.
|
| > That's true, and I am not anti-AI.
|
| Me neither!
| no-name-here wrote:
| The past may be past, but it's important that even now we
| point out the relative scale of resource usage,
| pollution, etc going forward of everything from cars to
| AI to golf courses to beef.
| lxgr wrote:
| That might be true, but at least I started asking way
| more questions since we've had competent LLMs.
| bloomca wrote:
| I agree with your message but not sure about the
| conclusion. Cars themselves are commodified luxury
| available (in the US pretty much required) to everyone, and
| they do need to be subsidized, both in terms of
| infrastructure and the lifestyle they require.
|
| But with AI what is the exact price? My understanding is
| that R&D is extremely expensive, but running non-SOTA
| models is not that bad. We are getting pretty close to
| models which can be useful locally in many applications.
|
| Or do you mean that at scale running them locally is not
| possible and hence the infrastructure price is in data
| centers, which will be expensive to maintain and scale for
| demand?
| moritzwarhier wrote:
| Thanks for asking an open question about my point.
|
| First, because I initially failed to answer your more
| closed questions (this paragraph is edited in):
|
| > We are getting pretty close to models which can be
| useful locally in many applications. Or do you mean that
| at scale running them locally is not possible and hence
| the infrastructure price is in data centers, which will
| be expensive to maintain and scale for demand?
|
| I don't think there's a way around making the best of AI
| capabilities with minimum price and maximum control, and
| I'd agree this is met by on-prem data centers, just not
| in a rationally targeted way.
|
| Back to my original comment:
|
| Because it (my conclusion) was not so clear, and maybe I
| just wanted to highlight some observations without
| delivering a real argument for or against things [, I
| thank you for your open question].
|
| The utility/leverage aspect for AI seems more esoteric
| than the one for cars because, apart from Chatbots, it's
| more hidden.
|
| And also, similar to cars (or many other phenomena of
| industrialization), yes, my first vague point was the
| subsidization of infrastructure. But also, the power gap:
| that's something not only associated with AI or cars, but
| with a lot of technologies we all hold dear: sewage,
| powerline, logistics, etc etc.
|
| What reminds me of cars in the current AI frenzy is the
| fixation on cementing infrastructure. And also, I think,
| a lot more people agree on, for example, some kind of
| universal right to, for example, clean water.
|
| But all of industrialization confronts people with
| questions of efficiency, inequality, and collective
| support.
|
| Most people would, for example, support a right to get a
| minimum amount of clean water when you are living and
| working in a tradionally inhabited space (if you're on
| the social-darwinist side) or at least not harming
| society (if you're more of a social democrat).
|
| And, similar to the buildup of car infrastructure, and
| the procurement of resources, space etc for maximum
| building, giant data centers can obstruct people in
| buying drinking water. Or walking outside (AI obstructs
| traditional methods of online collaboration).
| onlyrealcuzzo wrote:
| > Take any stock index, remove AI stocks, what do you see?
| That's right! Nothing...
|
| Where did all the stock gains go before AI?
|
| FAANG / MAG-7.
|
| Was everything from 2012-2020 fake, too?
| toasty228 wrote:
| They went from ~9% of the sp500 to ~35% over your
| timeframe...
| atleastoptimal wrote:
| Not sure what your point is. Stock markets are based on money
| going into securities based on estimated future value. Even
| if AI were doubling productivity at a non-AI company, there
| is more leverage to that money going into an AI company.
|
| The question is, is AI leading to massive productivity gains
| in companies that implement it? AI productivity gains take
| time to diffuse, but so far companies in the S&P 500 are
| seeing very high growth. YOY earnings growth rate for the S&P
| 500 is 21.7% https://advantage.factset.com/hubfs/Website/Reso
| urces%20Sect...
| toasty228 wrote:
| > YOY earnings growth rate for the S&P 500 is 21.7%
|
| Now remove the companies selling the AI shovels:
| https://pbs.twimg.com/media/HIAjbZxacAARHwD.png
|
| > Not sure what your point is.
|
| My point is that they're selling us Skynet and the end of
| employment as we now it, things that we shouldn't even have
| to measure to perceive the results of, yet no one is able
| to measure any of it
|
| Pointing a finger at nvidia, google, and the other few
| companies stuck in circular investment schemes that
| shouldn't even be legal and saying "OOGA BOOGA line go UP,
| UP GOOD!" doesn't count in my book
| atleastoptimal wrote:
| Is the image you provided depicting revenue, or stock
| value? My point is about revenue.
| toasty228 wrote:
| Revenues don't matter when you sell a dollar for 50ct and
| half of the deals are circular anyways
| atleastoptimal wrote:
| So you're claiming that the revenue growth of the S&P 500
| over the last few years is largely due to "selling
| dollars for 50ct" and circular deals?
| toasty228 wrote:
| Yes.
|
| https://insights.som.yale.edu/insights/this-is-how-the-
| ai-bu...
|
| > AI-related stocks have accounted for 75% of S&P 500
| returns, 80% of earnings growth and 90% of capital
| spending growth since ChatGPT launched in November 2022.
| atleastoptimal wrote:
| has it occurred to you that AI companies may be making
| huge returns because AI is genuinely increasing
| productivity and driving actual economic growth via their
| products?
|
| If all these false practices can pull revenue out of
| nothing, why doesn't every company do it? How come AI
| companies seem to be able to pull off financial magic
| that no other company can match?
|
| All your analyses still ignore the revenue point.
| dash2 wrote:
| But then why don't we see this productivity growth in any
| other statistics? In layoffs or in faster GDP growth or
| in new software products?
| Jtarii wrote:
| Charitably the lag time for this technology to have
| noticeable effects could just be ~5 years away. Similarly
| to how computers didn't have a big impact for a decade
| after they were introduced as people got used to using
| them.
| no-name-here wrote:
| Your grandparent comment:
|
| > Take any stock index, remove AI stocks, what do you
| see? That's right! Nothing...
|
| Parent comment:
|
| > Now remove the companies selling the AI shovels:
| https://pbs.twimg....
|
| From your linked image, "excluding AI stocks" is "+16%"
| (the figure with AI stocks is far higher).
|
| Your sole source says +16% excluding AI - in what kind of
| market is +16% "nothing"?
| nilkn wrote:
| The original point of the stock market was to fund gigantic
| society-level projects (like railroads). Modern VC has
| replaced some of that at smaller scales but not all of it at
| the largest scales. So this could just be the stock market
| performing the function it was designed to perform -- helping
| fund something transformative on a societal level.
| AussieWog93 wrote:
| Literally right here. eComm business turned around from
| losing money to profitable in less than 12 months after
| vibecoding a bunch of solutions to variousn problems we were
| having.
| bawolff wrote:
| > Take any stock index, remove AI stocks, what do you see?
| That's right! Nothing...
|
| I mean, do you know what the value of those stocks would be
| if AI didn't exist. Maybe they would be much more negative.
| Maybe we would be in a recession. Without a control this type
| of analysis is meaningless.
|
| And that is even assuming that AI productivity gains are
| happening now instead of 5-10 years from now.
| trimbo wrote:
| > So where is all the productivity going? Where is the value?
|
| Infrastructure doesn't produce value overnight. How long did
| it take the Interstate System to provide measurable value? I
| asked Gemini. Supposedly increased national productivity by
| 25% over 39 years[1]. But if you drove on a newly finished
| interstate in 1959, you saw the same cars just moving a lot
| faster.
|
| That's what we're seeing right now. People can produce an
| incredible amount of stuff really quickly with AI. Is it
| directly connected to measurable productivity across the
| entire economy? No, because, realizing a mass productivity
| increase from infrastructure takes time.
|
| [1] - https://www.richmondfed.org/publications/research/econ_
| focus...
| bakugo wrote:
| > undeniable, massive productivity gains.
|
| Just because you keep repeating something doesn't make it an
| undeniable truth.
| lbrito wrote:
| >undeniable, massive productivity gains.
|
| How can something so undeniable have zero scientific evidence?
| Are there any large peer reviewed or meta studies confirming
| your claim?
| aspenmartin wrote:
| It's a very hard experiment to run. You have a population
| that's already "treated". You can't blind them to the fact
| that they're using AI tools. It's hard to imagine a study
| that wouldn't have serious flaws that people would then use
| to dismiss and form their own conclusions. Sure you have METR
| but that was very low n with a very old model.
|
| I think the surest sign of productivity gains is the sheer
| volume of adoption. If you look beyond headlines, adoption is
| just incredible. Of course adoption does not necessarily
| point to productivity gains, but if this was some sort of
| FOMO or smoke and mirrors you would not see this much
| retention and this feverish a pace of adoption. You would not
| see a large segment of the profession using coding agents
| exclusively. All of these companies track productivity, again
| with imperfect proxies, yet everything points to a pretty
| consistent picture. Same with benchmarks, again a lot of
| crappy benchmarks but a lot of high quality ones too and a
| very diverse collection of tasks and capabilities they probe.
| 48terry wrote:
| Your second paragraph appears to be 3 different instances
| of saying "X does not necessarily point to productivity
| gains... but in the case of AI, X definitely means
| productivity" without really saying why that is true or why
| other explanations do not fit.
|
| Adoption meaning productivity supposes there are no other
| dominant factors for the AI push nor AI retention. It is
| possible for practices to be picked up or continued in
| spite of causing productivity DROPS. What studies have
| suggested are factors that make for productive work
| environments and what is actually enforced in the workplace
| are different things.
| aspenmartin wrote:
| It's 3 different weak but complimentary proxies. We form
| beliefs from imperfect evidence and I find these fairly
| convincing when it's hard to find any hard evidence of no
| productivity and exactly the scenario you would expect
| under the hypothesis that we do see productivity gains.
| None of this is supposed to be unassailable. I would
| challenge then if you disagree what the evidence you have
| for this is?
|
| Adoption implying at least some significant productivity
| gains doesn't contradict there being other factors.
| You're seeing entire companies _reshaped_. The argument
| is this is all for show or CEOs are in some sort of idiot
| class?
|
| "It is possible for practices to be picked up or
| continued in spite of causing productivity drops" well of
| course. I just find that incredibly far away from Occam's
| razor.
|
| My point is: we have lots of evidence that's highly
| consistent with real productivity gains, and I don't see
| many pieces of evidence to the contrary.
| overgard wrote:
| Sheer volume of adoption is fairly forced though - "use it
| or you're fired, and tokenmaxx the hell out of it". Most
| the people I know outside of tech don't seem to be
| particularly captured by it, if they use it at all.
| _aavaa_ wrote:
| Because even in a field like software engineering where the
| output of our work is save in version control, measuring
| baseline productivity is _hard_.
|
| LoC: people argue it's not what's important
|
| PRs/day: same as LoC
|
| Getting projects done faster: oh but what about the quality.
|
| Solve the technical problems and actually be more productive,
| the social systems build around the old way of doing things
| will hole you back.
|
| Finish a PR in 10 minutes doesn't matter if you're waiting
| days for a human review.
| demorro wrote:
| They are absolutely deniable. Huge swathes of people deny them.
| dofm wrote:
| He has recently made the very good point that actually, the
| FAANG companies are struggling to put _any_ ROI numbers on that
| incredible ground-level utility.
|
| Uber, for example, is so unclear there is any ROI, they are
| cutting their exposure pretty radically.
|
| He points out that one single Anthropic customer -- a payments
| provider -- accidentally had to pay Anthropic $500M for _one
| month_ of token spend.
|
| That is half what Apple is reportedly paying Google for the
| supply side of their entire consumer AI strategy.
| squidsoup wrote:
| It doesn't matter under Capitalist Realism, the banks were
| bailed out, the AI companies will be bailed out, and you will
| pay for it. There is no alternative.
| HerbManic wrote:
| I'm not sure if they would be bailed out. The government
| tends to help with bank bailouts as they are essentially
| the hemoglobin of the economy, I see this being more like
| the dot-com bubble were they will just let it fall and have
| the bigger more entrenched player pickup the scraps for
| cents on the dollar.
| Leynos wrote:
| I quite like my mechanical spider from Wild Wild West and the
| coffee it makes with a 50% success rate
| zachthewf wrote:
| Before you spend 20 minutes reading this article, it's worth
| understanding that the writer has been posting popular but
| consistently wrong takes for 2+ years (e.g.
| https://www.wheresyoured.at/peakai/ from March 2024) arguing that
| AI is failing, is a waste of money, is bad, will never work, etc.
| ericmcer wrote:
| Yeah they seem clickable because anything Anti-AI is a bit
| soothing right now, but he is constantly wrong and usually is
| pushing the angle of "these businesses aren't even profitable!"
|
| Instantly close the tab as soon as the popup to subscribe to
| his newsletter pops up.
| jimmaswell wrote:
| Why is anti-AI soothing?
| recursive wrote:
| For some of us it is, I suppose as an alternate view to AI
| booster-ism, particularly if you think the long term
| effects would be mostly negative.
| simonw wrote:
| Because there are still a _huge number_ of people who would
| be very relieved if the whole AI thing just went away.
| raziel2701 wrote:
| It's seen as an existential threat to young people. If you
| can't get a job you starve.
| Jtarii wrote:
| Gen AI is strictly bad for society.
| jimmaswell wrote:
| Can't really agree. It's improved my life more than any
| other single innovation made in my lifetime.
| Danox wrote:
| They ain't profitable yet. Most of the model maker's will be
| gone soon. It's unsustainable unless you're Google who has
| other income coming in to support their hobby, and the
| Chinese model makers are spending a fraction to be six months
| behind and many of them will be there for the long-term
| because they have backup support (government) who is in the
| race for the long-term.
|
| One other thing that's working against the model makers is
| the hardware is getting better and the models are getting
| smaller and more capable. I don't think we're going back to
| the mainframe days. Local will be the endgame.
|
| Is Ed right? Probably because in the end it's unsustainable
| the companies left will be the companies that have income
| coming from somewhere else and there's one large tech company
| that isn't even participating in the boondoggle unless you
| count $1 billion dollars a year as participating ultimately
| there is no moat in AI model making.
|
| Nvidia and Microsoft trying to introduce another Arm
| processor in a laptop of all things won't change the tide
| either.
| __alexs wrote:
| The quality of AI doomerism takes is matched only by the
| quality of AI boosterism takes. Ed's kind of interesting as a
| temperature sensor but I don't feel like you can really take
| anything he writes seriously.
| root_axis wrote:
| Can you point to anything specific from the article that you'd
| describe as consistently wrong? Not disagreeing with you, but
| nothing popped out to me after skimming the article.
| zachthewf wrote:
| I didn't read the posted article (I don't read this author
| anymore because I think it's basically anti-AI ideological
| propaganda).
|
| But from the article I linked back in March 2024:
|
| "Generative AI models are expensive and compute-intensive
| without providing obvious, tangible mass-market use cases.
| Murati and Altman's futures depend heavily on keeping the
| world believing that development and improvement of their
| models' capabilities will continue a rapacious pace of
| progress that has unquestionably slowed, with OpenAI
| admitting that GPT-4 may be worse on some tasks.
|
| As I've written before, hallucinations are a feature not a
| bug. These models do not "know" anything. They are
| mathematical behemoths generating a best guess based on
| training data and labeling, and thus do not "know" what you
| are asking it to do. You simply cannot fix them.
| Hallucinations are not going away."
|
| Since then:
|
| - hallucinations are dramatically less of a problem
|
| - several mass market use cases have emerged, most notably
| coding
|
| - rate of progress has increased
| Capricorn2481 wrote:
| > several mass market use cases have emerged, most notably
| coding
|
| Most notably? This is not a mass market use case in the way
| the author is describing. They are asserting that the
| amount of spend they need to get this off the ground
| necessitates the entire world coming in on it, and I would
| say that opinion has aged pretty well. There are a lot of
| coders, but there are more people scratching their heads as
| AI is shoved into every part of their lives.
| mashlol wrote:
| Has rate of progress increased? How does one measure that?
| Genuinely curious - would be very interesting to map out
| the "effectiveness" of each AI model vs how long it took to
| train/release.
|
| From my perspective, the model gains are mostly incremental
| now and a lot of the gains are just from things like
| improving the agent harnesses. I could be wrong though.
| _aavaa_ wrote:
| On the front page right now is the newest announcement
| from Xiaomi serving large model at over 1,000 tok/s on
| standard server gpus.
|
| Every facet of the field is being pushed on and advanced
| at the same time.
| bigstrat2003 wrote:
| > hallucinations are dramatically less of a problem
|
| No they aren't. The models still hallucinate just like they
| always did. You cannot trust them, ever, to get something
| right.
|
| > several mass market use cases have emerged, most notably
| coding
|
| They aren't really useful for coding based upon the above.
| Since you can't trust them, you have to carefully review
| everything they make, which in turn destroys any
| productivity they could've given you.
|
| > rate of progress has increased
|
| I have yet to see _any_ progress. Opus 4.8 that you get
| today is no more effective than GPT-3.5 was. Much less
| would I agree that the rate of progress has increased. Only
| hype has increased, but there has yet to be a drop of
| substance.
| root_axis wrote:
| I think the points you raise are reasonable signals to
| consider, but I don't think they show the author being
| "consistently wrong". The overall thesis still remains
| plausible even though we have seen LLMs continue to
| improve.
|
| > _- hallucinations are dramatically less of a problem_
|
| Sure, but it remains a big enough problem that human
| intervention and review is still necessary for any serious
| work across all use cases and industries.
|
| > _- several mass market use cases have emerged, most
| notably coding_
|
| Coding seems to be the only one, but there are still a lot
| of open questions about how the market can sustain the
| costs, and that's without considering the market dynamics
| that could emerge once costs are lowered enough that open
| source models start to become an attractive option.
|
| > _- rate of progress has increased_
|
| Debatable.
| SlinkyOnStairs wrote:
| > Sure, but it remains a big enough problem that human
| intervention and review is still necessary for any
| serious work across all use cases and industries.
|
| Another important consideration: Hallucinations getting
| less common/severe but not (as-good-as) solved makes them
| _worse_.
|
| LLMs used to very obviously get things wrong. _And people
| wouldn 't trust them_. Now they're good enough that
| people blindly trust them.
|
| Now people just directly PR AI output with little to no
| manual review. We even have clowns calling for the
| complete abolition of directly human-authored code.
|
| Whatever gains were had in better AI code output over the
| past two years I lose in having to review much more
| thoroughly.
| raziel2701 wrote:
| Hallucinations are still a problem. I recently asked one to
| give me a quote from a book, figuring that since these AI
| companies have pirated all books in existence surely it can
| just recite a specific passage no? It hallucinated the
| quote, I had even told it what chapter it was in. Had I not
| read the book recently maybe I would've believed the
| hallucinated quote.
|
| And it got me thinking, they sell these AIs as assistants,
| but it couldn't even look up a passage from a book. This is
| basic, elementary stuff, it should get it right. I would
| have fired this assistant right away if it were a person.
| Not only did it get it totally wrong, it came to me with
| utmost confidence that this is the quote from the book.
| Unreliable assistants? That's the product they're trying to
| sell? Get out of here with that trash. I can't trust it.
| lowbloodsugar wrote:
| His point is that coding is only a "market" because it is
| being sold at a loss. Businesses have to pay per-token
| prices and are saying that the cost is not justified.
|
| Nevertheless, it all misses the point if we get to AI post-
| scarcity utopia. But thats a big if.
| sumeno wrote:
| It doesn't miss the point because if we get to some AI
| post-scarcity utopia then the companies pouring trillions
| into it now are never going to make their money back on
| that investment.
|
| The only way they make their money back is if everyone
| pays them tons of money for it.
| azakai wrote:
| Not the person you are responding to, but here:
|
| > I believe that artificial intelligence has three quarters
| to prove itself before the apocalypse comes, and when it
| does, it will be that much worse, savaging the revenues of
| the biggest companies in tech. Once usage drops, so will the
| remarkable amounts of revenue that have flowed into big tech,
| and so will acres of data centers sit unused, the cloud
| equivalent of the massive overhiring we saw in post-lockdown
| Silicon Valley.
|
| We have seen 8 quarters since. Has any of that come to pass?
| phkahler wrote:
| Even if you see a real bubble or catastrophy in the making,
| predicting when it will pop is a fools game.
| simianwords wrote:
| if you can't predict when it will pop then you should
| really not predict anything. I can also predict that
| Google will pop. I won't tell you when but I'll tell you
| that it will. I'll remain thoroughly unfalsifiable and
| I'll keep pushing the dates.
| simianwords wrote:
| https://news.ycombinator.com/item?id=48447549
| gdcbe wrote:
| What if you phrase the question from "will AI ever be useful"
| (a term as utterly vague as "IT") to "will it ever be able to
| promise the financial gains these companies are hoping?
| Especially with local models eating their lunch :shrug:
| freejazz wrote:
| And its been 3 years of AI boosters telling me that my job as a
| litigating attorney will not exist in 2 months. Yet here I am,
| gainfully employed.
| themafia wrote:
| > Before you spend 20 minutes reading this article, it's worth
| understanding that the writer has been posting popular but
| consistently wrong
|
| So, judge the book by it's cover?
|
| > arguing that AI is failing, is a waste of money, is bad, will
| never work, etc.
|
| Then the opposite should be easy to prove. AI is succeeding, is
| efficient, is universally good, and is working everywhere it's
| tried. Are those true?
| gilbetron wrote:
| > So, judge the book by it's cover?
|
| It is literally judging the book by it's author, which is an
| extremely rationale judgement to make.
| themafia wrote:
| > It is literally judging the book by it's author
|
| How is that better?
|
| > which is an extremely rationale judgement to make.
|
| So it's "rational" to take bias into reading? Why even
| read? If you know what you think and refuse to accept new
| information then what purpose is there in consuming
| anything?
|
| You should just read the comments and get a warm fuzzy that
| the crowd, for the time being, agrees with your
| intentionally static ideology.
|
| Comments like these obviously hope they can sway the crowd
| before they can take an unbiased reading of the article. If
| the author is that wrong then the crowd here should be able
| to discover that on their own. If the author convinces the
| crowd then I'd think you'd want to present a better
| argument than "well, he was wrong _before_." Post hoc, ergo
| propter hoc, in action.
| bigstrat2003 wrote:
| That's the exact opposite of rational. It is, in fact, a
| formal logical fallacy (ad hominem). His argument can be
| correct even if he himself is not typically correct.
| supern0va wrote:
| On the surface, that's quite fair. However, there's one
| problem: it is much easier to make statements than to
| verify them, and that asymmetry is part of why the
| internet has been slowly eroding society.
|
| It's useful/necessary to use past writing/arguments from
| an author to say whether they should actually receive any
| further critical evaluation, or be dismissed. We
| shouldn't say definitively "they're always wrong, so
| they're wrong now". However, it's reasonable to say: the
| author has a demonstrated lack of credibility, so we can
| probably assume they're wrong here, particularly if they
| have been wrong in this domain so many times before. Or
| if they happen to be correct, it's probably not strongly
| demonstrated by their work.
| adampunk wrote:
| What's the point of reading someone's writings on a
| subject where you know they're not typically correct? How
| would we know what we 'learn' from Ed is right?
| asveikau wrote:
| Not sure where I heard this, but I'm reminded of a story about
| someone predicting the dotcom crash early, circa 1998. For 2
| years they were demonstrably crazy, and missed out on massive
| stock market gains. Then they were right. (And yes, tech slowly
| bounced back after that.)
|
| Predicting the timing of such a thing is notoriously difficult.
| I don't think being wrong about timing 2 years ago means there
| won't be a correction.
| abaymado wrote:
| Not related to AI but, I recently rewatched "The Big Short"
| and your comment reminded me of it. I can't testify the
| accuracy of the movie, but for over year, Michael Burry was
| viewed as in the same manner for shorting the market, while
| the economy was was in a hype cycle.
| deaton wrote:
| Burry of course has famously predicted 40 of the last 5
| crashes, so maybe not the best example.
| loeg wrote:
| And lost his shirt doing it. (Or, well, his investors'
| money. I'm sure he's fine.)
| https://www.reuters.com/sustainability/sustainable-
| finance-r...
| asveikau wrote:
| This is like the old quote, "the market can stay
| irrational longer than you can stay solvent"
| nostrademons wrote:
| I'm also reminded of all the HN posts from 2007-2009 that
| predicted that the adoption of social networking would be a
| terrible thing for privacy, that it would destroy society,
| that people would lose their jobs over crazy shit they said
| on the Internet, that it would lead to the decline of trust
| and in-person interactions, that people would forget how to
| socialize, etc.
|
| They were right about all of that but it took 15-20 years and
| the companies involved grew 100x in that timefold, eventually
| reaching trillion-dollar valuations that would've seemed
| insane in 2007.
|
| There is a tremendous amount of money to be made in
| destroying society.
| mike_hearn wrote:
| Eh, you can find HN posts predicting that literally
| everything will destroy privacy/society/trust/etc.
| Predicting doom is a popular pasttime.
|
| What I remember from that time period is people predicting
| that we were in a tech bubble driven by social media, that
| obviously Facebook and LinkedIn were overvalued because
| social media was a trivial fad, and so on. Example article
| pulled at random:
|
| https://theconversation.com/linkedin-is-floating-on-air-
| or-i...
|
| And yet there was no bubble, these companies did fine and
| Meta became a financial Godzilla.
| nostrademons wrote:
| They weren't wrong. We were in a tech bubble driven by
| social media. Digg, StumbleUpon, Kongregate, MySpace,
| Orkut, Slide, Meebo, Mahalo, Bebo, Justin.TV, etc. aren't
| exactly around anymore. Facebook and YouTube are the
| winners.
|
| Anyone remember this video?
|
| https://www.youtube.com/watch?v=I6IQ_FOCE6I
|
| How many of the logos that scroll by there still exist?
| asveikau wrote:
| I was definitely around when that video was current, but
| I don't remember it. It's pretty amusing.
|
| Ironically I feel like it captures the spirit of the
| then-coming 2010s boom more than the climate in 2007,
| though some of the language it's using is decidedly pre-
| mobile and more "web 2.0"-ish.
| zachthewf wrote:
| I'm open-minded to arguments about AI being a financial
| bubble and a bad business.
|
| I'm not open-minded to arguments about utility, given that I
| personally witnessed LLMs evolve from interesting but useless
| toys to insanely helpful tools I use every day.
| asveikau wrote:
| I guess one of Zitron's arguments is that the utility you
| see today is based on subsidized costs, that if you had to
| pay more it might not be worth the tradeoff to you.
|
| So the claim is the cost isn't coming down enough to make
| it make sense for a lot of uses in the long term. When I
| hear that next to the most wild claims, some by influential
| people, that the entire white collar workforce is going to
| be replaced very shortly, it's a bit of a useful reality
| check.
| degamad wrote:
| Exactly. The question is not "are people using it to do
| stuff?" because we know right now they are. Given free or
| heavily-subsidised access to powerful tools, people will
| use them.
|
| If I had someone giving me free access to cranes and
| excavators, I'd be raving about how easy it was to build
| houses now. But tomorrow when I have to pay full price
| for them, I'm going to be making very different
| calculations about return on investment.
|
| The question we need to be asking is "what is the likely
| full-price cost we'll have to pay for these tools, and is
| that cost likely to be worth paying?"
|
| What Ed's pointing to is that the full-price cost will
| have to cover the capital expenditures that have been
| invested, or the companies which risked that capital will
| go bust. That gives us a floor for what the full price
| cost will be, and that floor seems higher than the value
| being offered by the tools.
| red75prime wrote:
| > Predicting the timing of such a thing is notoriously
| difficult.
|
| So, it stands to reason that it wasn't a prediction, but a
| lucky guess (unless the alleged predictor has a history of
| correct predictions).
| Kye wrote:
| He also does PR _for_ AI companies and only really acknowledges
| this in interviews. As far as I know he never discloses it in
| his rants.
| supern0va wrote:
| I highly recommend folks read Wired's profile on him:
| https://www.wired.com/story/ai-pr-ed-zitron-profile/
|
| Tim Lee also pointed out that when Ed has posted details on
| some of his analysis, they have had some....oddities:
| https://x.com/binarybits/status/2034377838883700953
| aogaili wrote:
| Some people seem to see the world only through bubbles. But if
| you look at human history, despite the ups and downs, we have a
| trajectory; generally speaking, human-created systems evolve
| toward ever-increasing complexity, impact, and efficiency.
|
| The current wave of AI unlocked language - the tools are now
| speaking and understanding. This, on its own, is astonishing
| progress. Language is the foundation of our culture and society;
| it is the very technology that got us, as a species, to where we
| are today. To have tools that can understand, manipulate, and
| produce it is a massive leap forward.
|
| Once you see things that way, it is clear that we are not in a
| bubble; we are in a transition. Yes, there is tons of hype and
| over-investment, but the demand is real, and so is the impact.
| Unless you are deep in the tech and have that structural depth,
| it is easy to dismiss. This is like the invention of the personal
| computer, but with 100x the impact and speed.
| partiallypro wrote:
| The only "bubble" with AI is that the initial build out is
| cyclical, and many of the high flying chip stocks with no
| software arms (ala Nvidia's CUDA) will come back to Earth. I
| think anyone that thinks AI is going away or won't have massive
| impact (though maybe not in the doomsday scenario) are in
| complete denial.
| aogaili wrote:
| I share the same perspective.
| hungryhobbit wrote:
| RTFA; it's not about AI's massive impact or lack thereof ...
| it's about these businesses not having a viable business
| model that will sustain them (beyond the next couple years).
| cogman10 wrote:
| I think Zitron's problem is he's equating AI to OpenAI and
| Anthropic. I'd agree with him that both those businesses
| are in a dangerous position given how fast they've burnt
| through cash. However, that's not the entirety of the
| industry and there are a lot smaller labs doing more for a
| lot less capital.
|
| The business model does appear to be viable for these labs.
| But that viability comes because they aren't wasting a
| bunch of R&D money developing worthless products like AI
| video production.
| aogaili wrote:
| I admit, I didn't read the whole article; I read a few
| paragraphs and extrapolated the mindset from which the
| author operates.
|
| Regarding your comment about the business model--the people
| in Silicon Valley are not stupid. They know the playbook;
| we've seen it with social networks. The issue isn't the
| business model itself; it's that these companies need to
| dominate the market, and the big players are competing for
| that on a global scale. It's the exact same playbook that
| played out in financial systems and social networks, and
| now it's happening with AI. Once these technologies are
| deeply integrated into enterprises and the global economy,
| these players will dominate the market for decades to come.
|
| I can assure you, the people running those companies are
| smarter than you, me, and the author of this article."
| partiallypro wrote:
| I did. So, I'm confused how does that negate my comment
| exactly? Your second complete sentence totally is in
| conflict with your first btw.
| cogman10 wrote:
| What I suspect isn't that AI goes somewhere, but I do think
| that the cutting edge companies like Anthropic and OpenAI are
| in a very precarious position. They don't have very much of a
| moat and the competition has been catching up quick while
| spending a lot less doing so. IMO, the main thing keeping
| them alive right now is name recognition.
|
| If I were to make a prediction, it's that ultimately these
| cheaper models are going end up eating their lunch. I don't
| think they'll make back the money they've invested and once
| that reality hits investors, those two companies are sunk.
|
| That, however, is not the end of AI. Nor will it be the end
| of Nvidia/micron/etc. It will more just be a localized bubble
| pop that doesn't eliminate the product from the market.
| aogaili wrote:
| It is not just about cheaper models; it is about
| integration with the economy.
|
| These models are building deep integrations into companies
| and the entire economy. Once that stabilizes, it will be
| like the electricity grid--pumping tokens to fuel decision-
| making across the entire global society. Good luck
| unplugging from that.
|
| Furthermore, there is a massive geopolitical aspect to it:
| those who are already on the Western financial and
| technical stack will get integrated even deeper now.
| cogman10 wrote:
| > These models are building deep integrations into
| companies and the entire economy. Once that stabilizes,
| it will be like the electricity grid--pumping tokens to
| fuel decision-making across the entire global society.
| Good luck unplugging from that.
|
| Much like the electric grid, what we are seeing is a
| convergence on standard APIs. For example, most of these
| cheaper models are hosted using APIs compatible with
| OpenAI. It's not a matter of rewiring your electric plug
| to work with a different socket standard, instead it's
| just the process of plugging it into a new socket.
|
| > Furthermore, there is a massive geopolitical aspect to
| it: those who are already on the Western financial and
| technical stack will get integrated even deeper now.
|
| Certainly the Chinese models appear to be some of the
| best when it comes to competition, but they aren't the
| only ones. There are European models and other US based
| models which all run for cheaper.
| aogaili wrote:
| I see your point, but having worked as a consultant for a
| few years, I think most companies will opt to stay once
| things are stable. Once these systems are functional,
| nobody wants to touch them.
|
| I remember one government project where we wanted to
| migrate a system from COBOL to a modern stack. The
| requirement was for the UI to stay exactly the same as
| the old green terminal; the evaluation criterion was
| pixel-perfect proximity to the original. We literally had
| to build terminals using web tech.
|
| These models are not the same as each other. Once they
| are integrated and working, the incentive to change them
| is incredibly low. So really, the race is about who can
| integrate deeper, wider, and faster over the next couple
| of years--that is what will determine the long-term
| winners.
|
| This is the exact same playbook we saw with social
| networks. There is a reason why we have only a handful of
| them dominating globally, and guess what? It's not
| because of the tech.
| cogman10 wrote:
| > the incentive to change them is incredibly low
|
| There is no incentive to rewrite working software in
| COBOL to something else. You don't really change the
| people cost of maintaining that code all that much and
| you incur a huge rewrite cost.
|
| AI is different, it's an ongoing cost to the company. If
| that cost raises aggressively, you can bet companies will
| race to eliminate it, no matter how integrated it is.
| Companies can and do do this all the time.
|
| And the models are close, not the same, but close. That's
| what matters in LLM stuff in general. If a model is
| capable of doing the same work for less, it will be
| chosen. Especially since the switch over cost is often on
| the level of "point the tool at this URL instead of that
| URL".
|
| I get what you are saying if this were a more sticky
| concrete tech that is harder to move away from. But
| that's simply not the case for these LLMs. A big selling
| point they have is that they are super flexible.
| aogaili wrote:
| We might need to agree to disagree on this one.
|
| I don't think the transition will be as simple as just
| flipping a URL. There is an entire legal and technical
| infrastructure being built around these models and their
| integration. I think you underestimate an organization's
| resistance to change once things actually work, as well
| as the sheer complexity of making that shift.
|
| I also expect pressure will eventually drive the cost of
| running these models down. Power plants are being built,
| more capable chips are being produced, and a big chunk of
| the capital right now is being used to scale the physical
| infrastructure--the data centers and energy grid. Once
| that stabilizes, these companies will have positive cash
| flows. Again, it's highly similar to what we saw with the
| expansion of social networks, just with more aggressive
| and widespread adoption.
|
| Ultimately, a handful of companies are going to provide
| these core capabilities, just like we have a handful of
| major cloud providers right now. Why do you think this
| would change? If anything, the trend toward deep vendor
| lock-in is even stronger now.
| partiallypro wrote:
| The moat is the infrastructure and lock-in. Similar to AWS
| or anything else. Small data centers can't compete, and
| similarly people without massive compute won't be able to
| either (at least not on the enterprise level.) You might
| get a few edge models, but for huge businesses they will be
| using OpenAI and Anthropic (and Google/Microsoft/Amazon,
| etc).
|
| The biggest competitors aren't small models, they are just
| the traditional players that already have an "in" with
| enterprises. That I think will start to show its face once
| this initial round of buildout is complete, which may not
| be for another 5+ years.
| cogman10 wrote:
| > The biggest competitors aren't small models
|
| I disagree. Mainly because those small models are exactly
| what erode away the moat of needing a giant data center.
| Those smaller models have been proving themselves to not
| be far of from the SOTA models.
|
| As OpenAI and Anthropic look to raise their prices,
| businesses will be much more compelled to looking at
| cheaper models. And if the narrative is "do the same as
| you did with OpenAI at 1/20th the cost" that's going to
| sell to a lot of businesses.
|
| It certainly cuts into what exactly these companies can
| sell in general. For example, if I wanted to integrate AI
| into a product I'd almost certainly not chose OpenAI or
| Anthropic. That's because they are simply way too
| expensive and what they'd give me is a lot less. We've
| actually ran into just this. We needed a classifier for a
| lot of records, we picked a free model because, as you
| can imagine, we didn't need something as good as what
| OpenAI and Anthopic offered and free works.
| nozzlegear wrote:
| > _The current wave of AI unlocked language - the tools are now
| speaking and understanding. This, on its own, is astonishing
| progress. Language is the foundation of our culture and
| society; it is the very technology that got us, as a species,
| to where we are today._
|
| This is fire erasure
|
| /s
| aogaili wrote:
| Agreed haha! our beloved fire.
| throw4847285 wrote:
| Uhh, citations for all of these claims please.
| aogaili wrote:
| Download the tools and use them along with your head? I mean
| a lot of what I stated there is the obvious.
| aogaili wrote:
| You need citations for humanity shared history?
| simianwords wrote:
| Ed Zitron speaks to a particular type of angry tech conservative.
| He's not speaking truth or exposing anything. He's the soothing
| voice the tech nerds of yesterday year are yearning for.
|
| The angry polemic that goes on and on and on with cuss words used
| liberally is just meant to evoke emotion and cathartic resolution
| to the type of people mentioned above. Not truth.
|
| The thing is, there are a lot of people that find comfort in what
| he's writing - primarily because it's a coping mechanism against
| how quickly things are moving and a way to deal with being left
| behind. When you spend time, years, building institutional
| knowledge and making a whole identity out of it, you obviously
| will feel bad with the threat of it being commoditised.
|
| I would write against the content of the article but I find it
| easier and more illuminating to write what he has said before
| instead. Then it shows how incorrect the guy has been and with
| what confidence he keeps speaking with.
| simianwords wrote:
| I'm collecting many kinds of predictions Ed Zitron made so that
| you can see for yourself whether he has a good track record.
|
| -------
|
| > While complex, generative AI is a technology that
| probabilistically generates answers, and has no "intelligence."
| It is inherently limited by its architecture, and in turn can
| only get "better" in a linear fashion. I see no signs that the
| transformer-based architecture can do significantly more than
| it currently does.
|
| He wrote this in 2024 before reasoning models came out.
| Remember how ChatGPT was in 2024? Do you think this person is
| someone who gets predictions right?
|
| > Furthermore, I hypothesize a race to the bottom in generative
| AI will significantly hamper OpenAI's ability to expand
| revenue, compounded by the fact that we're approaching the
| limits of transformer-based architecture.
|
| He wrote this in 2024 and since then Anthropic's revenue
| increased by 160x to $40 B dollars a year and OpenAI's
| increased by 6x. Do you think this person gets predictions
| right still?
|
| > I believe we're reaching the upper limits about what
| generative AI can do and how accurate its outputs can be,
|
| He wrote this in 2024, do you really think we have reached
| upper limits? Huh?? What I'm using today is _significantly_
| more accurate and 2 tiers above what we had.
|
| > And if there are true industry-changing possibilities waiting
| for us on the other side, I am yet to hear them outside of the
| fan fiction of Silicon Valley hucksters.
|
| He says this about AI when we have with all honesty have had
| industry changing possibilities like agentic coding.
|
| > There are indications that consumers have also lost interest.
| As pointed out by Alex Kantrowitz' Big Technology newsletter,
| traffic to ChatGPT on both mobile and web has started to
| stagnate, if not decline. In January 2024, ChatGPT had 1.6
| billion visits -- 11% below the all-time peak of 1.8 billion.
| This makes it only modestly more popular than Bing, which had
| 1.3 billion unique visits during that period. On the mobile
| front, ChatGPT has an estimated 6.3 million US users -- or 1.7
| times less than the total of new Snapchat users added during Q4
| 2023.
|
| He agrees with the claim that the consumer interest has
| declined. Since he said this, there was a 9x growth in active
| users.
|
| -----
|
| https://www.youtube.com/watch?v=_wStScmT748&t=1s
|
| "AI Bubble Already Bursting?" (8 months back)
|
| https://www.youtube.com/watch?v=T8ByoAt5gCA&t=1s
|
| "A.I bubble is bursting with Ed Zitron" (1 year back)
|
| He's been constantly crying bubble for years now.
|
| -----
|
| > AI video won't get truly fixed just by waiting a year.
|
| This is what he had said in 2024, and you just need to compare
| video from then and now to check whether the predictions came
| true. Why would anyone trust what this guy has to say?
| james2doyle wrote:
| How's that meme go? "We are 2/3 years into being 6 months
| away from AI taking all white collar jobs".
|
| The criticism goes both ways. The word "fixed", in Ed terms,
| can be translated to "become a viable business that justifies
| the spend".
|
| In regards to AI video, I think the fact that Sora is no long
| around is an indicator. And there is seemingly no real
| appetite for AI video outside of memes, jokes, and
| misinformation, probably indicates that the prediction around
| AI video has come true.
| simianwords wrote:
| This website can't run if this sort of rhetoric is
| accepted: "they told lies so we can tell lies".
|
| Frankly this is anti-social and should not be tolerated
| here.
|
| >In regards to AI video, I think the fact that Sora is no
| long around is an indicator. And there is seemingly no real
| appetite for AI video outside of memes, jokes, and
| misinformation, probably indicates that the prediction
| around AI video has come true.
|
| His point was about the performance and accuracy and not
| about the community/market. He was wrong.
| Kim_Bruning wrote:
| Buried lede (if the title is the actual promise), the sources
| don't seem to back the title either. Someone with more patience
| can correct me if I accidentally missed a bombshell anyway.
|
| Edit:
|
| > If you're wondering what the story is, [...] I expect it to be
| out in the next two weeks [...] I can guarantee you it'll be
| worth it, and you'll be stunned by what I report.
|
| Ok, this takes clickbait to new lows. The headline is trying to
| sell the teaser here, with very limited meat in the middle of the
| sandwich.
| helloplanets wrote:
| Given this, his righteous anger towards craven boosters and
| grifters is pretty funny. Pot calling the kettle black.
| feverzsj wrote:
| I predict the bubble is going to pop right after the midterm
| election.
| saulpw wrote:
| Concur.
| brindleth wrote:
| Whenever I read these kind of articles about AI financials, I'm
| reminded of identical screeds I read about Uber a few years ago.
| They were angrily insistent that Uber was a scam company run by
| criminals and charlatans and could never, ever become profitable
| or make money for its investors. It was a house of cards that
| would come crashing down sooner or later, and take everyone's
| money with it. Now it's 2026. Uber still exists, has revenues of
| $50bn and is apparently a highly profitable business. I don't
| know if the original investors have made their money back yet,
| but Uber certainly hasn't collapsed.
|
| Maybe AI is different. Certainly, the level scale of investment
| is on a different order of magnitude. But I'm wary of believing
| anything about the financial impossibility of AI being
| sustainable when I've seen such similarly confident arguments
| proved wrong in the past.
| kunai wrote:
| Uber used the classic triple-E philosophy of Microsoft and
| entered a market that was ripe for disruption -- many cities
| lacked reliable taxi service entirely, others were cartels that
| fixed prices. They undercut prices to an extreme degree,
| subsidized fares, and when it either drove local taxi companies
| out of business and spurred widespread adoption as the default,
| it had a captive market and duopoly with Lyft which allowed
| them to raise fares without losing any market share whatsoever.
|
| It's a pretty classic business strategy, and not directly
| comparable to any of the AI companies. There's a reason people
| compare the current situation to the dotcom era and not Uber.
| Also, don't take Uber as an example of a slam-dunk VC success
| story and leave it at that -- plenty of dumb ideas get pitched
| and funded and go bankrupt for every Uber.
| hungryhobbit wrote:
| Yeah, people forget the risk to Uber was real in the early
| days. If municipalities had enforced their taxi laws, the
| company would have died and all those millions invested would
| have been lost (or pivoted into something else).
|
| It was only because Uber _successfully_ bulldozed over all
| regulations that it was able to succeed ... and that was hard
| to predict before it happened.
| james2doyle wrote:
| Absolutely. Even these days, Uber really only has one or two
| viable competitors. With any 3rd one in a far distant 3rd.
| Meanwhile, swapping which AI I'm using is as easy as clicking
| a dropdown. Hardly comparable to a physical car ride.
| parrellel wrote:
| I mean, do you really want to compare AI to the "do crimes hard
| and fast enough we become a monopoly before anyone can properly
| respond" model.
| marcosdumay wrote:
| Funny thing, the uber's investor results from last year only
| mentions "profit" once, in a motivating paragraph where they
| say they will be great.
|
| But it's famous for having collapsed after their IPO. It took 4
| years to get back at the same nominal valuation (not inflation
| corrected), and after all the 2020s inflation it is still at 2x
| the initial price.
| adamtaylor_13 wrote:
| Ed is an interesting character. His financial analysis of the AI
| industry makes logical sense to me (though I am not knowledgeable
| enough to actually know if it is _correct_.) However, he seems to
| be so angry at AI in general, that he misses the obvious areas
| where LLMs are actually changing the State of the Art.
|
| Coding seems to be one of the core use-cases for LLMs (as Simon
| Willison pointed out recently) and even if that's the only real
| use-case for LLMs, they're wildly useful. I do understand that
| useful != profitable and that's where I think Ed has a real
| point: until inference becomes much cheaper these companies
| cannot be profitable. Some mega-players will pay the API token
| price, but most will not.
| hungryhobbit wrote:
| I don't think whether "LLMs are actually changing the State of
| the Art" or not matters for anything he wrote.
|
| If the AI companies need $X billion in revenue to stay afloat,
| it doesn't matter if 0.5% or 5% or 50% of that revenue is from
| transforming the State of the Art. It's 100% irrelevant: what
| matters is that, transformation or no, these companies won't
| have the income to pay their bills. And if they can't pay their
| bills, a whole lot of other companies can't either.
|
| So again, transformation or no, it's still a house of cards
| waiting to collapse. The only thing that would change that is
| not more "transformation" ... it's a feature set that lets them
| multiply their current user base (or multiply how much they
| charge them) several times over.
| tom_ wrote:
| He's got subscribers. Maybe the attitude is one he's found
| plays well with them.
|
| I find it quite refreshing in some ways. Lots of people, when
| they start complaining about this or that aspect of this AI
| stuff, are wont to add in a little disclaimer that, despite all
| of the above, they actually really like AI and use it all the
| time. I assume this is to avoid the scenario of a bunch of
| pragmatic builders turning up and calmly shipping nuance in the
| comments (or whatever you call it these days when you get
| brigaded by a pile of angry keyboard warriors with chips on
| their shoulder) - and it sure is tiring having to wade through
| the equivocation.
|
| That's a criticism that'd be hard to level at Zitron! Say what
| you like about the man, but he's unafraid to appear to take a
| side.
| marcosdumay wrote:
| > Maybe the attitude is one he's found plays well with them.
|
| Kind of a self-fulfilling prophecy.
|
| What's not a problem, by the way. That's why people always
| recommend content creators to be themselves. If they try to
| be somebody else, they find their public is already busy
| following other people.
| simianwords wrote:
| > until inference becomes much cheaper these companies cannot
| be profitable. Some mega-players will pay the API token price,
| but most will not.
|
| This is often repeated but comes from ignorance mostly. You
| have * zero * reason to believe inference is costly other than
| just vibes. If you go by data and intuitions - the margins are
| high.
|
| This kind of thinking really reinforces my belief that people
| have no idea and are using this whole [AI is not profitable and
| too costly] thing as a cathartic way to deal with immense
| progress.
| lompad wrote:
| We know that inference cost is very significant, as he shows
| for example in this piece.
|
| https://www.wheresyoured.at/oai_docs/
|
| However, it needs to be said that he received those numbers.
| I personally have quite a few issues with him, but there's no
| reason to doubt his journalistic integrity. Because of that,
| I believe he reports truthfully on data he receives by
| informants.
|
| Additionally, none of the frontier models actually publicly
| talks about inference costs in anything but broad, "let's
| just forget that"-like takes. Which does not exactly spark
| confidence.
|
| I'm eagerly awaiting anthropic's public disclosure of their
| financial details. That should be rather interesting in any
| case and finally put the inference-discussion to rest.
| remich wrote:
| _No_ reason to doubt his journalistic integrity? He 's not
| a journalist for starters. He's a PR flack who does PR for
| AI startups on the side while blogging on substack. There
| is every reason to doubt his journalistic integrity.
| lompad wrote:
| The PR-thing was always openly communicated by him and is
| not some secret or gotcha. It's essentially "fleecing the
| boosters", which I fully approve of and do similarly
| myself.
|
| I'll gladly tell my customers all the most glorious stuff
| about AI and big tech while spending a significant chunk
| of the money they pay me on supporting AI-/tech-
| counterculture, such as doctorow, zitron and quite a few
| other writers, journalists and activists.
|
| It's the old "you live in a society" counter-point
| against anti-capitalist activism. Needing to make ends
| meet does not imply that your points or principles are
| meaningless, it just implies that you have no interest in
| being homeless and that way losing your chance to
| actually change things.
|
| So that's fine to me. But: I stated it for a reason,
| because I know others don't agree. I, personally,
| consider him trustworthy. You do not, and that's fine. I
| suspect we both await anthropic's Z.1, which will be able
| to settle a big chunk of the debate.
|
| If he is right, the numbers will show it.
| simianwords wrote:
| Why do you consider him trust worthy when sooo many of
| his predictions are false?
|
| https://news.ycombinator.com/item?id=48447549
| lompad wrote:
| He was right about the cost changes, which he predicted
| quite some time ago. People shouted at him that he was
| making it all up - yet it was correct.
|
| He was also right about AI-video and sora in particular
| being a fundamentally flawed idea.
|
| He was also right about the dangers and problems with the
| general inaccuracy of LLMs and people relying on it.
|
| Also about the expected triggering of ROI-checking in
| companies, such as Uber is doing now. His prediction is,
| ROI is negative. And I'm awaiting the society's consensus
| on that.
|
| The general direction seems correct to me. He's not a
| technical guy and does not have the knowledge to critique
| models on a factual basis. I do wish he'd just focus on
| the stuff he _does_ know about, which is the financial
| side of things.
|
| He is a much needed counterweight to the unhealthy hype
| going around, imho.
| oblio wrote:
| > You have * zero * reason to believe inference is costly
| other than just vibes. If you go by data and intuitions - the
| margins are high.
|
| 1. What data?
|
| 2. Intuitions = vibes.
|
| Vibes are bad when used against you, but good when used in
| your favor.
|
| Come on :-)))
| DonsDiscountGas wrote:
| It's pretty likely that inference will get substantially
| cheaper. His argument is that for these companies to be
| profitable some very major and (pre 2022) unprecedented things
| have to happen. Which I tend to agree with, except I think they
| will happen, seeing as how they've been happening for a few
| years.
| overgard wrote:
| Except inference has been getting more expensive, not less
| CuriouslyC wrote:
| Inference has been going down in price on a
| cost/intelligence basis. If you don't need the smartest
| model, there are plenty of good Chinese models that are
| dirt cheap.
| star-glider wrote:
| It seems that a certain kind of person cannot separate the
| following things: 1) I dislike AI as a technology 2) I dislike
| the people and companies that profit from AI 3) I think AI is
| useless
|
| These are three _completely separate_ positions to have. You
| can think AI is incredibly useful and also dislike it because
| it will, for example, reduce your relative status in society.
| You can love the tech but think that Sam Altman is a dishonest
| person, etc. But for some reason, most anti-AI commentators
| feel compelled to present all three arguments.
|
| Which is even sillier when you think about it, because if it's
| useless, then you really shouldn't care: the markets will
| eventually find out that it's useless, and everything will go
| back to normal, and the people you don't like will have lost
| money, so there's no point in being outraged. Of course, I
| don't really believe that they think it's useless. I _do_ think
| they 're worried about what it'll do to their prestige, though,
| and they're just hoping beyond hope that somehow everyone will
| one day "wake up" and share their belief that LLMs are just
| "stochastic parrots" with no utility, despite the fact that
| people are using them every day and can watch in real time as
| they improve.
| degamad wrote:
| > ... the markets will eventually find out that it's useless,
| and everything will go back to normal, and the people you
| don't like will have lost money, so there's no point in being
| outraged...
|
| Except that in the process of the markets finding out, things
| will not go back to normal if everyone's retirement is tied
| to the market. And in the process of finding out, things will
| not go back to normal if the hype cycle disrupts traditional
| hiring/firing decisions.
|
| If it's as bad as some of us believe, then when it falls
| apart, a lot of people get hurt as collateral damage.
|
| The market eventually found out about Bear Stearns, but a lot
| of innocent people lost their homes in the process.
| overgard wrote:
| I see little evidence that people combine all three positions
| together. You're making a broad generalization based on
| personal vibes.
| overgard wrote:
| So here's the thing. I am not generally an angry person. But
| Ed's writing really resonates with me, because for the last
| four years these people have been making a strategy of scaring
| the shit out of us while trying to ruin something I genuinely
| love (coding), while simultaneously fucking up the economy and
| multiple industries and turning the internet into slop. I very
| badly want more people to call these guys "chucklefucks" or
| whatever innovative ways he comes up with to insult them
| because they deserve far more public ridicule and disdain than
| the (captured, useless) media is giving them.
|
| So far the data for productivity in coding is.. sus. The
| productivity gains outside of toy projects are mostly anecdotal
| and it's hard to tell if those accounts are even real humans or
| just astroturfing and bots. Almost every programmer I know
| personally has a pretty measured opinion on where these things
| are useful and where they're not. The breathless hype seems
| mostly from non coders.
| hzhzhzha wrote:
| I want to be one data point seeing as this goes uncontested
| (the ones in the know don't care anymore to be honest).
|
| They are not only useful it is obvious they are. If you don't
| see it I really, really don't know what to tell you. You can
| tell yourself I am bot or shill or whatever if that helps you
| sleep but .. just trying to help out another dev here. Wake
| the F up.
| reasonableklout wrote:
| > Almost every programmer I know personally has a pretty
| measured opinion on where these things are useful and where
| they're not. The breathless hype seems mostly from non
| coders.
|
| We have polar opposite media bubbles. I see OG programmers
| all over my timeline either grieving the "end of software
| engineering" (a la Ryan Dahl) or extolling "automatic
| programming" (a la antirez).
| bilater wrote:
| every week I see this guy on HN. only forum where ppl still buy
| this c**
| tim333 wrote:
| The top twenty comments are negative about Ed. I think maybe HN
| just likes being skeptical.
| stephc_int13 wrote:
| His rhetoric is a bit obsessive and frankly biased against AI.
|
| That said, I think his voice is useful as a counter to the
| mainstream opinion.
|
| Given the amount of investments, approaching AI from the angle of
| economics seems correct.
|
| We all have some level of personal experience using AI/LLMs, both
| chatbots and coding tools, and I personally enjoy using them, but
| I am sure this experience is relevant in this discussion.
|
| I also enjoy luxury hotels, gourmet food, jet skis and
| helicopters, but this is not something I indulge in often because
| of the cost-utility ratio.
|
| The real cost of AI may or may not be lower than its utility. The
| bet is that utility is increasing while cost is falling.
| dwaltrip wrote:
| I'm so sick of people who peddle outrage for a living.
| tencentshill wrote:
| All the top comments are commenting on the author. And now I add
| this metacommentary. Probably good it was flagged.
| vb-8448 wrote:
| Zitron is in the business of _content creation_ and not
| _successful predictions_. It doesn 't matter how many times he
| (and several others around) will say _the end is here_ , they
| have to be right only once.
|
| BTW, one thing for sure he is right about are the economics, _as
| of today_ there is no way these massive investments are gone be
| paid.
| DonsDiscountGas wrote:
| For the purposes of content creation they don't even have to be
| right once
| JacobAsmuth wrote:
| Now that you mention it, has Ed ever made a single testable
| prediction that came true?
| titzer wrote:
| > This is a hysterical era perpetuated by liars, cowards,
| imbeciles, craven boosters and the easily-fooled. Those excited
| about generative AI are either the victim or the perpetrator of a
| con centered around a technology to ingratiate at the highest
| cost possible.
|
| Who writes like this? When you lead with "everyone who doesn't
| agree with me is a lying cheat coward imbecile" I think we should
| just turn the volume down on you to zero.
|
| This is breakdown in dialog. If it leads like this then I I don't
| care how accurate the critical analysis to follow is. I didn't
| read the rest of the article and don't think anyone else should
| either out of sheer disdain for this argumentation style.
| binyu wrote:
| AI has been slowing down relatively, considering its trajectory
| over the past 20-30 years. For one, even if LLM may have plateaud
| in terms of intelligence-parameters ratio, research is on-going
| on new frontiers for ML, including (but not limited to) world
| models. Other research directions are studying backpropagation
| and its physical analogies, such as equilibrium of chaotic
| states.
|
| In addition, there's a lot of research on the hardware angle and
| actual prototypes are already being built such as AI-on-chip
| Cerebra and Taalas for one.
| bazaah wrote:
| I hadn't heard of the TMobile and Brex spend caps, only knew
| about Uber's because it went viral last week. I expect we'll see
| more of that now that everyone is paying per token, and it sort
| of feels like you _cannot_ both have spending caps and require
| extensive AI usage for performance reviews -- I wonder that will
| shake out in the end?
|
| Anecdotally, $dayJob consumes Anthropic models via Azure
| subscriptions which lend themselves pretty neatly to the spending
| dashboards Ed mentions are missing from Anthropic themselves, and
| finance seems ok with the current usage, but there's no real hard
| incentives internally for AI usage either.
|
| I guess Q3-4 are going to be interesting to see where this all
| goes.
| simonw wrote:
| Ed's argument for why "AI is slowing down" rests on company
| spending caps, in particular the Uber $1,500/engineer/tool cap.
|
| I interpret the exact same evidence in the opposite direction. A
| year ago the idea that a company would spend
| $1,500/month/employee on AI tooling felt absurd, what could
| people possible want to do with AI that would cost that much?
|
| Then coding agents (and, increasingly, general purpose agents)
| happened and suddenly companies are having to set limits because
| otherwise the demand from their employees is too high.
|
| The TAM of these AI companies just leapt up to $1,500/knowledge-
| worker/month, how is that "slowing down"?
| gdcbe wrote:
| Maybe in USA in big tech where companies give absurd wages to
| engineers anyway in some states, that might be acceptable. But
| to make their ROI they need that (and more) to be spend world
| wide... no way that is gonna be a budget that is gonna fly in
| the long term...
|
| Companies love to cut costs, and just like they axe employee
| numbers at will, they will just as well make that kind of
| budget quickly dissapear the moment they realize they can go a
| different path for same or better value... Or simply because
| share holder short-term value demands it...
| simonw wrote:
| The Uber $1,500/engineer/month thing is just the _first_
| signal we have had of the price companies may be willing to
| accept. This price will clearly vary wildly across
| professions, industries and geographies.
|
| I think it's a poor number to build an "AI is slowing down"
| narrative around.
| B56b wrote:
| The problem is that $1500/engineer/month would be a pretty
| modest amount of demand for labs. OpenAI/Anthropic are
| basing their $1T valuations on the explosive uncapped
| growth of unlimited agentic token spending. On so many
| levels of the industry this growth is now priced in. You
| don't think so?
| simonw wrote:
| I don't have a particularly great answer to that question
| - I'm not enough of a financial analysis to have
| confidence in an opinion.
|
| I do however think that shouting "look, Uber capped
| pricing at $1500/engineer/month hence AI is slowing down"
| is a questionable position to take.
| famouswaffles wrote:
| >OpenAI/Anthropic are basing their $1T valuations on the
| explosive uncapped growth of unlimited agentic token
| spending.
|
| No they're not. In reality, actual 'explosive uncapped
| growth of unlimited agentic token spending' will result
| in valuations several times more than a 'mere' $1T.
| lunar_mycroft wrote:
| Uber is _not_ the only company that 's putting a per-
| developer limit on AI spending. I know this because I work
| for another one (and we have a significantly lower limit).
| You just heard about Uber first because they're high
| profile.
| simonw wrote:
| I didn't say they were the only company, I said they were
| the "first signal".
|
| The more signals the better! What cap did your company
| pick, and what geography / kind of industry are you in?
| remich wrote:
| It's also not $1,500 per month per engineer. It's that per
| month per engineer _per tool_. Which means it could easily be
| at least $3,000 (Claude Code and Cursor) or $4,500 if Codex was
| also an option on top of those two.
|
| _And_ as you have written on your blog it 's a soft cap that
| can be exceeded with justification.
| crakhamster01 wrote:
| I don't really understand _how_ engineers at Uber are hitting
| $1500 /month. Are they forced to pay API costs?
|
| My company provides employees with API keys and soft limits,
| but as soon as you approach ~$400/month they ask that you get a
| Claude/Codex Max subscription instead. Curious if it's not the
| same case at Uber.
| overgard wrote:
| Saying its going to be 1500 a month across the board is highly
| speculative. How many companies can even demonstrate that
| they're getting more than 18000 dollars a year in surplus value
| per employee by using this tech?
| JacobAsmuth wrote:
| How speculative would it have been to say that it was
| anything more than $20/mo back in November?
| 1vuio0pswjnm7 wrote:
| "Last week I went on Bloomberg and discussed the state of the AI
| bubble with a clarity that rattled even the sweatiest boosters,
| mostly because I spoke with clarity about an investment frenzy
| whipped up through hype, deceit and mythology."
|
| Bloomberg is interested in what he has to say
|
| But not HN commenters
| tim333 wrote:
| Well there are a lot of commenters so presumably some interest.
| I just had a look at the Bloomberg bit
| https://youtu.be/zbKDmkJPVvI and didn't see sweaty boosters
| rattled, just Ed doing his usual spiel - they are loss making
| and so it's all a big con. Which is kind of unproven on the big
| con bit.
| 1vuio0pswjnm7 wrote:
| "Can I Advertise On Your Newsletter?
|
| Yes! Email me at ed@ezpr.com. I have an extremely high bar both
| for advertisers and the cost of advertising on here - I have
| 84,000 subscribers and a 55-60% open rate, as well as an 8-11%
| clickthrough rate.
|
| I do not do any kind of outcome-based advertisement (IE: X
| number of people click through and you pay me Y), so any kind
| of agreement would effectively be a sponsorship. I have an
| engaged reader base and you will have to pay to get in front of
| them, as I also do not need advertising to support this
| newsletter."
|
| Maybe the "AI" companies could pay for sponsorship
|
| Would he take the money and run their ads
| putzdown wrote:
| One of the "smells" that gives away a quacky ranter is they speak
| in impassioned, "Why doesn't everyone understand this?" tones,
| but in fact their argument just doesn't flow. If Zitron's
| argument were as solid as he keeps saying it is, you would read
| it and understand it and see that it is solid. He would begin
| somewhere-statistics on AI demand, say-and then walk the
| calculations carefully over to the next step-maybe revenue needed
| for profitability by AI companies-and you could follow the
| argument. But no. He jumps. He leaps. He circles back. If the
| situation were really "Gosh why can't you see it?!"-clear, his
| explanation of the situation would be clear. It isn't, because it
| isn't.
| Terr_ wrote:
| > He would begin somewhere-statistics on AI demand, say-and
| then walk the calculations carefully over to the next step-
| maybe revenue needed for profitability by AI companies-and you
| could follow the argument.
|
| Which of the hyperlinks provided at the beginning sounded like
| what you wanted, and after you clicked it* how did it
| disappoint you?
|
| The information you are describing is stuff I would not expect
| anybody to repeatedly duplicate across periodic blog-posts.
|
| * (Yes, I'm being sardonic, but if you _did_ bother to click
| them, then I 'm legitimately interested in your answer.)
| athrowaway3z wrote:
| He's right that its all going to pop dramatically and
| catastrophically for some. But having read a bunch of his
| stuff, there are two things he's just plain wrong about and
| they make his martyrdom tone too grating.
|
| - His own objectivity - he consistently throws shade
| (rightfully) at the pro-AI side being financially 'required'
| to hold a certain world view, but is completely blind to his
| own claim to fame effecting him similarly.
|
| - He consistently claims AI can't be made to work, and tries
| to prove this by calculating with the bubble prices. Its like
| saying tulips could never be profitable in the middle of the
| mania because ships were too expensive as proven by their
| current price to use for shipping tulips.
|
| Add in the semi regular instance downplaying AI's usefulness
| contradicting my own experience and I mostly dont bother
| reading him anymore.
|
| Its not like I'll be surprised that shit hits the fan, and
| he's not going to call the 'when' any better than
| wallstreetbets or an octopus.
| hn_throwaway_99 wrote:
| Yeah, to be honest I think his take is a bit nonsense
| because it's so historically inaccurate.
|
| _Most_ hugely transformational technologies in the past
| also resulted in giant bubbles that burst, because
| investors piled into lots of companies in the hope that
| their particular company would win out. Railroads,
| automobiles, telecommunications networks, the Internet,
| etc. etc. were all hugely important, transformational
| technologies that all caused giant bubbles that burst.
|
| But Ed Zitron seems hellbent on saying AI is a nothing
| burger, and that's why the bubble will burst. But the
| latter doesn't necessarily follow from the former, and
| indeed the examples I gave show that the exact opposite is
| often true.
|
| I believe that the AI bubble will burst _precisely because_
| it is such a transformational technology. AI may not live
| up to the ways its biggest cultists like to shout ( "Feel
| the AGI flow through you!!!"), but similarly in the .com
| boom/bust there was tons of nonsense about how we'd do
| absolutely everything online, we were in a new "eyeball
| economy", whatever that meant, yada yada, yet I'd argue
| that in some ways the Internet was actually a bigger impact
| than originally envisioned, just not necessarily in the way
| that late 90s boosters envisioned it.
| alfalfasprout wrote:
| It's not entirely clear to me that the opposing argument is
| well-formed either. You constantly see numbers and statistics
| being wildly mis-used or overextrapolated.
| sigmoid10 wrote:
| I particularly enjoy reading big banners asking me to pay for a
| newsletter subscription if I "liked" the content. Not if I
| found it interesting. Not if it actually provided any value
| whatsoever to me. No, you just have to "like" it. In other
| words, it is meant to be written in an engaging way and perhaps
| reinforce your believes like an echo chamber or even stir up
| certain strong emotions. Not to convey information. So, thanks,
| but no. I'm sure this opinion blog is very well written, but I
| don't think it is more well founded than anything else in this
| sea of opinions that sports a bigger garbage patch than the
| Pacific Ocean.
| argee wrote:
| A big chunk of text asked for support on the basis of the
| article. I hadn't read the article.
|
| I scrolled down a bit to read. A popup took up my screen,
| asking me to subscribe, having read essentially nothing at
| this point.
|
| I just left. Life is too short.
| dolebirchwood wrote:
| I know the HN guidelines discourage commenting on
| "tangential annoyances" on a website, but I think this
| issue is more than just tangential and more than just an
| annoyance.
|
| When an author is this relentless in pushing you to sign
| up, there is good reason to suspect that financial motives
| are unduly driving an agenda.
|
| I counted 8 such instances:
|
| 1. In the sidebar
|
| 2. At the top of the article
|
| 3. Popup in the middle of the screen after just a couple of
| scrolls into the body
|
| 4. Several paragraphs into the article
|
| 5. At the bottom of the article
|
| 6. At the bottom of the page under the comments section
|
| 7. Popup at the bottom of the screen after scrolling to the
| end of the body
|
| 8. (My personal favorite) Click the "user" icon in the
| bottom-right corner, which you'd normally expect to open an
| AI chat bot these days, and (surprise) you're prompted to
| sign up for a paid subscription
|
| This sort of behavior just completely tanks any and all
| credibility this person may have.
| shimman wrote:
| Of things to be upset about, an independent journalist
| asking readers to pay for access ranks very low.
| Especially compared to LLM companies that are
| exacerbating the climate crisis, increasing cancer rates
| among residents, or increasing utilities for residents.
|
| This sort of behavior completely tanks any and all
| credibility this commentator may have.
| no-name-here wrote:
| Is the OP article "journalism" or more of a rant with
| self-aggrandizement about how they're so smart and such a
| good person that it makes lots of people angry?
| ccamrobertson wrote:
| Agreed. Phrases like "journalists are currently gooning over
| OpenAI and Anthropic" really put me off. It's a poor attempt at
| modern muckraking; cheeky yet offering little substance.
| dofm wrote:
| He's just a Brit, writing in a style we write in. Sweary,
| comical, red-top. The Register did it for years.
| Kiro wrote:
| I don't think you know what "gooning" means. It's edgy Gen
| Z slang and has nothing to do with being British.
| dofm wrote:
| I didn't say it was. I'm just observing that his
| muckraking style is part of a very long British pundit
| tradition. Americans have never liked it -- Intel got
| _very_ upset about The Register 's coverage of "the
| Itanic".
|
| (And he's not Gen Z anyway is he; he's among the older
| millennials. He's appropriating it for muckraking
| purposes.)
| 1attice wrote:
| Sure, but does that vibe invalidate the argument? What an
| odd time the middle of an argument is to be clutching
| pearls and worrying about prose quality.
|
| Style and vibes notwithstanding, is there anything in
| your view that wrong with the argument itself? Could a
| better or more polite writer have convinced you with the
| same shape of logic?
| Kiro wrote:
| I responded to a comment about the prose. Why are you not
| calling out that one instead?
| Jtarii wrote:
| It shows that the author has a strong negative emotional
| reaction towards AI which likely influences his opinions
| and impartiality.
|
| He is preaching to the choir, if you already hate AI you
| will love the article, if you don't hate AI already you
| will find the article insufferable.
| 1attice wrote:
| Well, we don't have to speculate as to whether there is
| some sort of emotional taint on Zitron's thinking; it's
| shot through. But again, that does nothing to damage or
| offset _the argument_, which is available for your
| inspection and consideration, and you, as a thinking
| person, are handily capable of vetting. :) There is no
| need to use a heuristic; you have the thing itself.
| ElProlactin wrote:
| > Could a better or more polite writer have convinced you
| with the same shape of logic?
|
| If you're writing in an attempt to convince people of
| something, isn't how you deliver the message of critical
| importance?
|
| This is basic Sales 101. The _way_ you sell (products,
| services, ideas, etc.) is directly related to how
| successful you are.
| sumeno wrote:
| He is not writing his blog to convince people, his
| primary audience already agrees.
|
| That doesn't make him wrong.
| ElProlactin wrote:
| > He is not writing his blog to convince people, his
| primary audience already agrees.
|
| He's selling a paid newsletter, so at least one of his
| motivations is to make money. His target subscribers are
| certainly people who lean towards his viewpoint but he
| still needs to do some convincing because the market of
| people who are open if not warm to his thesis is much
| bigger than the market of people who already share his
| thesis.
|
| > That doesn't make him wrong.
|
| I think it's way too early for anyone pontificating about
| AI, the economics of AI, etc. to be declared "wrong" or
| "right". This is going to take years, if not decades, to
| play out.
| oytis wrote:
| I'm not a Brit, but I do enjoy British culture, including
| writing. I haven't been able to read any of Ed's rants to
| the end despite generally being on the cautious side
| towards LLMs
| SlinkyOnStairs wrote:
| > He would begin somewhere-statistics on AI demand, say-and
| then walk the calculations carefully over to the next step-
| maybe revenue needed for profitability by AI companies-and you
| could follow the argument.
|
| That's exactly what the first (titled) section does?
| 0000000000100 wrote:
| Haha thought you were referring to the upsell at the start
| asking to subscribe to the newsletter for $70 / year. But yes
| it does call out the unprecedented amount of money getting
| dumped into AI.
|
| What turned me off though was this paragraph:
|
| > This is a hysterical era perpetuated by liars, cowards,
| imbeciles, craven boosters and the easily-fooled. Those
| excited about generative AI are either the victim or the
| perpetrator of a con centered around a technology to
| ingratiate at the highest cost possible.
|
| That's a very bold claim. Really anyone excited about
| generative AI dude? That's just an absurd claim, and makes it
| sound like he hasn't used an LLM since GPT 3.5. It's just the
| language is so hyperbolic and angry that it's giving me more
| rant vibes that really hurt the tone and damage the (many
| valid) claims he's trying to make.
|
| Really tried to read through this all the way, but man I'm
| just not in love with this guy. I feel like the frustration
| is clouding his judgement. This line is another one with a
| fact that isn't really grounded:
|
| > so, you know, they only need to grow by 496% by the end of
| 2029!
|
| Which isn't wrong, but also Anthropic's revenue increased
| from $1 billion in Dec. 2024 to $47 billion May of 2026.
| Which of course doesn't guarantee that it will continue to
| grow at that scale, but it's clear that there is a strong
| demand for what they are creating.
|
| Idk, not really sure what my point is here. There are just so
| many facts and numbers quoted in here... It's a bit
| exhausting to refute a piece like this, when parts are
| genuinely correct, and parts are maybe subconciously
| exaggerated due to some emotional leaking into the argument.
| Tanjreeve wrote:
| So basically you can't find fault with the numbers but you
| find the tone annoying?
| LogicFailsMe wrote:
| Well, he dismisses any value whatsoever to GenAI. That's
| immediate bozo bit criteria to me. And, well, if
| Anthropic revenue doesn't grow 5x between now and the end
| of the decade, I'll be pretty surprised. But, sure, if it
| doesn't, then someone will keep them around anyway. AMD
| almost died in the 2010s as one example, but they kept
| getting propped up and now they're back in the game
| swinging. There are people who can see alpha beyond the
| next 10Q. Ed Zitron isn't that sort.
| mlyle wrote:
| > Well, he dismisses any value whatsoever to GenAI.
|
| I didn't read it that way. I see a lot of value in it.
|
| I just don't see us justifying the amount of
| infrastructure being built or current valuations. Or in
| the unlikely event that we do, the societal upheaval is
| going to take away the ability to monetize it
| meaningfully.
|
| OpenAI and Anthropic may make it through. But that is
| different from saying valuations are justified or that
| all this infrastructure will pay off.
| LogicFailsMe wrote:
| "Those excited about generative AI are either the victim
| or the perpetrator of a con centered around a technology
| to ingratiate at the highest cost possible."
|
| How else would you read the above statement? He's just
| preaching to his own choir IMO.
|
| My take: like any gold rush, a lot of dumb ideas will get
| backed and they will all fail. And then we'll keep the
| ones that worked. SSND. Good luck picking the winners a
| priori.
| mlyle wrote:
| I read it in context as being about the market prospects
| of genai.
|
| The problem is, when there is so much overinvestment,
| everything gets wrecked. In the aftermath of the dotcom
| boom there was at least a bedrock of fiber and still
| useful equipment to build upon amid the rubble. This time
| we are going so much further; also many of the durable
| assets are misplaced bets and the depreciating ones will
| depreciate more steeply.
| LogicFailsMe wrote:
| Someone should do the analysis of a decade and a half of
| Nvidia datacenter GPUs from Fermi to Kepler to Maxwell to
| Pascal to Volta to (Turing) to Ampere to Hopper to
| Blackwell and generate some hard depreciation numbers.
| Fiddling around a bit, 16-20% annual depreciation (so 5-6
| years total and then any further revenue is bonus goods)
| it would appear, but that's a fiddle number.
|
| But confounding this, K80s and V100s are still offered by
| cloud providers 13 and 9 years after their releases and
| academia still loves their GTX 1080 Pascals in their
| desktops. At companies, the beancounters take a
| computation and find the best architecture !/$ for that
| calculation. It does not need to be brand new shiny. It's
| Nvidia's job to make that case, not them. But anyway, the
| real data is right there. And those old GPUs demonstrate
| the dark fiber is already in place (and it's not so dark
| or they'd pull their racks).
|
| AI is the special case. New GPU generations are the only
| way to access HW implementations of last year's research
| on precision modes and matrix math. If that slows down,
| that would be the first real bellwether of a slowdown. It
| hasn't happened yet. I'm a little surprised myself, but I
| also think coding agents are the vanguard of general
| design agents and that's going to hit a lot of industries
| at once. So as long as the next generation of GPU halves
| the price of tokens and doubles throughput (or better),
| the demand for tokens will continue to rise IMO.
|
| What I don't think is that AI can come for anyone's job
| successfully no matter what the C-suite sorts insist.
|
| In summary, if you're a bear, you can point to the
| depreciation cycle and scream the sky is falling. And if
| you're a bull you can point to GPUs staying in production
| for a very long time despite the depreciation. Guess we
| have to wait for 2030.
| sumeno wrote:
| 5-6 years is wildly optimistic for GPUs in an AI data
| center
|
| Try 1-2: https://www.tomshardware.com/pc-
| components/gpus/datacenter-g...
| scubbo wrote:
| SSND?
| vatsachak wrote:
| Alright, let me explain what's happening this Q
|
| Chinese providers realized that LLMs have peaked and have
| started trying to reduce the price per token. Deepseek
| pro v4 can easily add tests to my complicated code and
| costs cents for a million tokens.
|
| I can ask Claude or ChatGPT architecture questions and
| then use Deepseek for the rest.
|
| How are these businesses going to pay to price of energy
| and GPU depreciation again?
| loandbehold wrote:
| He implies $400 billion in revenue by the end of 2029 is
| unrealistic when in fact it's very doable if you look at
| the trajectory of this technology since ChatGPT 4.0
| launch. Google and Meta bring in around $500 billion in
| ad revenue between two of them annually. ChatGPT will
| easily bring 100s of billions in ad revenue if fully
| monetized given 1. it has billion weekly active users 2.
| ChatGPT conversation provides even better context for ad
| targeting vs search or social media. Enterprise AI
| revenue is going through the roof already, and with
| computer use companies will literally be able to fire
| large percentage of white collar workers and replace them
| with AI agent without updating their software infra.
| vatsachak wrote:
| And if a pig had wings it could fly
| Jedd wrote:
| Does that '100s of billions' come from a big bucket
| somewhere called 'spare cash', or does it correlate to a
| commensurate reduction in the 'around $500 billion in ad
| revenue' that Google and Meta are extracting?
|
| Do your assumptions - " if you look at the trajectory " -
| factor in a slowing economy, a slowing growth in quality
| improvements in the tech, and/or the asymptote of market
| saturation for punters happy to stump up more than $50 a
| month?
| sailfast wrote:
| What about a few hundred billion in salary and benefits
| reductions due to mass layoffs?
|
| Not saying this would be good (qualitatively) or even
| good business in any sense, but we've already seen
| companies willing to sacrifice headcount to cover CAPEX
| for these models.
| monodeldiablo wrote:
| A few hundred billion in salary and benefits reductions
| equates to millions of layoffs. At minimum, we'd be
| looking at something about the same magnitude as the 2008
| financial crisis. That scale of workforce reduction would
| have profound implications for the broader economy.
|
| In a consumption-driven economy, businesses need
| consumers. Any gains from these layoffs would be short
| term at best.
| mhitza wrote:
| > Anthropic's revenue increased from $1 billion in Dec.
| 2024 to $47 billion May of 2026.
|
| That's the kind of claim that requires and asterix, and
| things like this are what feeds into the AI propaganda
| machine.
|
| That is an anualized revenue, which are projected numbers
| and not "real numbers".
| josh-sematic wrote:
| Divide both by 12 then and you have monthly revenues. The
| ratio between them remains the same and remains rather
| astonishing.
| fc417fc802 wrote:
| Dividing by 12 you still have the same problem. They're
| projected numbers as opposed to real ones as well as
| being grossly skewed by any short term fluctuations.
| JacobAsmuth wrote:
| Divide both by 12 and you do not get the projected
| numbers. You get monthly revenue, a real measured number.
| It is the number being reported * 12 when they state a
| new ARR.
|
| E.g. When Anthropic stated $1B ARR (an extrapolated
| value) what they were actually reporting is $(1/12)B
| Monthly revenue. If it helps their current monthly
| revenue is 47 times that, for a grand total of $(47/12)B
| per month in revenue.
| SlinkyOnStairs wrote:
| > Haha thought you were referring to the upsell at the
| start asking to subscribe to the newsletter for $70 / year.
|
| People like you would be why I put "(titled)" in the reply.
|
| > That's a very bold claim. Really anyone excited about
| generative AI dude? That's just an absurd claim, and makes
| it sound like he hasn't used an LLM since GPT 3.5. It's
| just the language is so hyperbolic and angry that it's
| giving me more rant vibes that really hurt the tone and
| damage the (many valid) claims he's trying to make.
|
| The premise is that AI is significantly more expensive than
| current subscription & token fees. Within that framing, yes
| basically all AI users are getting conned. Tricked into
| redesigning their workflow around an unaffordable
| technology, in the hopes there will be too much sunk cost
| and they'll just eat a thousands-a-month fee.
|
| > Which isn't wrong, but also Anthropic's revenue increased
| from $1 billion in Dec. 2024 to $47 billion May of 2026.
| Which of course doesn't guarantee that it will continue to
| grow at that scale, but it's clear that there is a strong
| demand for what they are creating.
|
| "Doesn't guarantee it will continue to grow" is an
| understatement.
|
| Let's take a generous assumption of the average
| subscription; $1000/month/seat. This will be quite a bit
| higher than pretty much everything but hardcore software
| dev, we'll re-do the math with $200 in a moment. Let's also
| grab Ed's $60B figure for both Anthropic/OpenAI, as it's
| more generous.
|
| That's 30 million subscribers for Anthropic, 30 million for
| OpenAI, 60 million total.
|
| They need to 5x. So 240 million extra subscriptions.
|
| ... _Are there 240 million people left on the planet who
| can afford $1000 /month?_? (Either directly, or their
| employer) This kind of scaling is already hitting the
| limits of people on the planet. That sounds ridiculous for
| "240 million people" against 8 billion, but remember that
| $1000/month is a lot of money and a lot of jobs just do not
| benefit from AI. 2/3rds of employment in the US is stuff
| that happens in the physical world. Claude won't restock
| shelves, manufacture goods, construct buildings, cook food,
| or wipe geriatric asses.
|
| Go again with $200/month. While this monthly fee is much
| more palatable, the sub-count inflates to 300 million subs
| needing to grow to 1.5 _billion_. They 'd need to sell a
| sub to _everyone_ in Europe and North America.
|
| (And while there's loads of people in Africa and Asia, most
| of those are low income. You're not getting expensive AI
| subscriptions out of them or their employers either.
| China's obviously not gonna buy US AI, India has a GDP-per-
| capita of $250/month.)
| D_Alex wrote:
| >They'd need to sell a sub to everyone in Europe and
| North America.
|
| Yep. Every man, woman and child, and even then provided
| we include Russia, Mexico, Cuba, Haiti etc, and, out of
| desperation to get to 1.5 billion, Turkey, which is in
| Europe a little.
| casey2 wrote:
| I mean it almost certainly won't increase unless a major
| company takes out substantial debt, in which case we just
| kick the can and have conversations about bigger numbers. I
| don't quite think you understand, where will these hundreds
| of billions come from? By 2029 we will be well into a
| hardware glut and people will run their own models.
| Anthropic doesn't have the data flywheel to compete with
| OpenAI or Google. They went all in on special purpose AI
| and hit a brick wall and had a "do as much evil as
| possible" strategy which didn't pay off. Hopefully they
| fail before they get the entire industry regulated.
| degamad wrote:
| [flagged]
| naishoya wrote:
| I just woke up and THIS! ... you almost owe me a new
| keyboard! I love it!
|
| This statement cleanly encapsulates the entire problem
| with all of the frontier models' companies' pre-IPO
| numbers.
|
| They have something-something "new technology" and we
| don't know anything about how the market is going to
| settle on the ethics, the utility, the human capacity
| opportunity cost impacts of not training and/or mis-
| educating an entire cohort of intern-engineers for a few
| seasons to a generation, the full environmental costs of
| hardware and operations necessary for the training each
| new larger model, ... and we cant even quantify the
| unknown-unknowns - the risks we cannot forsee.
|
| To predict market revenues for the next few years based
| on the curves, that they self report without external
| disclosure of the underlying numbers, is just like
| expecting your 2 yr old to continue growing at the same
| pace in the future and in the past - laughable. Good
| thing it was just water not coffee and it didnt quite
| come "out my nose" :- ) Thank you kind stranger!
| adampunk wrote:
| No wonder Ed is such a hit with this crowd.
| degamad wrote:
| Glad to be of service. I can't take credit for the idea,
| it was stolen from a meme I saw long ago, but it was one
| which sticks with you.
| 1attice wrote:
| Arguments have smells but rigour demands you investigate
| further. Zitron's smelly prose is, ironically, just the kind of
| stylistic distraction that AI can help condition; the further
| irony is that he will one day seem to have been right, for a
| year or two.
|
| The money is indeed losing its mind over AI, and Zitron is a
| stopped clock. A correction is coming but the tool isn't going
| anywhere.
| surgical_fire wrote:
| His arguments on the numbers of AI are actually pretty solid.
|
| I am still to see a solid counter to what he brings up there.
| lispisok wrote:
| Oddly suspicious how this comment which was not one of the
| first comments which does not address the content at all but
| the tone skyrocketed to the top.
| hnuser123456 wrote:
| The tone is written as abrasive to anyone who doesn't already
| agree, which shows this is more of an emotional opinion piece
| than open minded objective research.
|
| Hype cycles never last forever, but that doesn't mean all the
| value has been tapped by any means. The fact that modern GPUs
| can solve ridiculously complex high dimensional functions is
| a superpower in every possible field of research.
| BoggleOhYeah wrote:
| HN does this with every Zitron article.
| cmiles74 wrote:
| I don't read Ed Zitron, aside from when he appears here on
| Hacker News, and I also find his tone to be over-the-top. I
| think we might agree on that much.
|
| These articles are lengthy but, to my understanding, Ed's idea
| is...
|
| * AI companies have committed to purchasing X amount of compute
|
| * Data centers are being constructed to meet this demand,
| they'll need to charge amount Y
|
| * AI companies do not have sufficient revenue to pay amount Y
|
| IMHO this isn't surprising, personally the only real use-case
| for AI that I've seen is code generation or automated sales or
| scam calls. This doesn't seem like a big enough market for the
| huge dollar amounts I'm seeing thrown around.
|
| I'm curious why you think Ed is so far off the mark on this. To
| me, it seems like we are headed for a big correction on the
| whole AI thing.
| mike_hearn wrote:
| Not the OP but Zitron makes clear errors:
|
| * He seems to think that the moment Nvidia release new
| hardware, all existing hardware becomes worthless. It doesn't
| and there are plenty of tokens being served by old GPUs. This
| makes all his calculations about how quickly datacenters have
| to pay off useless.
|
| * All his numbers about costs, revenues etc are guesses or
| attempts to work backwards from off the cuff and frequently
| inconsistent comments by tech executives. They could easily
| be very far off.
|
| * He doesn't seem to understand that datacenters have never
| been full of hardware on their opening day. A lot of his
| attacks revolve around this confusion - he learns that an
| opened datacenter isn't yet at full load or fully equipped
| with GPUs and thinks that means it's been delayed. I remember
| when Google first opened their facility in the Dalles, it
| took years for it to completely fill with machines.
| cmiles74 wrote:
| > All his numbers about costs, revenues etc are guesses or
| attempts to work backwards from off the cuff and frequently
| inconsistent comments by tech executives. They could easily
| be very far off.
|
| Agreed, but I'd argue that Ed doesn't have much else to
| work with. I'd like to see journalists take this tack and
| start asking these executives to either back up their
| statements or back down from them. They should be held
| accountable for their statements.
|
| Even if we dial down these numbers by a magnitude they are
| still insanely large and the AI companies do not seem to be
| making enough money to balance things out.
|
| > He seems to think that the moment Nvidia release new
| hardware, all existing hardware becomes worthless. It
| doesn't and there are plenty of tokens being served by old
| GPUs. This makes all his calculations about how quickly
| datacenters have to pay off useless.
|
| I agree that older hardware from Nvidia doesn't become
| worthless when Nvidia releases new, more powerful hardware.
| I have to point out that it certainly loses a great deal of
| value and that's not nothing.
|
| > He doesn't seem to understand that datacenters have never
| been full of hardware on their opening day. A lot of his
| attacks revolve around this confusion - he learns that an
| opened datacenter isn't yet at full load or fully equipped
| with GPUs and thinks that means it's been delayed. I
| remember when Google first opened their facility in the
| Dalles, it took years for it to completely fill with
| machines.
|
| Is that really the case? I mean, I read about the build out
| of these data centers being delayed all of the time. I read
| this last week and it seems roughly in line with Ed's
| ravings:
|
| > A JPMorgan analysis last month found that more than 60%
| of data-center capacity planned for completion in 2027
| isn't yet under construction, and another 7% is delayed.[0]
|
| [0]: https://www.msn.com/en-us/news/technology/america-s-
| data-cen...
| LogicFailsMe wrote:
| It's either new GPUs make the old ones worthless or old
| GPUs make the new ones too expensive because they're
| still useful, it depends which ranter you're reading at
| the time.
|
| Just like Michael Burry kept comparing NVDA to CSCO and
| now he doesn't do so anymore now that NVDA's P/E is ~31
| and CSCO's is ~41. Funny that.
| JacobAsmuth wrote:
| H100s installed 4 years ago are more expensive to rent
| now than they were on day 1. It is not at all clear that
| older hardware is losing its value in a world where the
| next gen model is smarter and faster due to improved
| training+inference algorithms (e.g. custom kernels) but
| runs on the same hardware.
| dofm wrote:
| > He seems to think that the moment Nvidia release new
| hardware, all existing hardware becomes worthless.
|
| I am the OP and I _totally_ agree with you on this one
| point. In fact the progress being made by open weights
| models strongly suggests that some of this hardware has
| much more of a life.
|
| The overarching point he makes about incomplete data
| centres is that the current offering _is running
| successfully_ on that very incomplete capacity, right?
|
| What he is saying is that he cannot believe the demand
| exists to fill any of the unbuilt stuff, but much of it is
| still commitments that are going to have to be paid for,
| unless they can be backed out. He points to Nadella
| essentially confirming there will be overcapacity.
|
| He also makes an interesting point that people tend to
| think "I can't get a GPU right now" means "there is
| intense, live demand for GPUs in data centres" when in fact
| the reason you can't get one is buy-and-hold. Including
| much of that new replacement hardware: it is being bought
| even the old stuff would (let us stipulate _will_ ) do the
| job.
|
| I think he (or someone who interviewed him) recently said
| it reminded them less of the dot com boom and more of the
| Chinese real estate bubble.
| ai_critic wrote:
| It helps if you look at Zitron's work history and
| experience. He's a hype man and a games journalist. His
| opinions on this are whatever sells, not exactly whatever
| is correct.
|
| This is alarmingly obvious whenever he talks out of his
| depth about things like how companies actually use AI and
| reason about business decisions.
| michael-ax wrote:
| accuracy and precision are not the same thing. he's
| delivering one, you're asking for the other. no?
| ai_critic wrote:
| To put it more bluntly: he provides neither in his
| pursuit of rage views.
| sumeno wrote:
| They don't immediately become worthless, but they don't
| last all that long either
|
| https://www.tomshardware.com/pc-
| components/gpus/datacenter-g...
| CuriouslyC wrote:
| This doesn't match my experience, in academia I saw
| ~40-45% utilization NVIDIA GPU clusters that went 6 years
| with <20% failure rate. Might be a TPU thing?
| JamesBarney wrote:
| I don't know if Ed is far off the mark. But this article does
| nothing to help illuminate it.
|
| He mixes estimated capex spend by like 3 different sources
| with actually commitments by the LLM providers.
|
| He talks about how crazy it would be for ai providers to
| double revenue every year. But openai is doubling every 9
| months and anthropic is doubling every 3.
|
| It's obvious if AI consumption stops growing today those
| companies are in trouble, and if AI consumption keeps growing
| at current rates they'll be more than fine.
|
| Most people expect growth rate to slow, just no one knows by
| how much. This will determine if there is an over build out
| or not.
| hn_throwaway_99 wrote:
| > personally the only real use-case for AI that I've seen is
| code generation or automated sales or scam calls.
|
| That seems like a giant paucity of imagination. I can easily
| name a lot of areas where AI is already having a large impact
| and it's not hard to imagine the impact growing:
|
| 1. Customer service. Yes, we all like to laugh at the silly
| chatbot mistakes, linked list reversals and Instagram
| oopsies, but a lot of companies are putting a lot of effort
| (and spend) into AI for customer service.
|
| 2. The legal profession is already spending a lot on AI, and
| it will only grow. Again, we all like to read about
| hallucinated case citations, but those are solvable problems
| (honestly I felt they were more human problems than tech
| problems to begin with) and there are so many areas in
| research and document summarization that AI is really good
| at.
|
| 3. Radiology. There are lots of arguments over whether AI
| will "replace radiologists", but that's besides the point.
| The largest radiology groups in the country _already_ use AI
| software to check for specific missed diagnoses, and the
| expected spend on AI will grow, a lot.
|
| 4. Enterprise knowledge management. Services like Glean are
| popular and growing.
|
| I can easily go on.
| c0n5pir4cy wrote:
| I would argue that all 4 of these that you have mentioned
| can be handled with relatively small models very well.
|
| The real question is what situations are the flagship,
| larger models useful in and will that produce enough
| demand.
| sumeno wrote:
| Radiology isn't using chat bots
| monodeldiablo wrote:
| You annihilated your own argument with the inclusion of
| radiology. The only successfully deployed "AI" in use by
| radiologists (that I'm aware of) are bespoke image analysis
| models, not LLMs. And that space is rapidly fragmenting as
| there's a frustrating and seemingly irresolvable tension
| between sensitivity, generalizability, and accuracy.
| sabretooth1405 wrote:
| Everyone I know hates AI customer service. A couple of
| prominent food delivery apps here in India switched to AI
| chatbot customer services and it's been horrible since
| then. It's been almost impossible to get refunds since
| then, even when there's straight up fraud involved without
| screaming ok twitter.
|
| Now ofc it can be said that they haven't implemented it
| properly but at some point it needs to be considered that
| why isn't no one figuring it out?
| aagha wrote:
| He does this on his podcast on a regular basis.
| HerbManic wrote:
| I like Ed's sense of humor, I also like that he can distill
| down a lot of messy details into something more cogent,
| especially with the money side.
|
| But, I also think he has missed the mark on a fair few things
| in terms of out comes. He may be proven right yet in terms of
| the general shape of things for some parts of the industry but
| also will have some big misses.
|
| My general take away usually comes down to, places like OpenAI,
| Anthropic and Oracle have gone in a little to hard to fast and
| it may hurt them long term as they struggle to make it work in
| terms of economics. not that they can't just it will be
| difficult. But places like Microsoft, Google, Meta, Apple,
| Amazon; they have a very long runway to endure the growing
| pains and make it through to a long term business that no
| longer burns cash.
| marcus_holmes wrote:
| I kinda get it - he's been attacked for his negative views a
| lot, and that tends to produce a more passionate writing style.
| It's a little immature, sure, but also authentically human.
| overgard wrote:
| Right, because markets are always rational and nobody gets
| greedy and ignores the skeptics until things are out of hand.
|
| https://en.wikipedia.org/wiki/Tulip_mania
| ainch wrote:
| As WIRED reported[0], despite constantly writing about how an AI
| collapse is _just about_ to come, Zitron privately does PR for AI
| firms on the side. The man is an obvious hack, and it 's
| disappointing that he has become one of the mainstream faces of
| AI skepticism.
|
| [0]: https://www.wired.com/story/ai-pr-ed-zitron-profile/
| qaq wrote:
| Anthropic has made $330 billion in compute and chip commitments
| between Google, Amazon, and Microsoft, another $30 billion with
| CoreWeave and another $15 billion with SpaceX. To pay for this
| compute, Anthropic must meet its projected revenue of $174
| billion a year by 2029. Anthropic has raised $95 billion across
| rounds in February, April (from Google and Amazon), and May.
| These funds will be insufficient to cover Anthropic's costs, as
| will Anthropic's cash flow, meaning that it will have to raise at
| least another $200 billion in the next year.
|
| How people take this seriously? Anthropic is at 45B ARR S-1 shows
| inference margin climbed to 70% (obviously could drop) So where
| that 200B number is coming from ?
| thereitgoes456 wrote:
| Anthropic's S-1 is not public yet
| bandrami wrote:
| That wasn't an S1 and we have zero idea what GAAP compliant
| numbers for Anthropic or OpenAI would look like
| micromacrofoot wrote:
| It doesn't matter if it's slowing down, pretty much no one has
| implemented it to its full extent yet. It could stop right now
| and we'll be finding new implementations a decade from now.
|
| Anthropic and Open AI could evaporate tomorrow and we'll still be
| using the models.
|
| The market may collapse, but the people who think AI is going to
| disappear as a result don't understand what it is.
| andrewstuart wrote:
| AI companies are racing to win the future of computing.
|
| They are possibly in a winner take all death race against each
| other.
|
| The stakes are so high that these cash rich companies cannot
| afford not to throw everything they have into this.
|
| The sunk costs are irrelevant when it's a question of survival.
|
| Whether you hate or love AI computing is being completely
| reinvented - at the absolute core of this is computers
| programming computers.
|
| Anthropic is winning this race by a country mile right now.
|
| This is such an important future bet for these companies that the
| trillions must be spent because there's no future or a greatly
| diminished future for some of them unless they have ownership of
| the technology.
| SubiculumCode wrote:
| I stopped as soon as the popup hit.
| dsign wrote:
| The way I see it, AI is going to change the world radically. It
| could be for the worse, the better, or a mix of both, but in my
| mind there's no doubt.
|
| We are only five or six years into the leap LLMs represent. For
| reference, radio waves were discovered in 1886, Marconi used them
| for communications in 1895, and while telephone and radio
| coexisted for many decades, it wasn't until the 1995 that mobile
| phones and wireless technologies started picking up. It took so
| long not because of the physics of radio waves required time to
| mature and improve, but because everything else needed to profit
| from it did require time.
|
| To me, LLMs are not so much AI as it is a building block.
| Radiowaves maybe, or the equivalent of transistors. We are
| already seeing that it's possible to chain LLMs into agents.
| Currently, price is a strict limiting factor for coding and
| agents.It's probably fine-ish if all you want is Claude Code or
| Codex, but there are many other possible compositions of LLMs
| that most people don't dare to experiment with. For example, LLMs
| to drive NPC dialog and world mechanics in games is not a thing
| due to cost. Were prices of inference hardware go down and
| inference algorithms keep improving, I'm convinced (and afraid)
| we would see things very difficult to imagine today.
| A_D_E_P_T wrote:
| > _For example, LLMs to drive NPC dialog and world mechanics in
| games is not a thing due to cost._
|
| Hah, I'm actually working on just this problem.
|
| Cost isn't the issue. There are only so many coherent (in
| context) responses and scenarios, that you don't need an LLM to
| generate text in the game, in real time. Instead, you can have
| LLMs build a vast corpus of "atoms" (dialog messages,
| fragments, cues, etc.) that can be stringed together in a
| deterministic way in response to player input. These can also
| be pre-screened and subjected to various tests prior to
| implementation.
|
| To a player interacting in the game, a system like this would
| seem functionally indistinguishable from generated text within
| the game's designed interaction envelope. And it has huge
| advantages: Although it can expose seams if the player breaks
| character and decides to probe it, it won't be exploitable the
| way an LLM would be.
| 48terry wrote:
| > The way I see it, AI is going to change the world radically.
| It could be for the worse, the better, or a mix of both, but in
| my mind there's no doubt.
|
| Worthless statement. Wow, you suspect something can make things
| better, worse, or both? That's a keen insight there.
|
| > For reference, radio waves were discovered in 1886, Marconi
| used them for communications in 1895, and while telephone and
| radio coexisted for many decades, it wasn't until the 1995 that
| mobile phones and wireless technologies started picking up.
|
| We are still so early.
|
| I mean, we have advertised them in multiple super bowls, have
| companies that basically own tech news (incredulous journalists
| will repeat any stupid insane shit a CEO wants to say), that
| say they're valued at over a trillion dollars and nobody with
| the power to argue those finances seems willing to do anything
| but agree. We have built hundreds and hundreds of acres of data
| centers (and made deals for data centers that are never going
| to happen) that demand *billions* per month. They are devouring
| all the silicon to where people are visibly seeing the price of
| hardware double, triple, more in price. Work places insist on
| employees using AI (then pulled back because it turns out this
| stuff costs money and it's not fun anymore when it's not
| subsidized).
|
| But we just need more time, more eyes, more people looking at
| it.
|
| Where in the radio wave timeline did this happen?
| squidsoup wrote:
| > LLMs to drive NPC dialog
|
| Far more interested in dialog and characters developed by a
| writer - simulation is boring
| Jtarii wrote:
| >Far more interested in dialog and characters developed by a
| writer - simulation is boring
|
| It entirely depends on the situation. Background NPCs that
| just have conversations among themselves would be a great use
| of LLMs to make the world feel more immersive. Obviously you
| never want to directly engage the player with LLM generated
| writing.
| Havoc wrote:
| >have to be roughly twice the size they are today, and then
| double again basically every year until 2029 or 2030.
|
| Anthropic is growing way faster than doubling yearly so don't
| think this is entirely implausible
| aronowb14 wrote:
| I asked around my network recently - in the last month or two
| basically every large company has put in spending limits per
| engineer. Curious what their S1 will look like when they go
| public.
| atleastoptimal wrote:
| This is wishful thinking. AI is still getting better rapidly.
| Anthropic's revenue is still growing at an unprecedented rate and
| they haven't even released their best model (Mythos) for 4 months
| now.
| hereme888 wrote:
| Funny I just read an article on how it was actually speeding up.
| zuzululu wrote:
| I don't think anybody actually believes that the current
| investment is going to yield returns that they are projecting.
| Neither did people back in Dotcom or Railways or any other
| hype/bubbles. Yet these technology did transform and the returns
| came to fruition.
|
| Internet continued to thrive and grow even after the stock market
| came and went, it took 13 years to roughly nasdaq to recover but
| the explosion of GDP from internet has been largely decoupled
| from the previous bubble boom and bust.
|
| If you use the stock market as a yard stick to project new
| revolutionary technology we shouldn't have had trains, internet.
| In fact internet should've stopped with the bust of Nasdaq and
| everybody would've moved back to using paper _but we didn 't_ it
| gave rise to the next wave of economic output powered by this new
| tech.
|
| I don't see AI to be any different.
| degamad wrote:
| > it took 13 years to roughly nasdaq to recover
|
| So it's okay for everyone's who's due to retire in the next 13
| years to have their 401k or equivalent wiped out when the
| correction happens?
| RigelKentaurus wrote:
| The handwringing tone of the article is off-putting.
|
| Ed is confused between whether AI is useful, and whether the
| current level of funding and valuations are sustainable. The
| following statements can both be true:
|
| 1. AI is already quite useful and will continue to be so. This is
| true even if AGI doesn't happen.
|
| 2. The funding and valuations of many AI companies are too far
| ahead of their skis, and will probably roll back. Some may fail
| entirely.
|
| About the "where's the productivity in AI?" question: I think
| it's entirely possible that the primary benefit of AI will not be
| top-line growth but reduced costs (through reduced human labor).
| Companies will need to reduce prices to prevent losing market
| share to existing or new competitors, meaning that GDP may not
| increase, but costs will.
| yalogin wrote:
| As a tangent, I don't understand where and why meta fits into the
| AI race. They did not get any mind share (consumers) from the
| llms so far, granted they started the open source side to this
| but the Chinese companies produce far better models and have
| essentially become the default for on device set up.
|
| They have ai glasses and integration into instagram and facebook
| as the other avenues. I don't see ai glasses as compelling yet,
| and don't know how much more ad revenue or user engagement they
| can squeeze out with llms baked into the IG of FB flows. They are
| spending a lot and not seeing any returns. Am I wrong in being
| pessimistic about meta with AI?
| overgard wrote:
| You should probably be more pessimistic about Meta. Look at
| their last major venture, the Metaverse, which was basically
| embarassing. Their AI strategy is incoherent.
| gnarbarian wrote:
| if you think AI is slowing down, you may not be smart enough to
| tell the difference anymore.
| paulbjensen wrote:
| I find it nuts that I can use Claude Code for $20pm - I imagine
| that won't last forever but have to say it is great value for
| money.
|
| So when I see monthly budgets in the thousands for developers at
| some larger companies, I'm curious to learn how they are managing
| to spend that kind of figure: how much code/documentation are
| they feeding into their prompts, are they using agent
| orchestration systems to make the code factory run 24/7, and how
| much value is coming out the other end versus before?
|
| And, if they are pouring thousands into LLMs per developer, have
| they considered looking at alternatives like having LLMs running
| locally on own hardware with their own agent harness?
|
| Those are the kind of questions I'd love to ask - I just wonder
| how much stuff is truly cutting edge and how much might be
| wasteful?
| bloomca wrote:
| Developers at big companies need to pay per token, they don't
| have subscription available. So in case you use that, you
| likely spend way more than $20 in tokens.
|
| As for how to spend that much -- not that hard, to be honest.
| Just give it a lot of context and some relatively open-ended
| problem and it will easily eat through tons of tokens.
|
| I have $200 subscription for Codex and it is crazy what it can
| do in terms of debugging. I have a pretty complex Electron
| setup with some native code linked via Node addons, a few App
| Extensions and it can easily read the source code to see how
| the builder works internally (e.g. if your end Info.plist is
| not correct), debug the xcodebuild output to see at which step
| something is not linked correctly (like after XCode major
| version bump), etc.
|
| It is not a silver bullet but if you are not the one paying for
| it, there is no downside to throw a problem at it and see if it
| can come up with a fix.
|
| > And, if they are pouring thousands into LLMs per developer,
| have they considered looking at alternatives like having LLMs
| running locally on own hardware with their own agent harness?
|
| I am curious about that myself. I have a good machine now
| (Macbook Pro M5 Pro with 48GB memory), so I'll give it a try; I
| don't have high expectations so if it is actually helpful would
| be very neat.
| overgard wrote:
| I just looked at ccusage for a personal project. In 5 days
| (doing it as a hobby) I've managed to spend $250 in API tokens
| on a $200 subscription. 5 days, and thats on one computer (I
| split time using 3 of them). If I had to pay $2000 a month --
| no fricking way, not worth it.
| tossandthrow wrote:
| Given how I can manage and develop a huge production code base
| with an incredibly small team - and the rest of the industry
| apparently is not able to do it - I deem that we are still in the
| very early days.
| ilaksh wrote:
| Although I see huge utility in AI, I think he is right in terms
| of overspending and overenthusiastic build out. Because of for
| example what Apple is doing by putting an extremely efficient
| model with task adapters right onto phones.
|
| Also because we now have a massive demonstration that vastly more
| efficient hardware is desperately needed.
|
| Similarly other effective efforts towards on-device AI like
| Nvidia RTX Spark PCs and 2bit quants of strong models like DS4.
|
| So inevitably, significant investment will be going into vastly
| more efficient CIM efforts like Mythic AI and new FeFET devices
| etc. in order to make human-level and beyond AI at scale
| feasible. There is so much demand for this and the power
| requirements of current hardware are so excessive, it seems
| unlikely that the data center build-outs will be able to recoup
| their costs before the more efficient paradigms make it out of
| the lab and start scaling.
| jollyllama wrote:
| Lots of dismissive comments ITT, very few tackling the substance
| of the article.
|
| > AI Cannot Afford To Slow Down -- It Needs $3 Trillion Or More
| In Revenue By End Of 2030 To Sustain Its Existence
|
| Is this true? With the total 2024 wages being 11.7 trillion USD
| [0], and nonfarm payrolls totaling 158,000 in the same year [1],
| it's an order of magnitude higher than my back of the napkin
| guesses I've made that AI needs to take or create 1/20 jobs
| minimum to break even.
|
| [0] https://fred.stlouisfed.org/series/BA06RC1A027NBEA [1]
| https://fred.stlouisfed.org/series/PAYEMS
| irishcoffee wrote:
| If I thought there were some actual small cabal of people
| running the global economy, this is almost like a novel:
| massive amounts of money entered the economy starting in 2008
| and 2020-2023, the rich became insanely wealthy. Their wealth
| is now all tied up in the 2020s version of the railroad/fiber,
| we're going to essentially erase trillions of dollars from the
| global economy and reset.
|
| We sure do need a reset.
| philipallstar wrote:
| There's no "reset" required, other than resetting what people
| understand about money and finance, and having them realise
| that net worth is a stupid thing to use to excuse their
| revolutionary bloodlust.
| marcosdumay wrote:
| I really doubt the US will erase any money any time soon.
|
| The reset is prone to happen by other means.
| irishcoffee wrote:
| I consider myself of average intelligence, and I see this
| coming. Maybe I assume too much.
| marcosdumay wrote:
| Every government has complete control on how much of
| their money exists. If it disappears from the private
| finance market, it can compensate with any amount it
| wishes.
| throwaway27448 wrote:
| It would be better to lean into inflation and just dump a
| ton of money into the bottom of the market to dilute the
| top. Of course this only makes sense if the government is
| willing to regulate market control, which it has
| demonstrated time and time again it will not.
| ido wrote:
| Why only US wages rather than global wages? The US is the
| biggest economy but it's still only a minority of the global
| economy.
| zymhan wrote:
| Just consider the math there for a second, when you factor in
| the average US wage.
| beloch wrote:
| It's more interesting to ask, "Does AI _need_ to follow the
| current model of evil megacorps building massive data centres
| that, collectively, guzzle more energy than most nations on
| Earth? "
|
| Perhaps LLM's (or something better) will develop to be more
| efficient and quickly become something most people run on local
| hardware. Perhaps fad-obsessed management types will move onto
| the next big thing and AI will start being used more
| judiciously. Perhaps society will set sane regulatory limits
| that shape the direction AI is going in, from models that take
| jobs people want to models that, given the right hardware, can
| do the jobs few want.
|
| Anthropic and OpenAI don't have to succeed for AI to succeed.
| If they turn out to be a bubble that bursts and torches a lot
| of investors, it might actually be a fundamentally good thing
| for everybody else.
| ofcourseyoudo wrote:
| I guess my ears kind of turn off when you say "it's all slop,
| none of the apps are good, and it's a failure because no one has
| used AI to make the next Salesforce".
|
| I have found agentic coding to be extremely useful for a bunch of
| small, middleware, very focused bits of software for small
| businesses:
|
| * A company had a very specific scheduling need, they needed to
| move about 8-15 staff around with a bunch of different shifts,
| and have custom reports on who was working how many hours, and
| have the employees get a nice clean email summarizing their
| schedule
|
| * A manager wanted a very simple "let me send a text to add a to-
| do to the group list" need
|
| * A sales team of 3 wanted to be able to type pricing of raw
| goods into their phone, have it compared to other market sources,
| and have it text the other 2 salespeople and their manager when
| they were out in the field
|
| All of these were coded with Codex in about 4 hours with further
| refinements over the next week of back-and-forth with the people
| using the tools.
|
| I suppose yes we could have found some custom middleware
| solutions that did similar things, but it's nice to be able to
| make a web page or tiny mobile app that just does EXACTLY what
| the person wants.
|
| It's hard to do that and then listen to someone who says it's all
| just garbage.
| jillesvangurp wrote:
| I think it's time to distinguish between what frontier AI
| companies need regarding AI, and what will happen with AI if
| these companies don't get everything they need. Probably there's
| a bit more to this. Much of the technology is available via open
| source already and there's a growing ecosystem of AI tech that
| isn't really dependent on anything else than the hardware
| infrastructure needed to run it.
|
| A good analogy might be networking companies and infrastructure
| companies during the dot com bubble. It devalued a lot of
| companies but the internet stayed. A lot of dot com companies
| didn't make it. Much of the infrastructure investment did not go
| to waste, however. Nor did a the technology go away.
|
| I think it will be the same with data centers, related
| infrastructure, GPU hardware, algorithms, OSS components, etc.
| for AI companies. More companies need that stuff than is
| currently available. The ones that don't make it will have a lot
| of assets that they can pass on to the one that still have a
| chance. I don't think a lot of that stuff will get decommissioned
| or will be underutilized. It might get a little hair cut in value
| though. And like during the dot com bubble, some companies
| actually survived and did quite well. Especially those in the
| business of selling shovels during a gold rush.
|
| After the inevitable consolidation that follows the next logical
| stages in the hype cycle, I don't think AI will go away. It might
| be a bit of a bloodbath for some silicon valley investors that
| placed the wrong bets in the last few years. But that's the price
| of doing business over there. That doesn't mean it's all bad. And
| the smarter ones probably spread their risk enough that they
| still might come out looking alright.
|
| And like with the dot com bubble, many financial types have no
| clue what is happening and are running around like headless
| chickens. Which is why they ended up sinking a lot of money in
| exactly the wrong things. You'd hope they would have learned
| something.
|
| But articles like this suggest that that might be too much to
| hope. They still don't really get how technology tends to not
| stagnate and might continue to deliver potential for performance
| and cost optimization. The current level of investment is only
| unsustainable if that doesn't happen and nothing else changes. I
| don't think those kind of closed world assumptions are a safe bet
| at all.
| josefritzishere wrote:
| He may be bombastic but Zitron is right about the AI problem.
| These companies do hemorrhage cash, and have no viable plan to
| even become solvent. It may not be a scam but it sure looks like
| one. The problem it poses for the economy... is just as he says.
| dofm wrote:
| Today Apple launched its revamped AI offering. Judging by several
| reports, Apple pays Google a mere billion dollars a year to
| operate it. Essentially just licensing the IP. Google are
| (allegedly) happy to turn over the right to operate and distill
| their models for only a billion a year.
|
| Consumer revenue is only a smallish share of the puzzle, but
| still:
|
| If you are a _consumer_ and you have a Mac or an iPhone, what do
| you need from AI that Apple 's new offering won't provide? Why
| would you pay for ChatGPT, or even tolerate its inevitably
| increasingly desperate ad placements?
|
| Assume Google will have similar tools in their phones, and Google
| search will continue to have the offering it does.
|
| In short, where is the evidence that once Apple's tech exists,
| consumer AI is worth, to Anthropic or OpenAI, anything noticeably
| more than that $1B a year?
|
| Maybe OpenAI strikes a deal to put something in Samsung phones.
| Let's say Samsung is ten times as desperate as Apple (which is
| how it looks, often). Still only $10B a year?
|
| 2026 _consumer revenue_ projections from OpenAI are pitched at
| $14-15 billion, apparently. If they get that, it 's the only year
| they will get that, because by late this year, everyone with an
| iPhone will have something useful built in.
|
| Ed Zitron is a mouthy British rabble-rouser, but I think he is
| probably mostly on the money.
| jredwards wrote:
| I expect that a lot of the money will be in Enterprise AI.
| dofm wrote:
| Right but OpenAI are for real making that prediction about
| their _consumer_ revenue, which seems decidedly ambitious
| (considering that they are making nothing from their
| _current_ phone placement). And they have said that they
| expect it to be quite a large share!
|
| https://mlq.ai/news/openai-projects-over-280-billion-
| revenue...
|
| _" OpenAI projects revenue will be divided nearly equally
| between its consumer and enterprise business units by 2030"_
|
| That it is so absurdly ambitious and so likely to run up
| against reality strikes me as really indicative of the
| quality of the envelopes these calculations are being
| sketched on.
| mike_hearn wrote:
| Fidji Simo had to take medical leave so they're behind on
| their advertising platform. But in principle that could
| make a ton of money.
| jredwards wrote:
| I think OpenAI is just getting beaten so badly in the
| Enterprise space that they have to make rosy predictions
| about the consumer space.
| thewebguyd wrote:
| I think so too (Enterprise), but I think its going to look
| different from "Pay subscription for access to a model from
| OpenAI/Anthropic/Google."
|
| I don't think people will be doing business with the labs
| directly. "Enterprise AI" will be distilled down into purpose
| built products, with the model just basically being a generic
| commodity, and nearly irrelevant to the enterprises buying
| whatever these products are much like how I don't care if
| whatever SaaS was built in React, Vue, or some other
| framework as long as it works.
|
| Ironically, for as much shit as they get about Copilot,
| Microsoft I think has the right idea for the long game they
| just suck at execution. Copilot is the tool, integrated into
| the rest of their enterprise stack, it doesn't care what the
| model is behind the scenes (they already offer you the
| ability to choose between different models).
|
| That doesn't really bode well for the labs and their trillion
| dollar IPOs, because they are effectively reduced down to
| being a developer framework.
| pitched wrote:
| The free Chinese models are always approaching frontier-level
| power. The cost to Enterprise to run these models is where
| Anthropic and OpenAI are competing against in the long run.
| windexh8er wrote:
| That's cool, but the enterprise is cheap. If you have any
| proximity to sales in the space you know that procurement and
| lawyers exist that have a full time job redlining purchase
| orders and agreements to the N-th degree. The enterprise will
| pay for something that will make them money or prevent them
| from losing it. But the enterprise isn't paying a premium and
| they know that.
|
| Even within the Fortune 5 of the US if be surprised if any of
| them are paying more than $1B annually currently in total.
|
| And then you can take the parent context into account. If
| they can just equip users with a slightly more expensive Mac
| and call their Dell rep to order a few thousand DGX Spark to
| handle the rest... Why would they risk their trade secrets
| and intimate details flowing into models that may or may not
| be trustworthy long term?
|
| Most large enterprise have been burned by SaaS over the years
| in some way. I can't imagine there aren't architects in the
| large organizations that are truly weighing how to
| effectively use AI. And beyond that we're seeing more and
| more progress in SLMs and orchestration agents which become
| easier to run at scale on-prem.
| famouswaffles wrote:
| >If you are a consumer and you have a Mac or an iPhone, what do
| you need from AI that Apple's new offering won't provide? Why
| would you pay for ChatGPT, or even tolerate its inevitably
| increasingly desperate ad placements?
|
| Probably the same reason the Gemini app is still well behind
| ChatGPT in consumer usage and adoption despite being
| preinstalled on android phones worldwide ? Why are people using
| GPT on Windows. There's even a copilot button on new keyboards!
|
| Or maybe its the same reason Microsoft Edge is not the most
| popular Windows browser ? Maybe its the same reason Instagram
| threads did not even dent Tiktok ?
|
| You are asking the question the wrong way around. People use
| and like what they like and have a strong preference to
| continue doing so.
|
| This is just human behaviour. You don't need mind blowing moat.
| You begin to have problems only when:
|
| - Users are constantly using your product unsatisifed.
|
| - There's a competitor(s) with a significantly better offering
| that people are talking about.
|
| Will Apple's offering be providing any meaningful/significant
| benefit over just using GPT ? If not, don't expect any
| miracles.
| dofm wrote:
| > Will Apple's offering be providing any
| meaningful/significant benefit over just using GPT ? If not,
| don't expect any miracles.
|
| Judging by the announcements today about its integration into
| the OSes? They are offering useful things ChatGPT _cannot_
| offer unless they write an "everything app".
|
| One can (maybe should) make the argument that this is the
| browser monopoly again, but given that the USA has seemingly
| no intention of ever litigating that question again even if
| the EU does, there are clearly features here that OpenAI is
| effectively locked out of offering.
| famouswaffles wrote:
| Just because Apple said they're 'integrating into the OS'
| (which can really mean a lot of things) doesn't mean
| they'll offer something users will actually care about that
| Open AI can't match.
| discreteevent wrote:
| > that Open AI can't match.
|
| Open AI can match it but at what price?
| famouswaffles wrote:
| I don't understand what you are saying here
| saidnooneever wrote:
| likely cheaper than buying an apple product
| filoleg wrote:
| > Apple said they're 'integrating into the OS' (which can
| really mean a lot of things)
|
| Well, it can mean a lot of things, which is why Apple
| outlined plenty of specific use-cases and details of what
| they meant by "integrating into the OS" here.
| ai_slop_hater wrote:
| What did they outline? We had "browser use" for a while
| now, but it is still way too slow to be usable. Not to
| mention whatever OS integration they are making.
| throwthrowuknow wrote:
| Windows has been pushing the same thing hard without much
| success.
|
| Why do I care if AI is integrated into my OS when I can
| choose my preferred AI and it can use the OS directly?
| marcus_holmes wrote:
| This.
|
| The other day I wrote up some notes for a presentation.
| Opened Google Slides, clicked the gemini button, pasted
| the notes in and asked it to make the slides. Nope;
| gemini can only modify a single slide at a time in Google
| Slides.
|
| Pasted the same notes into claude, it wrote a pptx file,
| I imported that into Slides, job done.
|
| Being integrated into the product doesn't always mean a
| better result.
| pizlonator wrote:
| Yeah!
|
| Not being integrated can be an advantage because it gives
| you the freedom to think outside the box.
|
| Meanwhile an AI engineer embedded into an incumbent slide
| app team has to ask permission and get cross functional
| alignment for every little feature. And deal with
| neckbeard tech leads lecturing them on what the right
| architecture is
| duttish wrote:
| That's progress, last time I tried that a month or
| something ago gemini (the web app) crashed when trying to
| generate slides.
| D_Alex wrote:
| That's all true... however the point that Google will get
| just $1 billion per year from Apple for the AI service is
| still insightful.
|
| If AI use via Apple represents 10% of the total that vaguely
| implies that the total AI market is worth around $10 billion
| per year (which admittedly seems a bit low), and if it is
| just 1% (which also seems low) then we get $100 billion per
| year upper-end estimate.
|
| Which just is not enough to justify the current valuations of
| AI companies.
| brandon272 wrote:
| I admit to not having yet taken a deep dive on Apple's
| privacy claims (i.e. on device, private cloud etc) but one
| thing that Apple is going to be providing in this case is an
| actual privacy commitment that takes into consideration the
| level of sensitivity of data being uploaded into these AI
| chat interfaces.
|
| OpenAI's commitment to privacy is absymal relative to the
| sensitivity of the data people are dumping onto the platform.
| The CEO also has a reputation for being untrustworthy.
|
| The biggest threat to ChatGPT's moat may be a brilliant
| marketing campaign by Apple that really gets people thinking
| about what platform they want to be upload their secrets to.
| major505 wrote:
| This would be greate for google, because most people, specially
| in the apple environment don't much care to install new tools
| if they have a native tool that works reasonable well. If you
| have an ai assistant that's minimally competent in your desktop
| or phone, you will not care to go after chatgpt or
| alternatives, and google will receive tons of data to improve
| their models.
| iknowstuff wrote:
| ChatGPT has >1B users globally a mere 3 years in. iPhone is at
| 1.5B mostly concentrated in rich areas.
| dofm wrote:
| Only maybe fifty million of them are paying, though.
| dwaite wrote:
| It does not look nearly as good when you compare paying
| customers.
| al_borland wrote:
| > If you are a consumer and you have a Mac or an iPhone, what
| do you need from AI that Apple's new offering won't provide?
|
| I've been using Kagi Assistant for my AI needs, and have to
| say, Siri will probably replace it in the fall. The question
| will be, will I still want to keep Kagi for search, or will
| this new Siri get me where I need to be on all fronts? I need
| to start paying more attention to how often I actually use the
| search results vs just the AI summary.
|
| There are things I didn't see Apple show and I wonder how Siri
| will handle it. One example would be basic coding. They
| mentioned LLMs in Xcode and Siri with the Shortcuts app and
| Safari Extensions, but I just had Kagi write up a webpage as a
| means to display a bunch of data it gave me. Gemini could also
| do this, so maybe it's not a problem for Siri, but it remains
| to be seen. There is also a question of what the experience
| will be like. ChatGPT, for example, handles writing up this
| code is a much nicer way than Kagi Assistant. Kagi feels more
| like the results I would have had from ChatGPT a couple years
| ago where it just dumps out the code in a block and any change
| is an entirely new code dump, meanwhile ChatGPT goes into a
| coding interface with a live editor. Going to Xcode feels like
| overkill, Siri will probably be not enough... so that's a gap
| in the market Apple may not serve. I assume there will be
| several things like this. The prosumer level of AI usage, if
| you will.
| jimbokun wrote:
| Very very few consumers will be looking to use an AI to write
| code for them.
| chatmasta wrote:
| They will, but they won't realize it's writing code. It
| will look like Claude Cowork, which writes code for itself
| under the hood but is results-oriented for the user.
| TylerE wrote:
| Co-work is damn near magic. I've been working on a
| mapping project the past few days, am probably a couple
| hundred prompts deep in to it (I'm doing some very weird
| stuff with the data to produce a hybrid map). The
| processing pipeline is something like 12k lines of python
| and counting.
| bdangubic wrote:
| those few are the ones shelling out ridiculous money.
| mom&pop ChatGPT users aren't their key demographic/users,
| it is Uber's with $1.5k/SWE/month budgets
| al_borland wrote:
| I don't think what I did would be too uncommon. I asked the
| LLM to design an exercise program and went back and forth
| with it a bit. Everything was kind of scattered in the chat
| and hard to read/find. I asked for a web page to
| consolidate everything so I could just check it each day
| and see what to use. It made a single file I can just
| double-click and open in the browser. It's infinitely
| better than what the chat itself would have provided, and
| much better than telling it to give me a bunch of markdown
| tables.
|
| I could see the same thing being useful for the ultimate
| output of a lot of chats. For example, they showed Siri
| comparing specs for few different products. I used an LLM
| to do this once as well, but it was comparing 12 things
| with about 50 attributes. The table was fine, but what was
| better was asking for a webpage that let me click on the
| attribute rows I cared about so it could total up each
| column, which allowed me to easily rank them and better
| make a decision.
|
| Once it can make html files, it's a small step to have Siri
| throw it into iCloud, and make it web accessible. This
| would be more of a feature than something it would just do,
| but I could see this being used in the same way Google
| talked about making dynamic widgets to help explain
| concepts within Google Search. That's dynamic coding with
| an LLM as well, even if people don't know it. Apple
| wouldn't even need to show the code, they could just save
| it directly to a file and open Safari. That's essentially
| what their extension builder will do... write some
| JavaScript and load it into Safari.
| Yizahi wrote:
| Let's imagine for a second that this a few billion dollars per
| year to Google is correct. Why do you assume that it covers
| everything to be done by Google itself - from hosting to
| running actual servers? Apple may very well pay Google a
| licensing fee, take a trained LLM and run inference themselves
| locally or even at a yet another 3rd party for example a
| datacenter corporation or any mix of these. And then a true
| real cost of running just the inference on every Apple device
| would be separated into a completely different org payment
| flows, very obscured and higher than just a license fee.
|
| I'm not saying that this is what really happens. I'm saying
| that believing a CEO is as foolish and as grounded in reality
| as believing Ed Zitron.
| dofm wrote:
| > Why do you assume that it covers everything to be done by
| Google itself - from hosting to running actual servers?
|
| I don't, and that's the point, isn't it?
|
| It's the keys to a substantial chunk of the kingdom for $1B a
| year. Literally they are getting, for a very small price, the
| right to _distill their own models_ from Gemini.
|
| Is there money in this for someone with a data centre?
| Possibly. Is there money in it for NVIDIA? Possibly.
|
| But either way, that's not OpenAI or Anthropic, is it?
| aix1 wrote:
| > It's the keys to a substantial chunk of the kingdom for
| $1B a year. Literally they are getting, for a very small
| price, the right to distill their own models from Gemini.
|
| Here is a different interpretation: Apple bought the rights
| to distill and use a smaller version of one unspecified
| model in the Gemini family (there are many such models).
|
| The distillation will be carried out at Google's data
| centres so that the original weights never leave Google
| premises.
|
| For this to be keys to be kingdom it would need to cover
| all current and future models and would need to be very
| permissive with regards to distillation parameters and
| allowed uses of the distilled model.
|
| I expect the reality to be somewhere between these two
| extremes.
| hparadiz wrote:
| You are kind of glossing over the B2B market where contract
| pricing is basically just MBA vibes and the fact that people
| don't really care necessarily about the performance of the
| language model once it hits a baseline. They care about how it
| integrates into their lives. Precisely where first mover
| advantage comes into play. Having to train a language model all
| over again is it's own sunk cost.
| cyanydeez wrote:
| b2b needs actual ROI and that's no where near. CEOs would be
| yelling loudly if this were returning them cash instead
| they're just jettison people to afford the bills.
| shimman wrote:
| B2B absolutely cares, especially since ZIRP is unlikely to
| ever come back in our lifetimes. No sane corporation is going
| to continue to throw billions down the drain with nothing to
| show for it.
| hparadiz wrote:
| Most people using ChatGPT aren't using it for coding. They
| are using it for writing emails, working with spreadsheets,
| doing research, and writing reports. They could not care
| less about the coding aspect of language models. ZIRP in
| this context is meaningless. It's just another expense for
| every law and accounting firm. There's an entire world
| beyond tech jumping into this stuff right now. Like to give
| you perspective on this. I called my aunt in Germany who is
| an almost retired MD and she was the one that brought up
| ChatGPT and Claude to me.
| dofm wrote:
| OpenAI themselves said, in their revenue projections, that
| they expect the consumer vs enterprise revenue split to be
| 50:50, though -- see:
|
| https://news.ycombinator.com/item?id=48451053
| hparadiz wrote:
| That's actually a really good sign if they are getting that
| many consumer subs. I was expecting it to be more like 1:4.
| degamad wrote:
| The trick is in the wording - they probably aren't
| getting that many subs. They're saying they "expect" to
| get that many, at some point in the mythical future.
| gerdesj wrote:
| "Ed Zitron is a"
|
| gobby ... British rabble-rouser. "Gob" is the Dick van Dyke
| approved word for mouth.
| wrsh07 wrote:
| > 2026 consumer revenue projections from OpenAI are pitched at
| $14-15 billion, apparently. If they get that, it's the only
| year they will get that
|
| Would you care to wager on that?
|
| Because I would gladly take the other side at even odds.
|
| > consumer AI is worth, to Anthropic
|
| Anthropic does not really care about consumer AI. I expect
| consumer is where their least profitably customers are.
|
| My primary expectation is that Apple will mostly increase usage
| of AI by general consumers. To me, this reads like Instagram
| adding stories. Did it stop Snapchat's growth? Sure. But I
| would be cautious about claiming it will take too many users
| away from OpenAI. I think it will be a fairly different product
| offering.
|
| If you're paying to use ChatGPT right now, you might be using
| it for hobby coding, projects, or image generation. If you're
| paying a lot for ChatGPT, you're almost certainly using it for
| personal programming projects.
|
| The $100/month (and up) subscribers aren't going to churn
| because of this, and I would be extremely surprised if the
| $20/month users do in any meaningful way.
| dofm wrote:
| > Would you care to wager on that?
|
| I don't gamble. Though you might not be alone taking the bet:
|
| https://www.notus.org/technology/trump-blindsided-ai-
| compani...
|
| _" OpenAI CEO Sam Altman pitched the idea of turning over
| shares in his company to Trump in early 2025 and discussed
| the matter again with senior officials in recent weeks"_
| sarchertech wrote:
| > Because I would gladly take the other side at even odds.
|
| If you're only giving even odds you're not very confident in
| openAI at all. $15 billion is peanuts.
| overgard wrote:
| When I use these models, I honestly can't tell much of a
| difference between any of the frontier ones. Admittedly I'm
| not sitting around benchmarking them during the hype cycles,
| but as a coder I have zero issues switching to whatever's
| cheapest. Custom harnesses or whatever are not much of a moat
| (honestly Claude is so buggy right now that I've been using
| codex and opencode just so I don't have to deal with a
| flickery mess that screwed up my arrow keys)
|
| I just don't see how being the "premium" provider really
| works if much cheaper models are basically good enough.
| chupchap wrote:
| People who use ChatGPT have fed so much data about their own
| lives and interests into it. This includes a lot of information
| about personal lives, interests, plans, business and even
| family! Shifting to another AI app is painful as they would
| need to start from scratch.
| shironandonand wrote:
| making me glad I always use ChatGPT in an incognito window,
| guy.
| sarchertech wrote:
| I don't know anyone who uses ChatGPT who cares about that
| stuff. Most people just use it as a Google replacement.
|
| I actively hate it when it brings in some nonsense it thinks
| it knows about me. I told it my income once in an attempt to
| use it to find the perfect rewards credit card mix. Now
| anytime I try to get it to search for a deal it brings up
| some nonsense about "as a high income individual you don't
| worry about saving $X, you care more about reliability, so
| you don't need to look for the lowest cost" or something
| similar.
| arcanemachiner wrote:
| Turn off the "memory" feature in the settings. It just rots
| the context anyways.
| naishoya wrote:
| there is the option to opt-out of personalization, opt-out
| of using your conversations for training, and in that
| process reduce or eliminate any memory the system has of
| your personal preferences and context. If these actions
| don't erode your particular use-cases for ChatGPT, and if
| you think you can trust the model to follow these options
| this might be of use. I'm not trying to say "you're using
| it wrong" but that taking a more active control of the
| instaces facing you as a user might be of some benefit.
|
| I have iterated through different option configurations to
| reach a level of 'customization' that more or less conforms
| to my own use case, and this does include opting out of any
| and all lasting memory between instances and across chat
| sessions; and adds a selection of single initialization
| prompts which shape the chatbot's behavior to my
| requirements for that session's objective. these trim most
| if not all af the sycophantic interactions, reduce outputs
| to the specific formats and contours as defined and omits
| any of the 'explanations of the underlying reasons
| behind...' which is just noise. This also has enabled some
| pretty useful results without ever spending a dime on a
| paid account: the premium behavior presented to 'potential
| customers' as a lure continues to work for me, and for
| iteration across instances and accounts is possible with
| machine-ready yaml context file when a single sessions hits
| the 90% wall : one emit and ingest cycle rotation across
| account profiles in firefox and i pick right up with a
| fresh limit.
|
| Bouncing between ChatGPT and Claude, and between models for
| discrete subsets of larger tasks has really been impactful
| for my particular needs; but as i am not working in regions
| of knowledge that are beyond my own expertise and because I
| require the model to limit responses to very specific
| parameters, the logic space for unchecked hallucinations is
| low (but not zero).
|
| The most useful project results for me have been in
| developing an air-gapped private menagerie of multi-domain
| models which uses an operating structure not dissimilar to
| OpenMythos; but then my background includes HPC environment
| development for NUMA, unikernels, MPI and bare metal
| hypervisor design - so getting a design plan and functional
| code without requiring a team of programmers and months of
| time in order to even start using models under my control
| which have zero public facing risk for the projects i'm
| working on is a much better place to spend limited budget
| on. Last gen hardware in the V100 class is perfectly
| capable of running and delivering the physics calculation
| optimizations as required and I would rather buy and/or
| install solar+storage to supply the electricity for token
| generation than rent the same from any of the frontier
| models AND trust that "don't train and learn from me"
| preferences are and continue to be followed.
|
| If your use-case is a a 'lifestyle shopping assistant' then
| just turning off customization might be sufficient to stop
| it from telling you how to live your best life.
| why0hwhy wrote:
| Mmhmm and why spend on wrapper SaaS when open or self trained
| on device models do the job
|
| Web SaaS gonna end up being seen as another failed play at slim
| clients and entirely centralized sources of pay to play access
| to eyeballs; more AOL-ification of networks
| overgard wrote:
| > If you are a consumer and you have a Mac or an iPhone, what
| do you need from AI that Apple's new offering won't provide
|
| Honestly, I don't think I _need_ anything from AI at all. It 's
| a convenience but it doesn't really enable anything I wasn't
| doing before. That's probably their biggest problem. The
| biggest thing is it enables non-coders to write code, but it's
| very debatable that that's a good thing excluding personal
| projects
| zymhan wrote:
| They were not asking for your individual opinion. They were
| asking why any given person would need it.
| overgard wrote:
| It turns out I am any given person
| kachoio wrote:
| Bbut.. Elon said we are all going to be billionaires
| pxeger1 wrote:
| This rests on a lot of assumptions that the published figures for
| "planned" datacentres, "committed" AI spend, etc. are
| irreversible. I suspect that at least some of it is possible to
| back out of.
| bandrami wrote:
| That's true but then that's basically the end of Nvidia if that
| happens
| real_winidi wrote:
| The chart seems logical to me. Most problems are solved in the
| app space. New apps don't have to be the new facebook. They just
| need to be useful for the right audience (even a small one). It's
| like you have meat and bread in the supermarket, and add all
| other stuff you dont really need. Will be bought, but not as much
| as meat and bread, right?
| thewebguyd wrote:
| Whats a bit wild to me is Google's only selling point for their
| Pixel phones are increasingly Gemini.
|
| Now that you can get Gemini, operated by Apple (with the Apple
| privacy features that come along with that), why would you ever
| consider going Android/Pixel (outside of running GrapheneOS, but
| I'm talking regular consumers here)?
|
| Google isn't even making anything on the deal with Apple. They
| pay $20B/year to be the default search engine. This is Apple just
| giving a $1B a year discount to that to be able to license
| Gemini.
| cflewis wrote:
| I switched from iPhone to Pixel after I couldn't stand Liquid
| Glass and found myself using Gemini more than I expected.
|
| If you're in the Google ecosystem like Gmail and Calendar, it
| is exceptionally refreshing to be able to use an assistant that
| uses that ecosystem, instead of iOS requiring you to use Mail
| or its own Calendar app.
|
| I don't think there's any real gap between Pixel and iPhone on
| the things that matter: UX jank, battery life, camera. Even the
| messaging issue in the US has closed with encrytped RCS support
| between them launching. So now it's just an ecosystem question,
| which might be why Gemini is mentioned so much with Pixel.
| nicoburns wrote:
| Android phones are also quite a bit more capable than iPhones
| in a number of ways due to being more open. Plenty of people
| just straight up prefer the experience (and plenty of others
| prefer the cheaper prices).
| dofm wrote:
| Yes. And there is only one other major phone brand in the West
| with this kind of clout: Samsung. Who I think _will_ want their
| own thing that isn 't Google's, and who do have some
| connections to OpenAI.
|
| But given how dependent OpenAI are on Samsung, it's hard to
| believe they will see a radically better deal in material
| terms.
| vineyardmike wrote:
| The obvious answer to where the AI Labs get customers is Cloud
| GPUs. Most users (globally) have cheap phones with poor CPUs and
| small amounts of RAM. They can't run usable models locally, and
| it's not clear from the Google-Apple deal if G is selling access
| to their cloud compute as part of that $1B, or just sharing the
| weights/IP.
|
| Apple themselves have said there is usage limits, with a
| subscription upgrade for more usage. So clearly AI Labs are
| directly competing on that front, it's just a normal
| default/chosen decision. Considering there are defaults and still
| successful competitors (eg. safari v chrome), there's no reason
| to think that competition can't handle this too.
|
| Edit: I want to add that Google is also probably willing to give
| the model away at a discount to its true value in exchange for
| guaranteeing that their primary competition (who has tons of
| cash) won't have an economic incentive to enter the foundation
| model training arms race.
|
| Most users who actually want these features for anything more
| serious than summarization and style updates will probably find
| value in a modest subscription or ad-supported tier of higher
| quality models, even if just for occasional usage. Apple can
| provide this, but once you're comparing features, for many
| Gemini/Claude/ChatGPT may be a better fit.
|
| Oh, and I think there is an unfortunate but real risk that once
| again, apple totally over-promises here, and their AI models that
| they ship end up being pretty poor, and that drives users further
| into subscriptions.
| dofm wrote:
| > Oh, and I think there is an unfortunate but real risk that
| once again, apple totally over-promises here, and their AI
| models that they ship end up being pretty poor, and that drives
| users further into subscriptions.
|
| OK, that I would concede is a possibility. Though Gemini is
| clearly capable, and the (alleged) story is that they have
| licensed a one-trillion parameter form of Gemini. I don't think
| they are making the same mistake.
|
| ETA: I also concede they could make a different mistake ;-)
| avidphantasm wrote:
| The AI labs are racing to create a moat out of trillion-
| parameter models and the GPUs that can run them. The problem is
| this is the wrong architecture for most AI inference use cases.
| On-device inference is where this is going, clearly Apple
| believes this too. So Zitron is entirely correct about this AI
| datacenter build out being a boondoggle with no ROI.
| dwaite wrote:
| > Apple themselves have said there is usage limits, with a
| subscription upgrade for more usage.
|
| Specifically for image generation. They haven't indicated you
| have limits for Siri interactions.
| vineyardmike wrote:
| > "Some features, including image generation, have daily
| usage limits because they rely on powerful server models.
| Increased access is available with most iCloud plus
| subscription plans".
|
| Start at 1:07:00 in their announcement video. Craig is
| absolutely talking about "Apple Intelligence" as a whole in
| this segment.
|
| Pragmatically, of course they'd need to add metering to any
| cloud available APIs that rely on large models. There's no
| way they will eat the cost of serving unlimited access to a
| cloud LLM to end users if they won't eat the cost of an image
| generation model.
| brap wrote:
| It always seemed very natural to me that AI will move "down the
| stack", where Open AI and Anthropic don't really have a foot in
| the door.
|
| Who makes consumer devices? Google
|
| Who makes operating systems? Google
|
| Who makes browsers? Google
|
| Who makes the world's most popular websites? Google
|
| By the time 90% of average internet users get to chatgpt.com or
| whatever, they already went through several Google chokepoints,
| each layer is one more place Google can answer their questions.
|
| And that's not even getting into the chips, the data centers, the
| data, the talent, the consumer apps, the enterprise apps, the
| cloud platform, the brand, and of course the biggest cash
| printing machine in human history.
|
| You would honestly have to be insane to bet against G.
| chronci3740 wrote:
| > You would honestly have to be insane to bet against G.
|
| Nah this is just Googler cope
|
| Google missed the AI boat. Period.
| ordinarily wrote:
| Google literally invented the boat (transformers) to be fair.
| dwaite wrote:
| Part of the pitch of AI companies is that they mediate and
| provide a new surface for ads, for taking an affiliate cut of
| sales, etc.
|
| But it isn't like this hasn't been the long-running strategy
| for Google as well - provide more results on search so that
| people don't go to the site with ads, provide paid product
| results for shopping, to offer more services to keep people
| providing personal/behavioral queues to Google and more
| opportunities for ad placement.
|
| If anything, AI turned up the heat such that the frog noticed
| what temperature the pot was. But that doesn't really put them
| in a better position to execute than Google.
| guluarte wrote:
| I think the frontier labs are gonna launch new models under a new
| tier, but they're still figuring out how to announce it.
| loloquwowndueo wrote:
| So I open this page and the first line of the article should be
| the last, right?
|
| > If you liked this piece, you should subscribe to my premium
| newsletter. It's $70 a year
|
| Ok let me read the thing so I can make up my mind... start
| scrolling down and get slapped by some subscribe pop up.
|
| That's where I decided to just cut my losses and go do something
| else.
| jeffreyrogers wrote:
| I'm sort of an AI skeptic but I have been seeing this guy's
| essays for years now and he has always been super pessimistic on
| AI progress.
|
| I think a much more reasoned critique of AI is that of Tyler
| Cowen, whose argument is basically that most processes aren't
| constrained by lack of intelligence but by organizational and
| social factors which mean for AI to be useful you have to
| redesign organizations and work to take advantage of what AI is
| good at. Since most organizations are fairly bureaucratic that
| takes a while, especially in the large industries that are the
| most economically important.
|
| Ed's criticism of the large AI companies seems particularly
| misguided to me since they are the ones actually advancing the
| technology and seem to have real moats given their access to
| large amounts of training data from their users. I don't see any
| possible future in which 5 or 10 years from now there is less AI
| than we have now and I would expect usage to be much higher.
| danny_codes wrote:
| Completely agree. AI is here to stay, it's going to garner more
| and more use overtime. However, I'm skeptical that the
| investments being made right now are at of the right scale & at
| the right time. I completely agree that over time we'll rework
| more and more of our society around LLMs or their successors.
| However, like you say it's a slow process: we have to learn how
| to do it effectively, organizations need to change, people's
| attitudes and behaviors have to adapt. I just don't see is
| "getting there" fast enough to justify current spending levels.
| vatsachak wrote:
| Yeah. Models haven't really improved much from last year to this
| year.
|
| I really love LLMs for debugging and rubber ducking, but I kinda
| want to write all my code.
|
| LLMs tend to have a hard time understanding composition.
| naasking wrote:
| > that the infrastructure being built and compute commitments
| being made are being done so at a level that demands that
| generative AI and AI compute generate over $2 trillion in annual
| revenue by 2030
|
| That seems doable. Next generation architectures and the models
| they produce are accelerating progress. More capable with less
| data and compute, which ironically will drive more demand, aka
| Jevon's paradox.
|
| > If you are someone in the executive team of any major tech
| company, know that your employees are, for the most part,
| completely and utterly miserable.
|
| I agree this is a problem. Adopting too eagerly and too early,
| and not listening to feedback from the people who are using these
| tools is a recipe for disaster.
| lz400 wrote:
| Already many comments saying this but Ed Zitron is not a person I
| trust. He's been so biased and wrong on stuff that I consider
| very obvious and trivial that his complicated analysis with
| numbers and trends I can't just take at face value.
|
| As an example of obvious wrong things, I remember a tweet of his
| where he was mocking people talking about agents and agentic
| coding. He was kind of saying that he was going crazy as agents
| weren't a thing really and people talking about them like they
| were real. Something like "agents?! what agents?! these guys hear
| themselves?!". The answers were full of hundreds of people
| patiently explaining how they were actually _using_ agents. This
| wasn't in 2023, it was a couple of months ago.
|
| He just has an audience and an engagement target. His objective
| is clicks, not informing.
| JoeJonathan wrote:
| He also calls everyone a grifter, when he seems like one
| himself. Im deeply skeptical of our AI overlords, but its
| disingenuous to keep pretwnding theres nothing there.
| Grombobulous wrote:
| He provided a lot of quantitative analysis in this article.
| Perhaps an example or two you think these numbers are off-base
| could help bolster this point?
|
| I think the most compelling part of the article is that these
| numbers point to a situation where the level of investment
| required seems unsustainably high by plain dollars.
|
| You don't really have to agree with the author to see how it
| plays out. OpenAI and SpaceX and Anthropic need to go public
| this year to avoid running out of money. There's no more
| private money, not enough to fund them. The IPO is the last
| funding round.
|
| They can continue growing extremely quickly and AI can still be
| highly useful and maybe be transformative, but still not have
| the money to fund that growth.
|
| That part he wrote about an AI company gone bust canceling
| their Oracle contract made Oracle feel like a Nortel analogy to
| me. If they have a sudden lapse with a big chunk of their
| customers they are writing down triple digit billions of
| dollars.
| lz400 wrote:
| I guess what I'm saying is that I won't look at his numbers
| since he's an unreliable source from my point of view and
| there's a chance that he's going to try to deceive me and
| it's a waste of time for me to listen to him.
|
| I do have other sources of information and I probably agree
| in general that AI companies are doing pretty shady financial
| shenanigans. I even think it's possible that openai is in
| real trouble. But I don't extrapolate that into "AI is
| useless", which is what he does.
| Grombobulous wrote:
| I would agree with you that extrapolating to "AI is
| useless" is definitely a giant step too far, and that part
| of the article ruins a lot of the other interesting bits of
| it.
|
| It's great that he cites a lot of sources but some of them
| aren't great, like the Microsoft story about canceling
| their Claude spend. I think that particular story isn't
| much of an indicator of anything, and it might not even be
| true.
|
| But the financial part...this guy isn't the only person out
| there sounding the alarm about the math not mathing.
| lz400 wrote:
| FWIW I agree the financials are a bit crazy and OpenAI
| went a bit nuts with the circular deals. That said,
| honestly, I don't think it's the end of the world. I
| think there will probably be some correction/crash and it
| will probably be healthy. A lot of these circular deals
| will get canceled, but it's at the end of the day people
| changing imaginary numbers with each other. The
| underlying tech I still think it's revolutionary
| regardless, the same way that the internet was and the
| tech boom crash at the end of the day was a distraction
| from the fact that these companies did end up "ruling the
| world"
| dabedee wrote:
| This is what critical reading is for. It requires you
| examining your own assumptions as much as the text's. If
| you don't engage with something or someone because of your
| own bias or assumptions, that is also willful ignorance;
| you also might end up never updating your prior stance when
| new information emerges.
|
| There is a financial argument and capability argument.
|
| In this case, he doesn't make the claim one follows from
| the other.
| lz400 wrote:
| There's no shortage of sources of information. I'll
| exercise "critical reading" with sources I consider
| trustworthy to begin with. I've no time to engage with
| difficult analysis from people who are not worth the
| effort. You wouldn't engage with every lunacy you read on
| a tabloid, right? similar principle
| dabedee wrote:
| Fair enough. I won't debate preferences or how you choose
| to spend your time. I think one of the merits of his
| articles is that he surveys and gathers sources that
| others can engage with. Even if we admit he is biased,
| that exercise (his writing) alone is valuable because one
| can contradict or reassess his claims.
| no-name-here wrote:
| Grandparent comment's primary claim was that Ed has
| frequently claimed untrue things in the past and so
| questioned why people would continue going to such a source,
| but your reply didn't seem to address that at all?
|
| Someone else separately linked Ed's 2024 claims [1] that:
|
| A. AI revenue had about already maxed out.
|
| B. AI's output accuracy was already about as high as it would
| ever be
|
| C. AI users were already declining or was as high as it would
| ever be.
|
| So we have 3 2024 claims about whether AI was already the
| biggest/best it would ever be, and whether AI usage was even
| already shrinking. All ended up being the opposite of true.
|
| Have you looked at whether Ed's previous claims that went
| against popular AI views and are testable ended up being true
| or not?
|
| Does it matter whether an author's claims like that are true
| or not for whether you will continue consuming them?
|
| If straightforward claims like the above are so easily
| disprovable, what makes you believe that he isn't cherry-
| picking other stats in order to spread misinformation or
| disinformation, as the individual stats he points to might
| even be completely true, but if they are cherry-picked, they
| may be more misleading than elucidative?
|
| If someone has a multi-year history of frequently spreading
| false claims, should we trust their predictions about future
| events more than other sources?
|
| [1] https://news.ycombinator.com/item?id=48447549
| dghlsakjg wrote:
| His numbers are based on sources that he says he doesn't trust,
| which is quite interesting. While he may be directionally
| accurate (eg. The revenue needed to match the spend seems lofty
| at best) he seems to be mixing and matching numbers to create a
| worst case scenario that doesn't necessarily line up with
| reality. Combined with his complete unwillingness to be open
| minded about anything even tangentially related to AI, and I
| can't take him that seriously.
|
| Publications love a doom and gloom rant, which is why he seems
| to have built an entire career on hysterical anti-ai screeds.
| It doesn't mean that he's right though.
| w29UiIm2Xz wrote:
| It's disappointing that this article got mindshare when a more
| neutral author could better argue the bearish case for AI
| valuations. I want the steelman argument from a more respected
| individual.
|
| The problem is when untrusted authors take positions, then it
| circulates widely, then people discredit the author and by
| proxy the position, when the position could be correct.
|
| The article has a number of emotional appeals in it. Something
| more focused on raw numbers would foster more curious
| discussion.
| akoboldfrying wrote:
| It's possible that AI is the greatest technological leap forward
| since the Industrial Revolution, and simultaneously a bubble that
| will pop in the near future.
|
| I don't know much about the economics side; TFA gives a barrage
| of stats that seem to make a compelling case for bubblehood.
| OTOH, the claims about the utility of LLMs being unmeasurable are
| weak (the same criticism applies to hiring programmers, or indeed
| most office workers) and the metal spider straw man is frankly
| embarrassing to anybody who has actually used recent frontier
| agents for programming and seen what they can do.
| datsci_est_2015 wrote:
| Always a bit eyebrow-raising to me how much people focus on Ed's
| style rather than his message, which is, broadly, that the tech
| industry is deeply morally corrupted. He struggles to speak about
| it without becoming impassioned, but I read it as incredulousness
| rather than baseless hyperbole: "How are you still investing in
| and working for companies like Meta, despite the overwhelming
| evidence that they are terrible company that does terrible things
| to people?"
| minimaxir wrote:
| Style is relevant to how humans communicate and it's not always
| about the message, and it can sometimes work against it. AP
| Style is an editorial standard for a reason.
|
| IF I WROTE AN ENTIRE BLOG POST IN ALL CAPS ABOUT HOW AI IS
| LITERALLY SATAN PEOPLE WOULD JUST THINK I AM A CRAZY PERSON
| tsunamifury wrote:
| You're right style does matter, and the flat tone of AP is
| basically extinct now because it was not a meaningful or
| widely desired style.
| bawolff wrote:
| > his message, which is, broadly, that the tech industry is
| deeply morally corrupted
|
| If that's his message, why is he going on about ecconomic
| sustainability? Whether or not you have a coherent business
| model has nothing to do with how morally corrupt you are.
|
| Ultimately i agree with the GP post, the article reads like
| something preaching to the choir. If you already agree it seems
| natural. If you don't agree it looks like an incoherent rant
| that is not particularly convincing.
| datsci_est_2015 wrote:
| Arguing against the business model is a method of exposing
| the tactics of AI businesses as a short term grift rather
| than a principled venture. The entire economy suffers when
| grifters profit - there's not infinite money to spread
| around.
| bawolff wrote:
| Is it really a grift when everyone knows? Its not like they
| are keeping their financials secret. Heck, the main AI
| companies aren't even public yet, so its largely
| sophisticated investors getting "grifted".
|
| Normally a grift involves tricking someone. The AI
| situation seems more like a bunch of investors knowingly
| investing in something very speculative. If they lose their
| money, while that is the nature of speculative investments.
| overgard wrote:
| Elon Musk just got the rules of the NASDAQ changed so he
| can more or less force index funds to buy his shell
| company and take money from people's 401k. Feels very
| grifty to me.
| zetanor wrote:
| This is the kind of thing that the people in power really don't
| want you to know, but I'll say it anyway because if we don't
| get the message out, it's just another free win for the Nazis:
| a bad presentation is a poor information medium.
| labrador wrote:
| Missing from Zitron's calculations is government
| ownership/bailout of American AI in national security interest
| and winning the race to AGI with China. Trump has been making
| noise lately of owning 50% of these companies. Taxpayers will
| prop them up in other words.
| KennyBlanken wrote:
| This is apparently news to all the hardware retailers who are
| continuing to maintain the insanely overinflated prices on NVME
| storage, DDR5, and even DDR4 memory.
|
| Some are still steadily increasing prices.
|
| A 1TB NVME drive - a good one - cost about $70. Now it costs
| anywhere from $150 for shit-tier drives to $300+ for the higher
| end stuff that used to cost $100-120.
| LoganDark wrote:
| > currently gooning
|
| > No matter how horny or flaccid you are
|
| These analogies are great.
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