[HN Gopher] Google "We have no moat, and neither does OpenAI"
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Google "We have no moat, and neither does OpenAI"
Author : klelatti
Score : 1196 points
Date : 2023-05-04 10:19 UTC (12 hours ago)
(HTM) web link (www.semianalysis.com)
(TXT) w3m dump (www.semianalysis.com)
| berkle4455 wrote:
| Shorting Google is the best possible bet is my read.
| JumpCrisscross wrote:
| > _At the beginning of March the open source community got their
| hands on their first really capable foundation model, as Meta's
| LLaMA was leaked to the public_
|
| A Prometheus moment if I've ever seen one.
| dahwolf wrote:
| The current paradigm is that AI is a destination. A product you
| go to and interact with.
|
| That's not at all how the masses are going to interact with AI in
| the near future. It's going to be seamlessly integrated into
| every-day software. In Office/Google docs, at the operating
| system level (Android), in your graphics editor (Adobe), on major
| web platforms: search, image search, Youtube, the like.
|
| Since Google and other Big Tech continue to control these
| billion-user platforms, they have AI reach, even if they are
| temporarily behind in capability. They'll also find a way to
| integrate this in a way where you don't have to directly pay for
| the capability, as it's paid in other ways: ads.
|
| OpenAI faces the existential risk, not Google. They'll catch up
| and will have the reach/subsidy advantage.
|
| And it doesn't end there. This so-called "competition" from open
| source is going to be free labor. Any winning idea ported into
| Google's products on short notice. Thanks open source!
| titzer wrote:
| > It's going to be seamlessly integrated into every-day
| software.
|
| I...kinda don't want this? UIs have already changed in so many
| different fits, starts, waves, and cycles. I used to have
| skills. But I have no skills now. Nothing works like it used
| to. Yeah they were tricky to use but I cannot imagine that a
| murky AI interface is going to be any easier to use, and
| certainly impossible to master.
|
| Even if it _is_ easier to use, I am not sure I want that
| either. I don 't know where the buttons are. I don't know what
| I can do and what I can't. And it won't stay the same, dodging
| my feckless attempts to commit to memory how it works and get
| better at it...?
| jjoonathan wrote:
| It was a sad day when I realized I was systematically
| overinvesting in skills on churning technology and that my
| investments would never amortize. Suddenly my parents'
| stubborn unwillingness to bother learning anything
| technological made complete sense and I had to sharply adjust
| my own patience threshold sharply downwards.
| TeMPOraL wrote:
| There are some software tools where the investment pays
| back, and has been over decades. Microsoft Office (in part
| because it's not reinventing itself, but rather accrues new
| features; in part because everyone else copies its UI
| patterns). Photoshop. Emacs.
|
| With modern software, I find it that there isn't much to
| learn at all - in the past decade, seems to only be
| _removing_ features and interaction modes, never adding
| anything new.
|
| Still, I don't regret having learned so much all those
| years ago. It gives me an idea what the software _could_
| do. What it was _supposed to_ do. This means I often think
| of multi-step solutions for problems most people around me
| can 't solve unless there's a dedicated SaaS for it. As
| frustrating as it often is to not be able to do something
| you could 10 years ago, sometimes I discover that some of
| the more advanced features still remain in modern toy-like
| software.
| amelius wrote:
| An AI interface in Office brings back memories of Clippy.
| patmorgan23 wrote:
| OpenAI=Microsoft for all intents and purposes.
|
| Microsoft has a stake in OpenAI and has integrated into Azure,
| Bing and Microsoft 365.
| TeMPOraL wrote:
| Honestly, I can't see Google failing here. Like other tech
| giants, they're sitting on a ridiculously large war chest.
| Worst case, they can wait for the space to settle a bit and
| spend a few billion to buy the market leader. If AI really is
| an existential threat to their business prospects, spending
| their reserves on this is a no-brainer.
| blowski wrote:
| That was true for IBM in the 1970s and Microsoft in the 90s.
| Despite holding a royal flush, they managed to lose the game
| through a combination of arrogance, internal fighting,
| innovator's dilemma, concern over anti-trust, and
| bureaucratic inertia. It will be hard for Google to pull this
| off.
| quickthrower2 wrote:
| Microsoft aint doing so bad now
| aero-deck wrote:
| Disagree. What you have in mind is already how the masses
| interact AI. There is little value-add for making machine
| translation, auto-correct and video recommendations better.
|
| I can think of a myriad of use-cases for AI that involve
| custom-tuning foundation models to user-specific environments.
| Think of an app that can detect bad dog behavior, or an app
| that gives you pointers on your golf swing. The moat for AI is
| going to be around building user-friendly tools for fine-tuning
| models to domain-specific applications, and getting users to
| spend enough time fine-tuning those tools to where the switch-
| cost to another tool becomes too high.
|
| When google complains that there is no moat, they're
| complaining that there is no moat big enough to sustain
| companies as large as Google.
| narrator wrote:
| I think the problem with AI being everywhere and ubiquitous is
| that AI is the first technology in a very long time that
| requires non-trivial compute power. That compute power costs
| money. This is why you only get a limited number of messages
| every few hours from GPT4. It simply costs too much to be a
| ubiquitous technology.
|
| For example, the biggest LLama model only runs on an A100 that
| costs about $15,000 on ebay. The new H100 that is 3x faster
| goes for about $40,000 and both of these cards can only support
| a limited number of users, not the tens of thousands of users
| who can run off a high-end webserver.
|
| I'd imagine Google would lose a lot of money if they put GPT4
| level AI into every search, and they are obsessed with cost per
| search. Multiply that by the billions and it's the kind of
| thing that will not be cheap enough to be ad supported.
| rileyphone wrote:
| You can run it (quantified at least) on a $4000 Mac thanks to
| Apple's unified memory. Surely other manufacturers are
| looking for how to expand VRAM, hopefully Intel or AMD.
| Animats wrote:
| It's a win for Google that LLMs are getting cheaper to run.
| OpenAI's service is too expensive to be ad-funded. Google
| needs a technology that's cheaper to provide to maintain
| their ad-supported business model.
| patrickk wrote:
| Google could make a bet like they did with YouTube.
|
| At the time, operating YouTube was eye wateringly expensive
| and lost billions. But google could see where things were
| going: a triple trend of falling storage costs, falling
| bandwidth and transmission costs (I'm trying to dig up a
| link I read years ago about this but google search has
| gotten so shit that I can't find it).
|
| It was similar for Asic miners for Bitcoin. Given enough
| demand, specialised, lower cost hardware specially for LLMs
| will emerge.
| Certhas wrote:
| The article talks about this explicitly though. Reasonably
| good models are running on raspberry Pis now.
| james-revisoai wrote:
| You're right and this is why they didn't heavily use BERT(in
| the full sense), arguably the game-changing NLP model of the
| 10s. They couldn't justify bringing the cost per search up.
| unicornmama wrote:
| This cost argument is being overblown. While it's a
| limitation for today's product, enginners are very good at
| optimization. Therefore the costs will drop in the medium to
| long term from efforts on both the software and hardware
| side.
| ok123456 wrote:
| Within a decade mid-level consumer cards will be just as
| powerful as those $40k cards.
| [deleted]
| bcrosby95 wrote:
| Considering how long it took mid level consumer cards to
| beat my $600 1080, you're way more optimistic than I am.
| airstrike wrote:
| Time for a dedicated "AI box" at home with hotswapping
| compute boards? Maybe put it inside a humanoid or animal-like
| robot with TTS capabilities?
|
| Sign me up for that kickstarter!
|
| EDIT: based on some quick googling (should I have asked
| ChatGPT instead?), Nvidia sells the Jetson Xavier Nx dev kit
| for ~$610 https://www.electromaker.io/shop/product/nvidia-
| jetson-xavie...
|
| Just need the robot toy dog enclosure
|
| (See https://www.electromaker.io/blog/article/best-sbc-for-
| ai-sin... for a list of alternatives if that one is too
| expensive)
| yayr wrote:
| each billion parameters using 16 bit floats requires around
| 2 GB of GPU or TPU RAM. ChatGPT is expected to have around
| 1000 billion. Good open source LLMs have around 7-20
| billion currently. Consumer GPUs currently max out at 24
| GB. You can now quantize the model to e.g. 4 bits instead
| of 32 per parameter and do other compressions, but still
| there is quite a limit what you can do with 24 GB of RAM.
| The Apple unified memory approach may be a path forward to
| increase that... so one box gives you access to the small
| models, for a GPT4 like model you'd need (for inference and
| if you had the model and tools) probably 100 of those 4090s
| or 25 of H100 with 96 GBs I guess to fit in 2 TB of model
| data.
| niemandhier wrote:
| Currently we do not explore sparsity. The next iteration
| of models will be much more compact by focusing on
| reducing effective tensor size.
| bee_rider wrote:
| It seems like a ton of engineering effort has been put
| into these neural network frameworks. How didn't they
| explore sparsity yet? With numerical linear algebra
| that's, like, the most obvious thing to do (which is to
| say, you probably know beforehand if your problem can be
| mapped to sparse matrices).
| [deleted]
| version_five wrote:
| I think this won't work out: AI is so populat now because it's
| a destination. It's been rebranded as a cool thing to play
| with, that anyone can immediately see the potential in. That
| all collapses when it's integrated into Word or other
| "productivity" tools and it just becomes another annoying
| feature that gives you some irrelevant suggestions.
|
| OpenAI has no moat, but at least they have first mover
| advantage on a cool product, and may be able to get some chumps
| (microsoft) to think this will translate into a lasting feature
| inside of office or bing.
| kelipso wrote:
| To be fair, the open source model has been what's been working
| for the last few decades. The concern with LLMs was that open
| source (and academia) couldn't do what the big companies are
| doing because they couldn't get access to enough computing
| resources. The article is arguing (and I guess open source ML
| groups are showing) you don't need those computing resources to
| pave the way. It's still an open question whether OpenAI or the
| other big companies can find a most in AI via either some
| model, dataset, computing resources, whatever. But then you
| could ask that question about any field.
| dahwolf wrote:
| That makes sense. But I would argue to smaller/cheaper models
| are not a threat to Google, they are a solution. They will
| still have the reach advantage and can more cheaply integrate
| small/low costs models at every touch point.
| not2b wrote:
| But none of the "open source" AI models are open source in
| the classic sense. They are free but they aren't the source
| code; they are closer to a freely distributable compiled
| binary where the compiler and the original input hasn't been
| released. A true open source AI model would need to specify
| the training data and the code to go from the training data
| to the model. Certainly it would be very expensive for
| someone else to take this information, build the model again,
| and verify that the same result is obtained, and maybe we
| don't really need that. But if we don't have it, then I think
| we need some other term than "open source" to describe these
| things. You can get it, you can share it, but you don't know
| what's in it.
| kelipso wrote:
| I agree with you to the extent that yeah technically it's
| not open source because the data is not known. But for
| these foundation models like Llama, the model structure is
| obviously known, pretty sure (didn't check) the
| hyperparameters used to train the model is known, the
| remaining unknown of data, it's pretty much the same for
| all foundation models, CommonCrawl etc. So replicating
| Llama once you know all that is a mechanical step and so
| isn't really closed source in a sense. Though probably some
| new term open something is more appropriate.
|
| The real sauce is the data you fine tune these foundation
| models on, so RLHF, specific proprietary data for your
| subfield, etc. The model definition, basically Transformer
| architecture and a bunch of tricks to get it to scale are
| mostly all published material, hyper parameters to train
| the model are less accessible but also part of published
| literature; then the data and (probably) niche field you
| apply it to becomes the key. Gonna be fun times!
| kbrkbr wrote:
| RWKV does: https://github.com/BlinkDL/RWKV-LM It uses ,,the
| Pile": https://pile.eleuther.ai/ And I've seen some more in
| the last weeks.
| not2b wrote:
| Good to hear. Let's reserve "open source" for cases like
| that.
| 4ndrewl wrote:
| This is 100% correct - products evolve to become features. Not
| sure OpenAI faces the existential risk as MS need them to
| compete with Google in this space.
| chabons wrote:
| > Not sure OpenAI faces the existential risk as MS need them
| to compete with Google in this space.
|
| I think OP is arguing that in that partnership Microsoft
| holds the power, as they have the existing platforms. The
| linked article argues that AI technology itself is not as
| much of a moat as previously thought, and the argument
| therefore is that Microsoft likely doesn't need OpenAI in the
| long term.
| unicornmama wrote:
| Google makes almost all its money from search. These platforms
| are all there to reinforce its search monopoly. ChatGPT has
| obsoleted search. ChatGPT will do to Google search what the
| Internet did to public libraries - make them mostly irrelevant.
| baryphonic wrote:
| How has ChatGPT obsoleted search, when hallucination and the
| token limits are major problems?
|
| It's (sort of) obviated search for certain kinds of queries
| engineers make, but not normies.
|
| I say sort of, because IMO it's pretty bad at spitting out
| accurate (or even syntactically correct) code for any
| nontrivial problem. I have to give it lots of corrections,
| and often it will just invent new code that also is broken in
| some way.
| standyro wrote:
| I think you're underestimating product-market fit.
|
| Normies don't care about the exact truth
| unicornmama wrote:
| I've replaced almost all my usage of Google Search with
| ChatGPT. The only reason's I've had to use Google search is
| to look up current news, and do some fact checking. In my
| experience, GPT-4 rarely provides incorrect results. This
| includes things like asking for recipes, food
| recommendations, clarifying what food is safe to eat when
| pregnant, how to drain my dog tricks, translating
| documents, explaining terminology from finance,
| understanding different kinds of whiskey, etc.
| lexandstuff wrote:
| This was true for me too, but I'm starting to find the
| data's cutoff date a problem, and it gets worse every
| day. I was reminded about it yesterday when it knew
| nothing about the new programming language Mojo or recent
| voice conversion algorithms.
|
| The eventual winner will have a model that stays up-to-
| date.
| james-revisoai wrote:
| It's mentioned in the article, but LoRA or RAG will
| enable this.
|
| Phind is getting awfully close to this point already
| really. Integrating new knowledge isn't a bottleneck like
| we know from expert systems, I think it just hasn't been
| a priority for research and commercial reasons, till
| recently.
| zoiksmeboiks wrote:
| [dead]
| bhl wrote:
| > It's going to be seamlessly integrated into every-day
| software. In Office/Google docs, at the operating system level
| (Android), in your graphics editor (Adobe), on major web
| platforms: search, image search, Youtube, the like
|
| Agreed but I don't think the products that'll gain market share
| from this wave of AI will be legacy web 2 apps; rather it'll be
| AI-native or first apps that are build from ground up to
| collect user data and fulfill user intent. Prime example is
| TikTok.
| vosper wrote:
| > OpenAI faces the existential risk, not Google.
|
| Yes, but the quickest way for anyone to get themselves to
| state-of-the-art is to buy OpenAI. Their existential risk is
| whether they continue to be (semi)independent, not whether they
| shutdown or not. Presumably Microsoft is the obvious acquirer,
| but there must be a bunch of others who could also be in the
| running.
| sgt101 wrote:
| But if you wait a month you can get that model for free...
| irrational wrote:
| It being everywhere worries me a lot. It outputs a lot of false
| information and the typical person doesn't have the time or
| inclination to vet the output. Maybe this is a problem that
| will be solved. I'm not optimistic on that front.
| mattferderer wrote:
| Same can be said about the results that pop up on your
| favorite search engine or asking other people questions.
|
| If anything advances in AI & search tech will do a better job
| at providing citations that agree & disagree with the results
| given. But this can be a turtles all the way down problem.
| ngngngng wrote:
| Really interesting to look at this from a product perspective.
| I've been obsessively looking at it from an AI user perspective,
| but instead of thinking of it as a "moat", I just keep thinking
| of the line from Disney's The Incredibles, "And when everyone is
| super, no one will be."
|
| Every app that I might build utilizing AI is really just a
| window, or a wrapper into the model itself. Everything is easy to
| replicate. Why would anyone pay for my AI wrapper when they could
| just build THING themselves? Or just wait until GPT-{current+1}
| when the model can do THING directly, followed swiftly by free
| and open source models being able to do THING as well.
| sdenton4 wrote:
| Just gotta get to the point where we can just ask the model to
| code the wrapper we want to use it with...
| ngngngng wrote:
| Any wrapper that needs writing speaks to a gap in the AI's
| current capabilities. I just don't see why or how I would put
| man-hours into trying to close that gap when a future model
| could eclipse my work at any time.
| unraveller wrote:
| you've got future frostbite
| Nick87633 wrote:
| Because people pay for convenience, and may not be technical
| enough to stay up to date on the latest and best AI company for
| their use case. Presumably your specialized app would switch to
| better AI instances for that use case as they come along in
| which case they're paying for your curation as well.
| ngngngng wrote:
| Maybe. It just seems to me that every single angle of AI has
| this same moat issue.
|
| It's like the generation ship problem. Send a ship to the
| stars today, and before it gets there technology might
| advance such that the second ship we send gets there before
| the first.
|
| How do you justify the capital necessary to stand out in an
| AI driven marketplace when the next models could make your
| business obsolete at any time?
| whimsicalism wrote:
| > Giant models are slowing us down. In the long run, the best
| models are the ones which can be iterated upon quickly. We should
| make small variants more than an afterthought, now that we know
| what is possible in the <20B parameter regime.
|
| Maybe this is true for the median query/conversation that people
| are having with these agents - but it certainly has not been what
| I have observed in my experience in technical/research work.
|
| GPT-4 is legitimately very useful. But any of the agents below
| that (including ChatGPT) cannot perform complex tasks up to
| snuff.
| pbhjpbhj wrote:
| My understanding was that most of the current research effort
| was towards trimming and/or producing smaller models with power
| of larger models, is that not true?
| goatlover wrote:
| Doesn't mean the smaller models are anywhere close to the
| capabilities of GPT-4.
| akhayam wrote:
| The real moats in this field will come from the hardware
| industry. It's way too expensive to train these models on general
| purpose compute. Vertically designed silicon that brings down the
| unit economics of training and inference workloads are already
| being designed, in industry and in academia.
| danielmarkbruce wrote:
| NVIDIA already has a big moat in this area. It might not last
| forever, but at least for a good while they have a big one.
| amelius wrote:
| Intelligence is becoming a commodity.
| SanderNL wrote:
| I have been toying around with Stable Diffusion for a while now
| and becoming comfortable with the enormous community filled with
| _textual inversions_ , _LoRAs_ , _hyper networks_ and
| _checkpoints_. You can get things with names like "chill blend",
| a fine-tuned model on top of the SD with the author's personal
| style.
|
| There is something called automatic1111 which is a pretty
| comprehensive web UI for managing all these moving parts. Filled
| to the brim with extensions to handle AI upscaling, inpainting,
| outpainting, etc.
|
| One of these is ControlNet where you can generate new images
| based on pose info extracted from an existing image or edited by
| yourself in the web based 3d editor (integrated, of course). Not
| just pose but depth maps, etc. All with a few clicks.
|
| The level of detail and sheer amount of _stuff_ is ridiculous and
| it all has meaning and substantial impact on the end result. I
| have not even talked about the prompting. You can do stuff like
| [cow:dog:.25] where the generator will start with a cow and then
| switch over at 25% of the process to a dog. You can use parens
| like ((sunglasses)) to focus extra hard on that concept.
|
| There are so called LoRAs trained on specific styles and/or
| characters. These are usually like 5-100MB and work unreasonably
| well.
|
| You can switch over to the base model easily and the original SD
| results are 80s arcade game vs GTA5. This stuff has been around
| for like a year. This is ridiculous.
|
| LLMs are enormously "undertooled". Give it a year or so.
|
| My point by the way is that any quality issues in the open source
| models will be fixed and then some.
| int_19h wrote:
| Local LLMs already have a UI intentionally similar to
| AUTOMATIC1111, including LoRAs, training with checkpoints,
| various extensions including multimodal and experimental long-
| term memory etc.
|
| https://github.com/oobabooga/text-generation-webui
| Der_Einzige wrote:
| I wrote a whole gist about this exact thing!!!!
|
| https://gist.github.com/Hellisotherpeople/45c619ee22aac6865c...
| yyyk wrote:
| The memo sounds like spin because it is. The surface argument is
| equivalent to arguing that no one could sell closed source
| software because open source exists, and that open source must
| also be commodotized (oddly, Apple and Microsoft are doing just
| fine). The implied argument is that Google Research was doing
| fine giving away their trade secrets and giving negative value to
| Google because it was going to happen anyway and the secrets are
| financially worthless anyhow.
|
| Nonsense. There are moats if one is willing to look for them.
| After all, productizing is a very different thing from an
| academic comparison. ChatGPT is way out there _as a product_,
| while open efforts are at 0% on this. You can't lock down a
| technology*, but you can lock down an ecosystem, a product or
| hardware. OpenAI can create an API ecosystem which will be
| difficult to take down. They can try to make custom hardware to
| make their models really cheap to run. Monopoly? Nah. This won't
| happen. But they could make some money - and reduce the value of
| Google's search monopoly.
|
| * Barring software patents which fortunately aren't yet at play.
|
| EDIT: I'll give the memo a virtual point for identifying Meta
| (Facebook) as a competitor who could profit by using current OSS
| efforts. But otherwise it's just spin.
| burnished wrote:
| How do you distinguish between an opinion you disagree with and
| 'spin'?
| yyyk wrote:
| A) When IMHO the underlying argument is not quite honest.
|
| B) When it comes from an interested party.
|
| C) When there's enough of A and B that I feel it's
| intentional.
|
| The underlying argument here would apply to some extremely
| profitable existing closed source software, so it's
| _obviously_ not complete. Even closed source software which
| is strictly inferior manages to find some very profitable
| moats.
|
| As for the source, it comes from Google Research, which has
| done a very poor job of using their knowledge to benefit
| Google. The article downplays the failures (we couldn't have
| done anything differently, but it doesn't matter anyway since
| Open Source will consume all!), and doesn't even _think_
| about productization.
|
| The latter does give me a little bit of doubt: the article
| could also be emblematic of Google Research's failures and
| not 100% spin...
| burnished wrote:
| Thank you for the cogent response.
|
| My reading was that this was personal opinion of a
| researcher, it seems like you are reading the deficiencies
| you note as intentional omissions whereas I am reading them
| as simple flaws.
|
| Does it change your perspective that this was aimed at a
| private audience? To me it came off as a blanket admission
| that they were not doing the right thing and needed to do
| something different to be successful. That may be the core
| difference, I read it as blame accepting whereas you read
| it as blame deflecting.
| yyyk wrote:
| >Does it change your perspective that this was aimed at a
| private audience?
|
| Was it? Someone leaked the article to the press. Per the
| article, someone granted permission to publish the leak.
| I'm assuming that someone had standing to give said
| permission, either from Google Research or being the
| author. I can see a scenario when someone intentionally
| 'leaks' in order to put something in the public sphere
| without attribution. Perhaps I'm too uncharitable or too
| cynical.
|
| Still, I find the underlying argument too simplistic.
|
| At $WORK, we have some $SOFTWARE that certain $CLIENTS
| run on Windows Server. It would be cheaper if they ran it
| on Linux. I have good confidence it would work the same,
| and we could test with the typical deployment patterns.
| The typical $CLIENT attitude is to not even think about
| this ("We don't have anyone to manage a Linux deployment,
| and $$client of $CLIENT wouldn't even hear of Linux, we
| barely got a current deployment plan approved").
|
| Arguing that Open Source Linux could do everything that
| Windows Server can or that Linux development speed is
| higher wouldn't do anything to change their mind - it's
| based on other factors, and even if we finally got past
| that there would be ROI to consider (compared to other
| things that could be done in the same time).
| endorphine wrote:
| What does "spin" mean?
| ChicagoBoy11 wrote:
| The question I'd love to be able to ask the author is how, in
| fact, this is different from search. Google successfully built a
| moat around that, but one can argue, too, that it should not have
| been long-lived. True, there was the secrete page-rank sauce, but
| sooner or later everyone had that. Other corporations could crawl
| anything and index whatever at any cost (i.e. Bing), yet search,
| which is in some sense also a commodity heavily reliant on models
| trained partly on user input, is what underpins Google's success.
| What about that problem allowed it to successfully defend it for
| so long, and why can't you weave a narrative that something like
| that might, too, exist for generative AI?
| frabcus wrote:
| One example - they mine people's labour of searching beyond the
| first page of results - so when a small % of people really dig
| into results, they can infer which the good sites are deeper in
| (e.g. by when you settle on one).
|
| Bing doesn't have enough traffic to do this as well, so is less
| good at finding quality new sites, reducing overall quality.
|
| Source: Doing SEO, but about 8 years ago now, the ecosystem
| will have changed.
| politician wrote:
| If the moat is simply brand name recognition, then the market
| leader is OpenAI. That's an existential problem for Google and
| explains the author's perspective.
| wg0 wrote:
| Google's best bet to topple the existing advantage from the
| competition is to train a model on their whole giant internet
| index on their own compute cloud and then release that model
| under GPL v3.0/Apache/MIT/CC license.
|
| This will eliminate first mover advantage for the competition.
| These models (by OpenAPI et el.) however, cannot be monetised
| indefinitely just like in past compilers, kernels and web servers
| could not be monetised indefinitely.
|
| These days, majority of the computing is on GCC, Clang, LLVM and
| Linux which wasn't the case at one point and even Intel used to
| sell their own compiler (not sure of the current status)
| tikkun wrote:
| The part of the post that resonates for me is that working with
| the open source community may allow a model to improve faster.
| And, whichever model improves faster, will win - if it can
| continue that pace of improvement.
|
| The author talks about Koala but notes that ChatGPT is better.
| GPT-4 is then significantly better than GPT-3.5. If you've used
| all the models and can afford to spend money, you'd be insane to
| not use GPT-4 over all the other models.
|
| Midjourney is more popular (from what I'm seeing) than Stable
| Diffusion at the moment because it's better at the moment.
| Midjourney is closed-source.
|
| The point I'm wanting to make is that users will go to whoever
| has the best model. So, the winning strategy is whatever strategy
| allows your model to compound in quality faster and to continue
| to compound that growth in quality for longer.
|
| Open source doesn't always win in producing better quality
| products.
|
| Linux won in servers and supercomputing, but not in end user
| computing.
|
| Open-source databases mostly won.
|
| Chromium sorta won, but really Chrome.
|
| Then in most other areas, closed-source has won.
|
| So one takeaway might be that open-source will win in areas where
| the users are often software developers that can make
| improvements to the product they're using, and closed-source will
| win in other areas.
| randomdata wrote:
| _> Linux won in servers and supercomputing, but not in end user
| computing._
|
| It seems just about every computing appliance in my home runs
| Linux. Then you have Android, ChromeOS, etc. which are also
| quite popular with end users, the first one especially. It may
| not have won, but I think it is safe to say that it is
| dominating.
| jononor wrote:
| Appliances are not end user computing, but embedded computing
| - the OS is incidental and under full control of the
| manufacturer. Some might argue that even mobile phones are
| not sufficiently under the control of end users to qualify.
| randomdata wrote:
| _> Appliances are not end user computing_
|
| They are when the end user is using them. Think things like
| TVs or even thermostats.
|
| _> the OS is incidental and under full control of the
| manufacturer._
|
| For all intents and purposes Linux _has_ won where those
| conditions aren't met.
| seydor wrote:
| None of the models will "win" because it is just a foundation.
| Google won because they leveeraged the linux ecosystem to build
| a monetizable business with a moat on top of it. The real moat
| will be some specific application on top of LLMs
| hospitalJail wrote:
| >Midjourney is more popular (from what I'm seeing) than Stable
| Diffusion at the moment because it's better at the moment.
| Midjourney is closed-source.
|
| Midjourney is easier, its not better. The low barrier to entry
| has it popular, but it isnt as realistic, doesnt follow the
| prompt as well, and has almost no customization.
|
| SD is the holy grail of AI art, if you can afford a computer or
| server to run SD + have the ability to figure out how to
| install python, clone Automatic1111 from git, and run the
| installer, its the best. Those 3 steps are too much for most
| people, so they default to something more like an app. Maybe it
| is too soon, but it seems SD has already won. MJ is like using
| MS paint, where SD is like photoshop.
| BoorishBears wrote:
| I have SD up on a machine with a 3090 and it can't produce
| output half as good as MJ without a ton of work.
|
| I use SD to augment MJ, like fixing hands with specific LORAs
| for example, so I definitely appreciate that it exists. But
| for actually creating a full image in one shot, they're not
| even comparable.
| yieldcrv wrote:
| Midjourney retrains itself, I have one click installer apps
| for SD, Midjourney and the live prompt community is very good
|
| None of this stuff is copyrightable so I dont care that its
| not private
| dragonwriter wrote:
| > SD is the holy grail of AI art, if you can afford a
| computer or server to run SD + have the ability to figure out
| how to install python, clone Automatic1111 from git, and run
| the installer, its the best.
|
| If you can afford Colab (which is free if you don't want to
| use it too much), you can just click one of the existing
| A1111 colabs and run that, you don't need to figure out
| python, git, or A1111 installs.
| kyleyeats wrote:
| Google is cracking down on this recently.
| flangola7 wrote:
| Cracking down on what exactly?
| LordDragonfang wrote:
| Free Colabs have started blocking any SD web-ui it detects
| (presumably because it's meant as a community service for
| ML researchers, not for people who want to play hentai
| gacha, and they're running out of server time)
| robinsord wrote:
| [dead]
| contravert wrote:
| I just want to add my $0.02 currently working at a games
| studio that is integrating AI generated art into our art
| pipelines.
|
| Midjourney definitely generates really high quality art based
| on simple prompts, but the inability to really customize the
| output basically kills its utility.
|
| We heavily use Stable Diffusion with specific models and
| ControlNet to get customizable and consistent results. Our
| artists also need to extensively tweak and post-process the
| output, and re-run it again in Stable Diffusion.
|
| This entire workflow is definitely beyond a Discord-based
| interface to say the least.
| netdur wrote:
| use https://github.com/deep-floyd/IF, it uses LLM to
| generate exact art you need.
| jamilton wrote:
| The image quality of DeepFloyd is much lower than Stable
| Diffusion 1.5 though, it's a pretty major tradeoff. Can
| definitely be part of the workflow since it really is
| good at composition, but right now it's not a
| replacement.
| jononor wrote:
| If you would give a talk about this, I would watch it -
| despite being out of the graphics for almost 10 years now.
| Really want to hear from the trenches about the workflows,
| benefits and challenges you have.
| ketzo wrote:
| Do you have a link to a decent tutorial for someone to do
| what you're describing in the last paragraph?
| xhrpost wrote:
| It took me a little hunting, but thanks to Reddit I
| eventually found a cloud-gpu host that provides a working
| Stable Diffusion image. So you basically don't have to do
| anything that GP said. Everything is installed and you just
| rent the hardware.
|
| https://www.runpod.io/console/templates
|
| Look for "RunPod Stable Diffusion". I spent a whole
| $0.35/hr playing around with my own SD instance that I had
| running in minutes.
| jamilton wrote:
| You can do the same thing on vast.ai too.
|
| It's a little inconvenient to use non-base models and
| plugins this way (you pay extra for more storage), but
| it's definitely an easy way to use the full power of SD.
| ZephyrBlu wrote:
| 35c/hr seems crazy expensive compared to Midjourney.
| Midjourney gives you set fast hours (Immediate GPU) and
| unlimited relaxed hours (Delayed GPU). It also has a lot
| of built-in parameters you can use to easily tweak
| images. I'd rather pay for MJ than run my own SD.
|
| The main upside of running your own SD is that you can
| completely automate it, but I'm not sure how useful that
| really is.
| dragonwriter wrote:
| > The main upside of running your own SD is that you can
| completely automate it
|
| No, the main upside of running your own SD web UI is that
| you can select and deploy your own checkpoints (not just
| using the base SD models), LoRas, embeddings, upscaling
| models, and UI plugins supporting additional
| services/models/features like multidiffusion (bigger gens
| and controls of which areas within the image different
| prompts apply to), ControlNet and associated models,
| video synthesis, combinatorial prompts, prompt shifting
| during generation to do blending effects, and, well, a
| million other things.
|
| Also, you can completely automate it.
| ImprobableTruth wrote:
| The midjourney price would be equivalent to ~100 hours
| cloud time. How is that crazy expensive?
| enlyth wrote:
| https://rentry.org/sdg-link
| hospitalJail wrote:
| Do you need additional detail that cannot be found here?
|
| https://github.com/AUTOMATIC1111/stable-diffusion-webui
|
| Or are you looking for the cutting edge stuff like control
| net?
|
| If you want to use colab instead, I used this a month or
| two ago.
|
| https://colab.research.google.com/github/TheLastBen/fast-
| sta...
|
| I hope other people can give you further reading.
| erichocean wrote:
| There are dozens on YouTube. My kids did it, and they don't
| even program and had never touched Python in their life.
|
| Even trained their own models using a cloud GPU.
|
| The SD ecosystem is wild.
| lrem wrote:
| Are you sure about this? For the couple things I tried, a
| colleague with Midjourney managed to outperform my attempts
| with SD by leaps and bounds.
| jamilton wrote:
| There's a higher "skill ceiling" with SD. You can install
| different models for different styles or subjects, use
| ControlNet for composition, and use plugins to do things
| you can't easily do with MJ.
| chefandy wrote:
| That seems to depend on your use case. Frankly, I don't have
| much use for either of them but Midjourney was much closer.
|
| I've twice spent a couple of hours unsuccessfully trying to
| generate a simple background image that would be blurred out
| when rendering 3D models. SD out-of-the-box was far worse,
| but Midjourney still was not up to the task. It's incredible
| how well they can generate images of nearly any
| subject/object and make some changes to the style and
| placement, but trying to precisely achieve critical broad-
| stroke things like like perspective, sizing, lighting
| direction/amount/temperature, etc. was far too cumbersome.
| Prompt refining is just like having a program with a bunch of
| nebulous undocumented menu entries that you just have to
| click on to see what they do rather than just giving you the
| tools to make what you need to make. Was that the right entry
| or the wrong entry? Who knows! Maybe just try it again to see
| if it works better!
|
| There's a fundamental disconnect between professional-level
| and consumer-level tools. Consumer tools must be
| approachable, easy to use, quickly yield appealing results,
| affordable, and require little maintenance. Professional
| tools need to be precise, reliable, capable of repeated
| results with the most demanding tasks, and easily serviceable
| into perfect working order.
|
| These are consumer-level tools. If you merely need a cool
| picture of a space ship done in such and such style with such
| and such guns blah blah blah (that for some reason always
| looks 10%-50% Thomas Kinkaid,) these tools are great, but
| they abstract away the controls that really matter in
| professional work. Novices who get overwhelmed by all of
| those factors love it because they don't understand, and
| probably don't care about what they're giving up. For serious
| work, aside from getting inspo images or maybe generating
| deliberately weird bits of whatever, they're hit-or-miss at
| best. Without exception, doing a rough mock-up in a modelling
| program took FAR less time than trying to wrangle exactly
| what I needed from one of those generators.
|
| I'm sure they'll get there someday but right now they're
| miles away from being professional-quality image generation
| tools.
| jstarfish wrote:
| > Without exception, doing a rough mock-up in a modelling
| program took FAR less time than trying to wrangle exactly
| what I needed from one of those generators.
|
| I think a lot of people have unrealistic expectations of
| the tech-- they think they can get _exactly_ what they want
| if they are articulate enough in describing it with words.
|
| Feed your rough mock-up to img2img (or use inpaint sketch)
| and you'll land much closer to where you're trying to go.
|
| It's a power tool. It will do tedious manual work
| (producing art) very quickly. The difference between
| professionals and consumers in how they use it is that the
| professional asks the machine to "finish what I started,"
| whereas the consumer tells the machine to "do all of the
| work for me."
| chefandy wrote:
| I tried img2img. It will do rough finishing work but it
| won't take some lighting vectors and match my lighting.
| It won't shift the viewpoint by 18 degrees. It puts a
| smooth sheen on rough work with broad stroke needs and
| that's valuable in some cases, but it is not a general-
| purpose professional tool.
|
| Canva competently satisfies most non-professional needs
| but it only satisfies a narrow slice of professional
| needs. Trying to use it for most professional work takes
| vastly _more_ time and effort than using a proper
| professional tool. LaTeX fits academic paper publisher 's
| needs and can pump out formatted and laid-out text far
| quicker than someone using InDesign but you'd go crazy
| trying to assemble a modern magazine or high-end book. It
| doesn't need polish or sheen. It needs something
| fundamentally structurally different.
|
| I'm both a professional digital artists and a long time
| back-end software developer. This slice of time has
| really opened my eyes to what it must be like for most
| non-developers to speak to developers: constantly
| oversimplifying your use case and assuming some
| algorithmic approximation will do without really
| understanding the problem.
| jstarfish wrote:
| Fair enough. Your 3D modeling needs might be a bit
| advanced for the current state of things. It works pretty
| well for flat graphic design, stock photo or illustration
| purposes.
|
| I'm holding out for an instruct-based model that will
| take explicit instructions, or at least layered prompts.
| Mutating the original prompt along with the picture (or
| changing the entire thing to only describe certain parts,
| a la inpainting) is frustrating to me.
| chefandy wrote:
| I will say though that low-effort higher-volume
| professionals (e.g. mobile game mills, Fiverrrr designers)
| will likely profit from these tools once they can out-
| compete cheap online assets from stock images/models/etc.
| but they're so not there yet.
| jamilton wrote:
| ControlNet helps a lot with composition and lighting
| (https://sandner.art/create-atmospheric-effects-in-stable-
| dif...). It requires more work than just entering a prompt,
| but probably less work than doing it manually once you get
| used to it. I think there's a number of StableDiffusion
| clients in development that are trying to make this easier.
| tysam_and wrote:
| Midjourney is higher quality by a fair bit, from my personal
| experience and from being near a few of the top early AI
| artists for a good little while.
| Workaccount2 wrote:
| Is midjourneys model actually better?
|
| I was under the impression that midjourney was just running
| a form of SD and it's real secret sauce are the peripheral
| prompts it injects on the backend along with your prompts.
|
| I could be totally off the mark here.
| og_kalu wrote:
| The model is obviously massively better. and they haven't
| been using SD in any form since the test mode of v3. the
| models are trained from scratch.
| jaxboxer wrote:
| [dead]
| sixothree wrote:
| Is midjourney still using discord as its primary user
| interface? That really turned me off.
| chefandy wrote:
| Yes-- a classmate uses it. They do @everyone announces in
| their server every day, and while you can mute actual
| notifications, it still adds one to your badge count. My
| attention is too valuable-- that would get me to cancel
| my subscription.
| sixothree wrote:
| When I used it, it didn't feel like a product. It felt
| like a demo. If I have to rely on some bot in a public
| forum, I'm not sure I like this product.
| Sohcahtoa82 wrote:
| I've operated on the assumption that MidJourney is
| deliberately knee-capping their growth by making it only
| work on Discord to ensure they don't grow faster than
| they can add hardware.
|
| I could be entirely wrong, though. Maybe the person
| making that decision is just an idiot.
|
| I have an IRC bot that has triggers for DALL-E, GPT3, and
| ChatGPT. I really want to make one for MidJourney, and I
| would happily pay MJ for the privilege. But I can't. Not
| without breaking some rules.
| lukebitts wrote:
| MJ edits your prompts, you can achieve the same level of
| quality if you use the same prompts they do (which can be
| found on the internet)
| HelloMcFly wrote:
| > Midjourney is easier, its not better
|
| Does being easier not influence whether it's better? I mean
| this in that for many of the ways AI art would be used, MJ
| already seems to be "good enough" at a lot of it.
|
| Secondarily: doesn't Midjourney's increased user base and
| increased ratings they get from users help it refine its
| model, thus meaning that "ease of use" creates a feedback
| loop with "quality of output" because more users are engaged?
|
| I'm asking real questions, not making a statement I believe
| in and just adding a question mark.
| hospitalJail wrote:
| >Does being easier not influence whether it's better?
|
| As mentioned, what is better, MS Paint or photoshop? If MJ
| ignores your prompt and spits out a half related picture,
| are you going to continue using it?
|
| If anything MJ is a stepping stone to SD. You get a taste
| of AI art, but want to do something specific that MJ cannot
| do. You learn about control-net, alternative models,
| inpainting, etc... and you decide you need to move on from
| MS Paint to Photoshop.
|
| I personally used free AI art(cant remember which), it was
| super cool, but quickly I wanted to use different models
| and generate thousands of pictures at a time. I wanted to
| make gifs, img2img, etc... and the only people doing that
| were on SD.
| fastball wrote:
| I think you actually have that backwards, because your
| conception of "easier" is a bit skewed.
|
| The question is not "which is easier?", but rather "which
| is easier to use to produce high-quality output". In your
| analogy, I'd argue the answer to that question is
| actually Photoshop. Likewise the answer in the MJ/SD case
| is MJ.
| jaxboxer wrote:
| [dead]
| HelloMcFly wrote:
| > As mentioned, what is better, MS Paint or photoshop?
|
| Metaphor is useful, but this feels overly-reductive. The
| gap between the amount of effort it takes to make
| something great or approaching the vision you had is
| massive between MS Paint and Photoshop. Not so for SD and
| MJ.
|
| However, I am appreciating that SD seems to be clearly
| better if you need something more specific / precise. I
| don't think I'm convinced (yet) that because it can get
| more precise inherently makes it a better tool.
| syntheweave wrote:
| It's the old consumer/professional distinction at play:
| "If it's a professional tool, it's a job to know how to
| use it."
|
| There are definitely some professionalized paradigms
| emerging in the use of SD: one video tutorial I saw this
| morning covering basic photobash + img2img and use of
| controlnet had a commenter saying that they preferred
| using the lineart function in controlnet to get more
| control and leverage their drawing skills.
|
| When you see that kind of thing it's a huge signal for
| professionalization, because someone suggesting the
| optimal first step is "learn how to draw" deviates so
| completely from the original context of prompt-based
| image generation: "just type some words and the image
| magically appears".
| Spivak wrote:
| > Does being easier not influence whether it's better
|
| Midjourney let's you type in a thing and get a result that
| will look great, which is no small accomplishment. If you
| want "incidental art" like blog post heros there is no
| competition. But it's really hard to use if you want to get
| exactly what you want.
| ModernMech wrote:
| > But it's really hard to use if you want to get exactly
| what you want.
|
| Alternatively, if you don't know what you want, it's
| _really_ good for inspiration.
| Spivak wrote:
| Very true, I've fleshed out RPG scenes/characters with
| it.
| mdorazio wrote:
| > Midjourney is easier, its not better.
|
| By what measure? Midjourney v5 is massively better with every
| prompt topic I've thrown at it than SD. It's not even close.
| SD, however, is much better if you want an actual
| customizable toolchain or to do things like train it on your
| own face/character.
| ZephyrBlu wrote:
| They also just released v5.1, which seems to be quite a bit
| better than v5.
| fumar wrote:
| Agreed. I pay for MJ and have several SD versions running
| on my PC. I like the ability to fine tune the SD models and
| my Pc with a 4090 is plenty fast, but I can't match MJ's
| output on artistic quality. SD allows for 4k sized outputs
| which is great but I can't use the art like I would like.
| FWIW the SD NSFW community is large but that is not where I
| invest my time with AI art.
| throwaway675309 wrote:
| Generate the following picture in mid journey: "A school of
| dolphins spanking a mermaid with their flukes."
|
| A 1000 V-rolls won't get you there. For something like this
| control net combined with inpainting is indispensable. Not
| to mention the excessively heavy handed censorship in MJ.
|
| Midjourney excels in overall quality, but it completely
| falls down if you have an actual complex vision.
| MetaWhirledPeas wrote:
| > Linux won in servers and supercomputing, but not in end user
| computing.
|
| Pardon the side discussion, but I think this is because of a
| few things.
|
| 1. OS-exclusive "killer apps" (Office, anything that integrates
| with an iPhone)
|
| 2. Games
|
| The killer apps have better alternatives now, and games are
| starting to work better on Linux. Microsoft's business model no
| longer requires everyone to use Windows. (Mac is another
| story.) So I think that, at least for non-Macolytes, Linux end
| user dominance is certainly on the horizon.
| flerchin wrote:
| This year is the year of the Linux Desktop!
|
| I kid. I've been primarily a Linux Desktop user for 20 years.
| importantbrian wrote:
| Linux did kind of win for end user computing. Android is
| based on a modified linux kernel.
| visarga wrote:
| > users will go to whoever has the best model
|
| Depends. You might want privacy, need low price in order to
| process big volumes, need no commercial restrictions, need a
| different tuning, or the task is easy enough and can be done by
| the smaller free model - why not? Why pay money, leak
| information, and get subjected to their rules?
|
| You will only use GPT-4 or 5 for that 10% of tasks that really
| require it. The future spells bad for OpenAI, there is less
| profit in the large and seldom used big models. For 90% of the
| tasks there is a "good enough" level, and we're approaching it,
| we don't need smarter models except rarely.
|
| Another concern for big model developers is data leaks - you
| can exfiltrate the skills of a large model by batch solving
| tasks. This works pretty well, you can make smaller models that
| are just as good as GPT-4 but on a single task. So you can do
| that if you need to call the API too many times - make your own
| free and libre model.
|
| I think the logical response in this situation would be to
| start working on AI-anti-malware, like filters for fake news
| and deceptive sites. It's gonna be a cat and mouse game from
| now on. Better to accept this situation and move on, we can't
| stop AI misuse completely, we'll have to manage it, and learn
| quickly.
| toyg wrote:
| _> Linux won in servers and supercomputing, but not in end user
| computing_
|
| "End user computing" these days means mobile, and mobile is
| dominated by Linux (in Apple's case BSD, but we're splitting
| hair) and Chrome/WebKit - which began as KHTML.
|
| The only area where opensource failed is the desktop, and
| that's also because of Microsoft's skill in defending their
| moats.
| kenjackson wrote:
| The kernel isn't the OS/environment. Distiling iOS to BSD is
| just not useful in the context of this discussion.
| toyg wrote:
| The kernel is absolutely the OS, the desktop environment is
| an interface to it.
| tremon wrote:
| Is e.g. libc part of the OS, or the desktop environment?
| kenjackson wrote:
| The kernel is part of it. But it's not all of it. Again,
| especially in the context of this discussion.
| kashkhan wrote:
| aren't androids linux? thats the biggest by far end user
| platform.
|
| of course google doesnt want to acknowledge it too much.
|
| https://source.android.com/
| mirekrusin wrote:
| If you think you can use GPT-4 then you don't know what you're
| talking about.
|
| API access is on waitlist.
|
| UI has limit of 25 messages in 3 hours.
|
| If you think big, known companies can get ahead of the waitlist
| and use it - short answer is no, they can't because of their
| IP. Nobody is going to sign off leaking out all internal
| knowledge to play with something.
|
| ClosedAI seems to have big problem with capacity.
|
| Those poems about your colleague's upcoming birthday do burn a
| lot of GPU cycles.
| realusername wrote:
| That's also why I think OpenAI is in a tough spot in the long
| run. They just threw as much expensive hardware as they could
| to build this moat. There's basically two things which can
| happen from now on:
|
| - Some scalability breakthrough will appear, if that's the
| case their moat disappears pretty much instantly and the cost
| of LLMs will plunge close to zero being a commodity. That's
| the future I'm betting on from what's happening now.
|
| - No scalability breakthrough will appear and then it means
| that they will have a hard time to expand further as seen as
| the gpt4 limited access.
|
| Either way, they are in a tough spot.
| int_19h wrote:
| Big, known companies are _already_ getting their GPT-4 fix
| via Azure OpenAI Service, where they can get meaningful
| guarantees for their data, and even on-prem if they really
| want it.
| Closi wrote:
| Pretty easy to get API access, I got it within a few days.
| Aware this is a sample of one, but also can't believe they
| fast tracked me.
| rolisz wrote:
| It took me several weeks to get access. I just got it
| today.
| dwringer wrote:
| I've been waiting a little over a month with no update so
| far, but I don't expect any sort of fast track since I'm
| not currently a paying customer.
| Closi wrote:
| Are you using the gpt3 api?
| wahnfrieden wrote:
| GPT4 sucks for many use cases because it's SLOW. It will co-
| exist with ChatGPT variants.
| jquery wrote:
| It's about using the right tool for the right job. GPT-4 is
| an incredibly versatile generalist tool and a fantastic jack
| of all trades. However, this comes with some drawbacks. While
| saying it 'sucks' might be an exaggeration, I generally
| concur with the point you're making.
| wahnfrieden wrote:
| It's no exaggeration that it sucks for certain use cases
| where you would expect and can achieve near-realtime
| response, and that's fine because it's not built for that
| use case. I'm responding to someone saying it's always best
| if you can afford it
| happycube wrote:
| And far more expensive than ChatGPT via API, so it makes
| sense to use ChatGPT3.5, or the locally run equivalents once
| they get as good, as much as possible.
| chaxor wrote:
| It's quite fast if you use it at ~4 AM in the US. There's
| definitely a cycle in time. Putting things in a queue to run
| while you sleep is a good work around.
| yesimahuman wrote:
| Yea 3.5 is more than good enough for a whole slew of tasks
| (especially code), and it's ridiculously fast. I rarely find
| the need to use 4 but certainly if there was a usecase it was
| significantly better at that mattered to me, I would.
| amon22 wrote:
| > users will go to whoever has the best model
|
| Not me, I refuse to use OpenAI products but I do sometimes use
| vicuna 13b when I'm coding C. It's pretty good and I'm happy to
| see the rapid advancement of open source LLMs. It gives me hope
| for the future.
|
| > Linux won in servers and supercomputing, but not in end user
| computing.
|
| I use linux on all of my computers and I love it, many of us do
| (obviously). I'm aware that I'm a small minority even among
| other developers but I think looking at just statistics misses
| the point. Even if the majority will just use the most
| approachable tool (and there is nothing wrong with that), it's
| important to have an alternative. For me this is the point of
| open software, not market domination or whatever.
| [deleted]
| nabakin wrote:
| I think the best situation is when a company will perform an
| expensive but high value task that the open source community
| can't and then give it back to them for further iterations and
| development. If the community isn't able to perform a high
| value task again, a company steps in, does it, and gives it
| back to the community to restart the process.
|
| In this way, everyone's skills are being leveraged to innovate
| at a rapid pace.
| ilyt wrote:
| > The point I'm wanting to make is that users will go to
| whoever has the best model. So, the winning strategy is
| whatever strategy allows your model to compound in quality
| faster and to continue to compound that growth in quality for
| longer.
|
| Best only works till second best is "close enough" and
| cheaper/free
| bilbo0s wrote:
| It's likely they will all be free in time. That's kind of the
| problem underlying the consternation here.
|
| It's the internet all over again. How do you win the race to
| the bottom?
|
| Once there
|
| How do you compete effectively with free? Microsoft and
| Amazon will have billions on billions coming in to float
| their free offerings for what is effectively eternity in
| business terms. Probably Google and Meta will as well. What
| happens to everyone else?
|
| I think you have to be in some niche market where you can
| charge. Because for everyone else, free is unsustainable.
|
| Porn maybe? But there will be way too many competitors there.
| So something more like medical. Or semiconductors. Or
| construction or something.
| ilyt wrote:
| > It's likely they will all be free in time. That's kind of
| the problem underlying the consternation here.
|
| That what I was getting to. Paid only makes sense if you're
| willing to provide stuff that OSS lacks, which is either
| "super specialized things not many people want to OSS" or,
| well good looking UI... (there seem to be massive lack of
| any UI/UX people vs developers in near anything OSS).
|
| AI is neither so it will be commoditized and mostly run in
| few OSS projects, and _probably_ for the best, the only
| thing worse than anyone having access to "near free
| copywriter bot that will write about anything you tell it
| to" is only people with money having access and control
| over it.
| quijoteuniv wrote:
| This is what happened with kubernetes no? Open source was about
| to take over so google release the code not to loose out.
| tontomath wrote:
| I think that pouring a lot of money in open source, by bounties
| or crowdfunding can accelerate open source alternatives to
| closed LLMs. Perhaps a middle way in which software will be
| declared open source six month from now can give enough
| compensation to those institutions contributing big money for
| developing LLM technology. That is a crowdfunding in which the
| great contributors have a limited time to be compensated, but
| capping the total prize just like that of chatgpt 3.5 or 4
| depending of the model.
| mesh wrote:
| >The point I'm wanting to make is that users will go to whoever
| has the best model.
|
| Best isn't defined just by quality though. In some instances
| for some groups, things like whether the model is trained on
| licensed content (with permission) and / or is safe for
| commercial use is more important.
|
| This is one reason why Adobe's Firefly has been received
| relatively well. (I work for Adobe).
| alfor wrote:
| How can a company keep up with the speed of what is happening
| in the open?
|
| Open AI had years of advanced that almost vanished in a few
| months.
|
| And we will see the rise of specialized models, smaller but
| targeted, working in team, delegating (Hugging GPT)
|
| I would use a small and fast model that only speak english, is
| expert at coding an science and not much more. Then you fire up
| an question to another model if yours is out of it's area.
| LordDragonfang wrote:
| Midjourney is more popular because it takes zero technical
| know-how compared to SD (even with A1111 it took me nearly an
| hour to walk my competent-but-layman brother through installing
| it) and doesn't require a high-end gaming PC to run it. (DALL-E
| lost because they let MJ eat their lunch)
| dragonwriter wrote:
| > Midjourney is more popular because it takes zero technical
| know-how compared to SD
|
| Both take zero technical knowledge to use the base models via
| first-party online hosts, but Midjourney is superior there.
|
| SD offers a lot more capacity _beyond_ what is available from
| the first-party online host, though, while with Midjourney,
| that's where it begins and ends, there is nothing more.
|
| > and doesn't require a high-end gaming PC to run it.
|
| Neither does SD (I use a couple-year-old business laptop with
| a 4GB Nvidia card; no sane person would call it a "highend
| gaming PC" to run A1111 locally, and there are options
| besides running it locally.)
| cubefox wrote:
| > DALL-E lost because they let MJ eat their lunch
|
| I wonder why nobody is talking about Bing Image Creator
|
| https://www.bing.com/images/create
|
| which uses some much more advanced version of Dall-E 2 in the
| background (so Dall-E 2.5? 3?), while being completely free
| to use. It can produce some pretty mind blowing results with
| quite simple prompts, although apparently not as impressive
| as Midjourney V5. A few examples:
|
| hyperrealistic
|
| https://www.bing.com/images/create/hyperrealistic/644fa0c48f.
| ..
|
| an allegory for femininity
|
| https://www.bing.com/images/create/an-allegory-for-
| femininit...
|
| portrait of a strange woman, hyperrealistic
|
| https://www.bing.com/images/create/portrait-of-a-strange-
| wom...
|
| allegory of logic, portrait
|
| https://www.bing.com/images/create/allegory-of-
| logic2c-portr...
|
| her strange bedfellow
|
| https://www.bing.com/images/create/her-strange-
| bedfellow/644...
|
| Mrs fox
|
| https://www.bing.com/images/create/mrs-
| fox/6446e85a32134e649...
|
| inside view
|
| https://www.bing.com/images/create/inside-
| view/6446f1dc573f4...
|
| in the midst of it all
|
| https://www.bing.com/images/create/in-the-midst-of-it-
| all/64...
|
| strange gal
|
| https://www.bing.com/images/create/strange-
| gal/6446e2a2ea7a4...
|
| sighting of a strange entity in an abandoned library
|
| https://www.bing.com/images/create/sighting-of-a-strange-
| ent...
|
| sleeping marble woman next to a wall of strange pictures
| inside an abandoned museum, close-up
|
| https://www.bing.com/images/create/sleeping-marble-woman-
| nex...
|
| sculpture of a woman posing next to a wall of strange
| pictures, close-up
|
| https://www.bing.com/images/create/sculpture-of-a-woman-
| posi...
|
| Easter
|
| https://www.bing.com/images/create/easter/643ae4968aff432684.
| ..
|
| Christmas on board a spaceship, DSLR photograph
|
| https://www.bing.com/images/create/christmas-on-board-a-
| spac...
|
| an angel, dancing to heavy metal
|
| https://www.bing.com/images/create/an-angel2c-dancing-to-
| hea...
|
| Saturday afternoon in the streets of a buzzing cyberpunk
| city, photo-realistic, DSLR
|
| https://www.bing.com/images/create/saturday-afternoon-in-
| the...
|
| The Dogfather
|
| https://www.bing.com/images/create/the-
| dogfather/6441d18950b...
|
| the unlikely guest
|
| https://www.bing.com/images/create/the-unlikely-
| guest/644446...
|
| Strange pictures in an abandoned museum
|
| https://www.bing.com/images/create/strange-pictures-in-an-
| ab...
|
| strange woman in an abandoned museum, close-up
|
| https://www.bing.com/images/create/strange-woman-in-an-
| aband...
|
| strange woman in an abandoned museum, strange pictures in the
| background
|
| https://www.bing.com/images/create/strange-woman-in-an-
| aband...
|
| a wall of strange pictures in an abandoned museum in
| Atlantis, close-up
|
| https://www.bing.com/images/create/a-wall-of-strange-
| picture...
|
| female sculpture in an abandoned museum in Atlantis, close-up
|
| https://www.bing.com/images/create/female-sculpture-in-an-
| ab...
|
| the unlikely guest
|
| https://www.bing.com/images/create/the-unlikely-
| guest/644490...
|
| an unlikely guest of the secret society in the lost city in a
| country without name, close-up
|
| https://www.bing.com/images/create/an-unlikely-guest-of-
| the-...
|
| I think the quality of most of these pictures is far beyond
| what is achievable with Dall-E 2. One issue that still exists
| (though to a lesser extent) is the fact that faces have to
| cover a fairly large area of the image. Smaller faces look
| strange, e.g. here:
|
| photograph of the unlikely guests
|
| https://www.bing.com/images/create/photograph-of-the-
| unlikel...
|
| It is as if the model creates a good draft in low resolution,
| and another model scales it up, but the latter model doesn't
| know what a face is? (I have no idea how diffusion models
| actually work.)
| reissbaker wrote:
| GPT-4 is so much better for complex tasks that I wouldn't use
| anything else. Trying to get 3.5 to do anything complicated is
| like pulling teeth, and using something worse than 3.5... Oof.
|
| TBH this feels like cope from Google; Bard is embarrassingly
| bad and they expected to be able to compete with OpenAI. In my
| experience, despite their graph in the article that puts them
| ahead of Vicuna-13B, they're actually behind... And you can't
| even use Bard as a developer, there's no API!
|
| But GPT-4 is so, so much better. It's not clear to me that
| individual people doing LoRa at home is going to meaningfully
| close the gap in terms of generalized capability -- at least,
| not faster than OpenAI itself improves its models. Similarly,
| StableDiffusion's image quality progress has in my experience
| stalled out, whereas Midjourney continues to dramatically
| improve every couple months, and easily beats SD. Open source
| isn't a magic bullet for quality.
|
| Edit: re: the complaints about Midjourney's UI being Discord --
| sure, that definitely constrains what you can do with it, but
| OpenAI's interface isn't Discord, it has an API. And you can
| fine-tune the GPT-3 models programmatically too, and although
| they haven't opened that up to GPT-4 yet, IME you can't fine-
| tune your way to GPT-4 quality anyway with anything.
|
| "There's no moat" and "OpenAI is irrelevant" feel like the
| cries of the company that's losing to OpenAI and wants to save
| face on the way out. Getting repeated generational improvements
| without the dataset size and compute scale of a dedicated,
| well-capitalized company is going to be very tough. As a
| somewhat similar data+compute problem, I can't think of an
| open-source project that effectively dethroned Google Search,
| for example... At least, not by _being better at search_ (you
| can argue that maybe LLMs are dethroning Google, but on the
| other hand, it 's not the open source models that are the best
| at that, it's closed-source GPT-4).
| karmasimida wrote:
| GPT-4 is a must if tool using is your goal.
|
| GPT-3.5, I think it is mostly suitable for:
|
| 1. Quick documentation lookup for non-essential facts
|
| 2. Lightweight documents writing and rewriting
|
| 3. Translation
|
| Other use cases should go straightly to GPT-4
| biesnecker wrote:
| I use GPT-3.5 for a lot of terminology lookup, and it's
| generally pretty great.
|
| "In the context of [field I'm ramping up in], what does X
| mean, and how is it different than Y" -- it's not as good
| as GPT4 but it emits so much quicker and it normally gets
| me where I needed to go.
| [deleted]
| joshbert wrote:
| I don't feel sorry for Google, nor the big amounts of PR
| nonsense they're putting out there in order to try to spin
| their being too slow to move LLM tech to the side of the
| consumer. Get better or get out.
| ineedasername wrote:
| Yes, I'd readily pay for GPT-4 access, though not the limited
| 25 requests per 3 hours version. I ponied up $20 for a month
| of usage to check it out, and it performs head & shoulders
| above 3.5 in its ability to comprehensively address more
| complex prompts and provide output that is more nuanced than
| ChatGPT.
|
| I'll also point out that paid api access to 3.5 (davinci-03)
| is frequently better than ChatGPT's use of 3.5. You get many
| fewer restrictions, and none the "awe shucks, I'm just a
| little 'ol LLM and so I couldn't possibly answer that".
|
| If you're frustrated by having to go to great lengths to
| prompt engineer and ask ChatGPT to "pretend" then it's worth
| it to pay for API access. I'm just frustrated that I can't
| use the GPT-4 API the same way yet (waitlist)
| obiefernandez wrote:
| If you're technical just get yourself OpenAI API access
| which is super cheap and hook it up to your own self-hosted
| ChatGPT clone like https://github.com/magma-labs/magma-chat
|
| The wait for GPT-4 is not as long as it used to be, and
| when you're using the API directly there's no censorship.
| DesiLurker wrote:
| .
| ineedasername wrote:
| Yep, I use the paid API, and it's a lot more flexible
| than ChatGPT. I'd didn't know about the self-hosted
| interface though: that will be my project for tomorrow
| morning, thanks!
|
| I've been on the GPT-4 waitlist for about 6 weeks, but
| I'm not sure what the typical wait is.
| reissbaker wrote:
| I hear ya! I'm out here dying on the GPT-4 API waitlist
| too. I use gpt-3.5-turbo's API extensively, and
| occasionally copy my prompts into GPT-4's web UI and watch
| as it just flawlessly does all the things 3.5 struggles
| with. Very frustrating since I don't have GPT-4 API access,
| but also very, very impressive. It's not even remotely
| close.
|
| I pay the $20 for ChatGPT Plus (aka, GPT-4 web interface
| access); personally I find it useful enough to be worth
| paying for, even in its rate-limited state. It already
| replaces Google for anything complex for me. I wish I could
| pay for the API too, and use it in my projects.
| moffkalast wrote:
| GPT 4 really shows how absolutely terrible regular web
| search is at finding anything these days. Another
| complete embarrassment for Google.
|
| Often times it can just recite things from memory that
| Google can't even properly link to, and they've got a
| proper index to work from for fucks sake.
| cube2222 wrote:
| Some snippets for folks who come just for the comments:
|
| > While our models still hold a slight edge in terms of quality,
| the gap is closing astonishingly quickly. Open-source models are
| faster, more customizable, more private, and pound-for-pound more
| capable. They are doing things with $100 and 13B params that we
| struggle with at $10M and 540B. And they are doing so in weeks,
| not months.
|
| > A tremendous outpouring of innovation followed, with just days
| between major developments (see The Timeline for the full
| breakdown). Here we are, barely a month later, and there are
| variants with instruction tuning, quantization, quality
| improvements, human evals, multimodality, RLHF, etc. etc. many of
| which build on each other.
|
| > This recent progress has direct, immediate implications for our
| business strategy. Who would pay for a Google product with usage
| restrictions if there is a free, high quality alternative without
| them?
|
| > Paradoxically, the one clear winner in all of this is Meta.
| Because the leaked model was theirs, they have effectively
| garnered an entire planet's worth of free labor. Since most open
| source innovation is happening on top of their architecture,
| there is nothing stopping them from directly incorporating it
| into their products.
|
| > And in the end, OpenAI doesn't matter. They are making the same
| mistakes we are in their posture relative to open source, and
| their ability to maintain an edge is necessarily in question.
| Open source alternatives can and will eventually eclipse them
| unless they change their stance. In this respect, at least, we
| can make the first move.
| lhl wrote:
| > Paradoxically, the one clear winner in all of this is Meta.
| Because the leaked model was theirs, they have effectively
| garnered an entire planet's worth of free labor. Since most
| open source innovation is happening on top of their
| architecture, there is nothing stopping them from directly
| incorporating it into their products.
|
| One interesting related point to this is Zuck's comments on
| Meta's AI strategy during their earnings call:
| https://www.reddit.com/r/MachineLearning/comments/1373nhq/di...
|
| Summary:
|
| """ Some noteworthy quotes that signal the thought process at
| Meta FAIR and more broadly We're just playing
| a different game on the infrastructure than companies like
| Google or Microsoft or Amazon We would aspire to
| and hope to make even more open than that. So, we'll need to
| figure out a way to do that. ...lead us to do more
| work in terms of open sourcing, some of the lower level models
| and tools Open sourcing low level tools make the
| way we run all this infrastructure more efficient over time.
| On PyTorch: It's generally been very valuable for us to provide
| that because now all of the best developers across the industry
| are using tools that we're also using internally.
| I would expect us to be pushing and helping to build out an
| open ecosystem.
|
| """
| borski wrote:
| > Since most open source innovation is happening on top of
| their architecture, there is nothing stopping them from
| directly incorporating it into their products.
|
| There's also nothing stopping anybody else from incorporating
| it into their products.
| ketzo wrote:
| There definitely is. LLaMA is not licensed for commercial
| use. It's impractical to prosecute 1,000 people tinkering on
| their laptops, but if Meta discovered that Amazon was using
| LLaMA for commercial purposes, it would be nuclear war.
| ada1981 wrote:
| Let's play... Global Thermo Nuclear War.
| spullara wrote:
| We don't know what legal protection a bunch of weights
| have. They may not be copyrightable.
| ketzo wrote:
| They _may_ not be. But do you wanna be the person /people
| to argue that against one of the richest companies in the
| world? I sure don't, and I _definitely_ wouldn 't stake
| my company/product on it.
| robinsord wrote:
| [dead]
| borski wrote:
| Touche.
| intalentive wrote:
| Open-LLaMA is already out. It's not the end-all-be-all
| either. Better, smaller, open source models will continue
| to be released.
| samstave wrote:
| >> _"T ey have effectively garnered an entire planet's worth of
| free labor."_
|
| -
|
| THIS IS WHY WE NEED DATA FUCKING OWNERSHIP.
|
| Users should be able to have a recourse to the use of their
| data in both of terms utility (for the parent company) and in
| terms of financial value to the parent company to the financial
| extraction of that value.
|
| Let me use cannabis as an example...
|
| When multiple cannabis cultivators (growers) combine their
| product for extraction into a singular product we have to
| figure out how to divide and pay the taxes..
|
| Same thing (I'll edit this later because I'm at the dentist
| whatshisface wrote:
| Meta's leaked model isn't open-source. I can found a business
| using Linux, that's open-source. The LLM piracy community are
| unpaid FB employees; it is not legal for anyone but Meta to use
| the results of their labor.
|
| I know this might be hard news but it needs to be said... if
| you want to put your time into working on open source LLMs, you
| need to get behind something you have a real (and yes, open
| source) license for.
| dragonwriter wrote:
| > Meta's leaked model isn't open-source.
|
| Meta's leaked model has been a factor in spurring open source
| development, whether or not it is open source; the article
| also discusses the practical market of effect of leaked-but-
| not-open things like Meta's model combined with the
| impracticality of prosecuting the vast hordes of individuals
| using it, and particularly notes that the open-except-for-
| the-base-model work on top of it is a major benefit for Meta
| (who can use the work directly) that locks out everyone else
| in the commercial market (who cannot), and leaning into open
| source base models is a counter to that.
| spullara wrote:
| I don't think we know where weights stand legally yet. They
| may end up being like databases, uncopyrightable.
| Blahah wrote:
| You are making an assumption that seems very strange to me -
| that the license matters for important use cases. It doesn't.
| Access to the technology is the only important factor,
| because nothing interesting about AI involves commercialising
| anything. It's a tool and now people have it. Whether they
| can make a company out of it is so far down the list of how
| it could make a difference that it doesn't even register.
| AnthonyMouse wrote:
| Most of the code isn't specific to a model. It happens that
| LLaMA is approximately the best LLM currently available to
| the public to run on their own hardware, so that's what
| people are doing. But as soon as anyone publishes a better
| one, people will use that, using largely the same code, and
| there is no reason it couldn't be open source.
|
| I'm also curious what the copyright status of these models
| even is, given the "algorithmic output isn't copyrightable"
| thing and that the models themselves are essentially the
| algorithmic output of a machine learning algorithm on third
| party data. What right does Meta have to impose restrictions
| on the use of that data against people who downloaded it from
| The Pirate Bay? Wouldn't it be the same model if someone just
| ran the same algorithm on the same public data?
|
| (Not that that isn't an impediment to people who don't want
| to risk the legal expenses of setting a precedent, which
| models explicitly in the public domain would resolve.)
| leereeves wrote:
| > I'm also curious what the copyright status of these
| models even is
|
| That's my question as well. The models are clearly
| derivative works based on other people's copyrighted texts.
|
| Only a twisted court system would allow
| Google/OpenAI/Facebook to build models on other people's
| work and then forbid other people to build new models based
| on GOF's models.
| AnthonyMouse wrote:
| > That's my question as well. The models are clearly
| derivative works based on other people's copyrighted
| texts.
|
| That's not that clear either. (Sometimes it's more clear.
| If you ask the model to write fan fiction, and it does,
| and you want to claim that isn't a derivative work, good
| luck with that.)
|
| But the model itself is essentially a collection of data.
| "In _Harry Potter and the Philosopher 's Stone_, Harry
| Potter is a wizard" is a fact about a work of fiction,
| not a work of fiction in itself. Facts generally aren't
| copyrightable. If you collect enough facts about
| something you could in principle reconstruct it, but
| that's not really something we've seen before and it's
| not obvious how to deal with it.
|
| That's going to create a practical problem if the models
| get good enough to e.g. emit the full text of the book on
| request, but the alternative is that it's illegal to make
| a model that knows everything there is to know about
| popular culture. Interesting times.
| math_dandy wrote:
| LLaMA leaked intentionally?
| happycube wrote:
| De facto, yes. There was _no way_ the weights wouldn 't be
| posted everywhere once they went out to that many people.
| int_19h wrote:
| There's a pull request in the official LLaMA repo that adds
| Magnet links for all the models to the README. Until these
| were uploaded to HuggingFace, this PR was the primary
| source for most people downloading the model.
|
| https://github.com/facebookresearch/llama/pull/73/files
|
| Two months later, Facebook hasn't merged the change, but
| they also haven't deleted it or tried to censor it in any
| way. I find that hard to explain unless the leak really was
| intentional; with pretty much any large company, this kind
| of thing would normally get killed on sight.
| lerchmo wrote:
| this is a temporary state. Open source alternatives are
| already available and more are being trained.
| tysam_and wrote:
| I'm still not on board with calling it leaked...the weights
| were open for anyone to get and use as long as they agreed to
| use them academically.
|
| Basically, completely open source with a non-commercial
| license. I'm not sure why so many people keep saying it
| 'leaked'. It's just using open source weights not directly
| from the provider in a way that violates the software
| license.
| tdullien wrote:
| I am still absolutely baffled that people think weights are
| copyrightable and hence licensable.
|
| There is no reason to believe they are, which means any
| restriction placed on the weights themselves is bullshit.
| downWidOutaFite wrote:
| It takes millions of dollars to generate the weights,
| shouldn't it have some legal protection?
| dragonwriter wrote:
| > It takes millions of dollars to generate the weights,
| shouldn't it have some legal protection?
|
| It does, if you choose to keep them internally as a trade
| secret.
|
| It does, if you share it only with people you contract
| with not to disclose it.
|
| But, for _copyright_ specifically, rather than "some
| legal protection" more generally, the "it takes millions
| of dollars" argument is a financial recasting of the
| "sweat of the brow" concept which has been definitively
| rejected by the courts.
| SuoDuanDao wrote:
| why wouldn't they be copyrightable? is it a discovered
| versus written thing?
| dragonwriter wrote:
| > why wouldn't they be copyrightable?
|
| Why would they be? I mean, what is the specific argument
| that they fall within the scope of the definition of what
| is copyrightable under US law?
| tdullien wrote:
| The fact that software falls under copyright was a
| conscious decision in 1978 because they couldn't find a
| better place to put it under; so "writing software" was
| equated to writing books or poetry.
|
| The point here is that copyright requires a human to have
| created something using their own labor/creativity.
|
| The result of an algorithm run by a machine isn't a
| creative work under these definitions.
| joelfried wrote:
| I think we can go further.
|
| From the US Copyright Office[1]: "A mere listing of
| ingredients is not protected under copyright law", and
| from their linked circular on that page [2]: "forms
| typically contain empty fields or lined spaces as well as
| words or short phrases that identify the content that
| should be recorded in each field or space".
|
| A list of identifiers and their weights seems pretty
| explicitly not protected under one or the other of these.
|
| [1] https://www.copyrightlaws.com/copyright-protection-
| recipes/ [2] https://www.copyright.gov/circs/circ33.pdf
| mirekrusin wrote:
| Meh, you can experiment on it for personal use as much as you
| want and that's all what's needed in this short period of
| time before powerful, open base models start appearing like
| mushrooms at which point the whole thing is going to be moot.
| avereveard wrote:
| Openai moat is the upcoming first party integration with ms
| office.
| kccqzy wrote:
| By that logic Google's moat is the integration with Gmail and
| Google Docs.
|
| And frankly it's not. People will decide to copy some text
| from Office or Docs to some other non-integrated tool, get
| LLMs to work, and then paste back to Office or Docs.
| goatlover wrote:
| That sounds rudimentary compared an integrated LLM could do
| for all your documents, emails, appointments, etc.
| sudosysgen wrote:
| Also, one can make Office plugins.
| HDThoreaun wrote:
| Some people will. Many others will just use the
| autocomplete functionality that is coming to every office
| suite product.
| Alifatisk wrote:
| > the one clear winner in all of this is Meta. Because the
| leaked model was theirs, they have effectively garnered an
| entire planet's worth of free labor. Since most open source
| innovation is happening on top of their architecture, there is
| nothing stopping them from directly incorporating it into their
| products.
|
| This
| wendyshu wrote:
| This... what?
| yellowstuff wrote:
| It's internet speak for "I agree with this."
| [deleted]
| diordiderot wrote:
| I think this type of comment is generally frowned upon on HN.
|
| Upvote serves the same purpose.
| Alifatisk wrote:
| My bad
| sterlind wrote:
| I wonder if OpenAI knew they didn't have a moat, and that's why
| they've been moving so fast and opening ChatGPT publicly -
| making the most of their lead in the short time they have left.
|
| I find it incredibly cathartic to see these massive tech
| companies and their gatekeepers get their lunch eaten by OSS.
| gitfan86 wrote:
| That is the nature of the singularity. Progress moves faster
| than any one person or any one company can keep up with.
| ddalex wrote:
| What happens when the society as a whole cannot keep up
| with progress? That's a scary thought.
| adamsbriscoe wrote:
| Taking the "no moat" argument at face value, I think it's
| important to remember that some of the largest players in AI
| are lobbying for regulation too.
| marcod wrote:
| If past performance is any indication, it's pretty safe to
| lobby for regulations in the US...
| HDThoreaun wrote:
| Yep, regulating the ladder behind you is a classic
| monopolist move
| tyre wrote:
| OpenAI doesn't need a moat and it's fine that they don't have
| one. From their charter:
|
| > We will attempt to directly build safe and beneficial AGI,
| but will also consider our mission fulfilled if our work aids
| others to achieve this outcome.
|
| This was from 2018 and they've taken large strides away from
| their originally stated mission. Overall, though, they should
| be happy to have made progress in what they set out to do.
| int_19h wrote:
| Note that this implies that if anyone tries to build AGI
| that is not "safe and beneficial" by OpenAI standards, it's
| fair game to suppress.
| enjo wrote:
| That's all well and good. I suspect their investors have a
| pretty different idea about their positioning tho.
| arcticbull wrote:
| Yes...
|
| > "we will attempt to directly build safe and beneficial
| AGI, but will also consider our mission fulfilled if our
| work aids others to achieve this outcome"
|
| ... has big "don't be evil" energy.
|
| I believe the next step was "we can do little a evil, as
| a treat."
| tyre wrote:
| Oh yeah, sure. I'm not sure I care much about that
| though. MSFT had the opportunity to think through all of
| this before they invested, OpenAI itself has incredible
| sums of money, and employees get to work on things they
| care about.
|
| If MSFT doesn't make anything on this investment--which
| it still might, given that a big chunk of its investment
| will likely go into Azure--then...okay.
| techwiz137 wrote:
| Sorry for the dumb question. But in the context of the AI
| space, what is moat?
| bluGill wrote:
| That is the million/billion+ dollar question. If find it
| and get there fast enough you can own the moat, and thus
| become rich.
|
| Note that I am not in any way implying that a moat even
| exists. There may be some reason AI becomes a winner takes
| all scheme and nobody else should bother playing, but it is
| also possible that there is no way to make your product
| better than anyone else. Only time will tell.
| leereeves wrote:
| Moat is a business term coined by Warren Buffett. It's a
| competitive advantage that isn't easily overcome and allows
| a company to earn high margins.
|
| I don't think there are any examples in the context of AI.
| As the post says, no one in the AI space has a moat right
| now.
| sterlind wrote:
| Historically, datasets have been a moat. Google had a
| massive head start from having a massive search index and
| user data. Then access to compute became the moat - fully
| training a trillion-parameter language model has only
| been in reach for megacorps. But now, there's a ton of
| publicly-available datasets, and LLaMA showed that you
| don't need massive numbers of parameters.
| rmason wrote:
| OpenAI has 80% of the developer community. Why isn't that
| considered a moat?
| passwordoops wrote:
| _Cynical rant begin_
|
| I'm sorry but I think this has more to do with looming anti trust
| legislation and the threat of being broken up than a sincere
| analysis of moats. Especially with the FTC's announcement on Meta
| yesterday, I'm seeing lots of folks say we need to come down hard
| on AI too. This letter's timing is a bit too convenient.
|
| _Cynical rant over_
| qwertox wrote:
| " _Just so you know, we won 't be the ones to blame for all the
| bad which is about to come_"
| xyzzy4747 wrote:
| I disagree with this. It's too expensive to train high quality
| models. For example I don't see how anyone would make an open-
| source GPT4 unless OpenAI leaks their model to the public.
| coolspot wrote:
| No one has created even something closed-source that is equal
| to GPT4.
| Hippocrates wrote:
| ELI5 How is it too expensive? I know ChatGPT was expensive to
| train but Vicuna-13b is said to have cost $300 to train
| [https://lmsys.org/blog/2023-03-30-vicuna/]
| harisec wrote:
| Vicuna-13b is based on LLAMA that was millions to train. $300
| is just to finetuning.
| DonHopkins wrote:
| "I Have No Moat, and I Must Scream"
|
| https://en.wikipedia.org/wiki/I_Have_No_Mouth,_and_I_Must_Sc...
| _trackno5 wrote:
| I get the feeling that at this point, the best thing Google could
| do is to go all in an open source their models and weights.
| They'd canibalize their own business, but they'd easily wipe out
| most of the competition.
| eternalban wrote:
| _" Paradoxically, the one clear winner in all of this is Meta.
| Because the leaked model was theirs, they have effectively
| garnered an entire planet's worth of free labor. Since most open
| source innovation is happening on top of their architecture,
| there is nothing stopping them from directly incorporating it
| into their products."_
|
| An interesting thought. Are the legal issues for derived works
| from the leaked model clarified or is the legal matter to be
| resolved at a later date when Meta starts suing small developers?
| dragonwriter wrote:
| Meta is clear to use anything open licensed and derived from or
| applied on top of the leaked material irrespective of the
| resolution, while for everyone else the issue is clouded. That
| makes Meta the winner.
| eternalban wrote:
| Yep, same thoughts here. I'm experiencing tin foil urges ..
| punnerud wrote:
| Is Tensorflow used in any of the OpenSource projects?
|
| I find PyTorch in everyone I check.
| balls187 wrote:
| My feeling on this is "f** yeah, and f** you [google et al]"
|
| How much computing innovation was pioneered by community
| enthusiasts and hobbyists that have been leveraged by these huge
| companies.
|
| I know meta, googlr, msft et al give back in way of opensource,
| but it really pales in comparison to the value those companies
| have extracted.
|
| I'm a huge believer in generative AI democratizing tech.
|
| Certainly I'm glad to pay for off-the-shelf custom tuned models,
| and for software that smartly integrates generative AI to improve
| usage, but not a fan of gate keeping this technology by a handful
| of untrustworthy corporations.
| ronaldoCR wrote:
| Doesn't the sheer cost of training create a moat on its own?
| echelon wrote:
| Yes, but so far we've seen universities, venture-backed open
| source outfits, and massive collections of hobbyists train all
| sorts of large models.
| hiddencost wrote:
| It's cheap to distill models, and trivial to scrape existing
| models. Anything anyone does rapidly gets replicated for
| 1/500th the price.
| ktbwrestler wrote:
| Can someone dumb this down for me because I don't understand why
| this is a surprise... people are getting excited and
| collaborating to improve and innovate the same models that these
| larger companies are milking to death
| cube2222 wrote:
| Basically, if I understand correctly, the "status quo" was that
| the big models by OpenAI and Google that are much better (raw)
| than anything that was open source recently, would remain the
| greatest, and the moat would be the technical complexity of
| training and running those big models.
|
| However, the open sourcing led to tons of people exploring tons
| of avenues in an extremely quick fashion, leading to the
| development of models that are able to close in on that
| performance in a much smaller envelope, destroying the only
| moat and making it possible for people with limited resources
| to experiment and innovate.
| galaxyLogic wrote:
| > big models by OpenAI and Google that are much better (raw)
| than anything that was open source recently,
|
| When you say "models" do you mean TRAINED models?
|
| Wouldn't the best training and supervised/feedback learning
| still be in the hands of the big players?
|
| An open source "model" of all content in the open internet is
| great, but it has the garbage-in/garbage-out problem.
| curiousgal wrote:
| I'm convinced that anyone sounding the alarm bells about AI has
| no idea whatsoever how these models are built.
| summerlight wrote:
| Note that this is a personal manifesto, which doesn't really
| represent Google's official stance. Which is unfortunate because
| I'm largely aligned with this position.
| hot_gril wrote:
| From one researcher, not a VP, director, etc.
| noobermin wrote:
| Is there any evidence this is real? It reads like an article
| written not for google but for fans of open source in their
| competitors supposed voice.
| Giorgi wrote:
| There is no way this is from Google. It screams fake.
| lysecret wrote:
| Fantastic article if you are quick to just go to the comments
| like I usually do, don't. Read it.
|
| One of my favorites: LoRA works by representing model updates as
| low-rank factorizations, which reduces the size of the update
| matrices by a factor of up to several thousand. This allows model
| fine-tuning at a fraction of the cost and time. Being able to
| personalize a language model in a few hours on consumer hardware
| is a big deal, particularly for aspirations that involve
| incorporating new and diverse knowledge in near real-time. The
| fact that this technology exists is underexploited inside Google,
| even though it directly impacts some of our most ambitious
| projects.
|
| Anyone has worked with LoRa ? Sounds super interesting.
| seydor wrote:
| If i understand correctly it is also shockingly simple,
| basically just the first figure in the paper:
| https://miro.medium.com/v2/resize:fit:730/1*D_i25E9dTd_5HMa4...
|
| train 2 matrices, add their product to the pretrained weights,
| and voila! Someone correct me if i m wrong
| eulers_secret wrote:
| If you use the web interface (oobabooga), then training a LoRa
| is as easy as clicking the "training" tab, keeping all the
| defaults, and giving it a flat text file of your data. The
| defaults are sane enough to not begin undermining any
| instruction tuning too much. Takes 3-5 hours on a 3080 for 7B,
| 4bit model (and ~1KWh).
|
| So far I've trained 3: 2 on the entire text of ASOIAF
| (converted from e-books) and 1 on the Harry Potter series. I
| can ask questions like "tell me a story about a long winter in
| Westeros" and get something in the "voice" of GRRM and with
| real references to the text. It can write HP fanfics all day
| long. My favorite so far was the assistant self-inserting into
| a story with Jon Snow, complete with "The Assistant has much
| data for you. Please wait while it fetches it." and actually
| having a conversation with Jon.
|
| Asking specific questions is way more of a miss (e.x. "Who are
| Jon Snow's real parents?" returns total BS), but that may be
| because my 3080 is too weak to train anything other than 7B
| models in 4bit (which is only supported with hacked patches). I
| used Koala as my base model.
|
| I'm getting close to dropping $1600 on a 4090, but I should
| find employment first... but then I'll have less time to mess
| with it.
| seydor wrote:
| how much memory does the 7B training need?
| eulers_secret wrote:
| ~7.5GB - it'll be the same as running inference with a full
| context. That's for 4-bit quantization, the 8-bit
| quantization uses more RAM than my 3080 has...
| seydor wrote:
| I wonder how much it would take to train the 4b 13B
| MacsHeadroom wrote:
| About 15GB training it in the webui.
|
| If you use
| https://github.com/johnsmith0031/alpaca_lora_4bit then
| 30B only needs 24GB, and works on a single 3090 or $200
| P40.
| sbrother wrote:
| Will it distribute training across multiple GFX cards? I have
| a 4x 2080Ti box I would love to be able to use for this sort
| of thing.
| eulers_secret wrote:
| Not for training with the webui:
| https://github.com/oobabooga/text-generation-
| webui/issues/11...
|
| It does seem to work using alpca-lora directly, though.
| Tiktaalik wrote:
| That's really interesting.
|
| I guess it would do really well with world building lore type
| stuff, being able to go into great depth about the Brackens
| vs the Blackwoods but would struggle at the sort of subtext
| that even human readers may have missed (eg. who poisoned
| Tywin? and as you said, who are Jon Snow's parents?)
| Kuinox wrote:
| Used 3090 are getting really cheaps on the second hand
| market. Then if you only need VRAM, the Tesla M40 are even
| cheaper at 100EUR per unit, which has 24GB of VRAM.
| MacsHeadroom wrote:
| The M40 does not support 4bit, so it's basically useless
| for LLMs.
|
| The P40 24GB is only $200, supports 4bit, and is about 80%
| the speed of a 3090 (surprisingly) for LLM purposes.
| Levitz wrote:
| I wholeheartedly second this. This article seems to me to be
| one important, small piece of text to read. It might very well
| end up somewhere in a history book someday.
| adroitboss wrote:
| You can find the guy who created it on reddit u/edwardjhu. I
| remember because he showed up in the Stable Diffusion
| Subreddit.
| https://www.reddit.com/r/StableDiffusion/comments/1223y27/im...
| m3kw9 wrote:
| It's always easier to use a prebuilt server which Google or
| OpenAI offers. Otherwise it's built locally into the OS, maybe
| Apple. Most people is not gonna setup their own servers for these
| models because they have multiple devices and the costs is still
| high vs OpenAI.
|
| Having ease of access is a big moat
| ChaitanyaSai wrote:
| This is easily among the rare highest quality articles/comments
| I've read in the past weeks, perhaps months (on LLMs/AI since
| that's what I am particularly interested in). And this was for
| internal consumption before it was made public. Reinforces my
| recent impression that so much that's being made for public
| consumption now is shallow and it is hard to find the good stuff.
| And sadly, increasing so even on HN. As I write this, I
| acknowledge I discovered this on HN :) Wish we had ways to
| incentivize the public sharing of such high-quality content that
| don't die at the altar of micro rewards.
| crazygringo wrote:
| Well yes, generally in the business world all the "good stuff",
| the really smart analysis, is extremely confidential. Really
| smart people are putting these things together, but these types
| of analyses are a competitive advantage, so they're absolutely
| never going to share it publicly.
|
| This was leaked, not intentionally made public.
|
| And it all makes sense -- the people producing these types of
| business analyses are world-class experts in their fields (the
| business strategy not just the tech), and are paid handsomely
| for that.
|
| The "regular stuff" people consume is written by journalists
| who are usually a bit more "jack of all trades master of none".
| A journalist might cover the entire consumer tech industry, not
| LLM's specifically. They can't produce this kind of analysis,
| nor should we expect them to.
|
| Industry experts are extremely valuable for a reason, and they
| don't bother writing analyses for public media since it doesn't
| pay as well.
| gerad wrote:
| Beware that there's also a ton of bias when something is
| analyzed internally. As Upton Sinclair once said "It is
| difficult to get a man to understand something, when his
| salary depends on his not understanding it."
|
| In the case of this analysis - it sounds great but it's
| wrong. OpenAI has a huge moat. It has captured the mind share
| of the world. The software it has shipped is dramatically
| better than anything anyone else has shipped (the difference
| between useless and useful). We'll see if folks catch up, but
| the race is currently OpenAI's to lose.
| crazygringo wrote:
| Mind share is not a moat. And market share or being first
| is not a moat.
|
| Moats are very specific things such as network effects,
| customers with sunk costs, etc. The very point of the term
| "moat" is to distinguish it from things like market share
| or mind share.
|
| The article is correct, OpenAI has no moat currently.
| gerad wrote:
| What's Google's moat? Mind share and being dramatically
| better than the competition is indeed a moat. Trust me
| mind share is incredibly hard to gain in this day and
| age.
| vigilantpuma wrote:
| Google, according to the article, has no moat either.
| wahern wrote:
| Sort of like sports recruiters.
| opportune wrote:
| Agreed, I have some expertise in a couple software topics,
| and there is nowhere in public media that would pay me to
| write about it.
|
| The only exception would be if my name were super
| recognizable/I had some legitimacy I could "sell" to publish
| something that did have commercial value, like some shitty
| CIO-targeted "article" about why XYZ is the future, in which
| case it's not really going to be interesting content or
| actually sharing ideas.
| whimsicalism wrote:
| If you feel like your criteria for quality is beyond what you
| can typically find in the popular public consumption, just
| start reading papers directly?
| crazygringo wrote:
| The value in this article is the business strategy
| perspective, not the details of LLM's.
|
| You generally won't find papers detailing the present-moment
| business strategies of specific for-profit corporations.
| whimsicalism wrote:
| Sure but this article is also not the present-moment
| business strategy, it is written by a single individual
| with a perspective.
| censor_me wrote:
| [dead]
| 0xbadcafebee wrote:
| Most HN submissions are clickbait advertisements by startups
| for B2B/B2C services, clickbait amateur blog editorials looking
| for subscribers, tutorials for newbies, conspiracy theories,
| spam, and literally every article posted to a major media
| outlet. Most comments are by amateurs that sound really
| confident.
|
| Don't believe me? Go look at
| https://news.ycombinator.com/newest . Maybe once a month you
| find something on here that is actually from an expert who
| knows what they're talking about and hasn't written a book on
| it yet, or a pet project by an incredibly talented person who
| has no idea it was submitted.
|
| Source: I've been here for 14 years. That makes me a little
| depressed...
| burnished wrote:
| Most of it is being written to make money off of you instead of
| communicate with you and it shows.
| swores wrote:
| Hi Sai, do you have an email address (or other preferred
| private message) I could contact you on? Feel free to send it
| to the relay email in my profile if you want to avoid putting
| it publicly (or reply here how to contact you).
|
| I'll ask my first question here below, so that if you have an
| answer it can benefit other HNers, and I'll save the other line
| of thought for email.
|
| Do you happen to have a list of other highest quality articles
| on AI/LLMs/etc that you've come across, and could share here?
|
| It's not my field but something I want to learn more about, and
| I've found it hard to, without knowing much about the specific
| subjects within AI that would be good to learn about makes it
| hard picking what to read or not.
| heliophobicdude wrote:
| I thought this was a good one this week but didn't get popular.
|
| https://huyenchip.com/2023/05/02/rlhf.html
| opportune wrote:
| There is some really high quality internal discussions at tech
| companies, unfortunately they are suffering from leaks due to
| their size and media have realized it's really easy to just
| take their internal content and publish it.
|
| It really sucks because there's definitely a chilling effect
| knowing any personal opinion expressed in text at a big tech
| company could end up in a headline like "GOOGLE SAYS <hot
| take>" because of a leak.
|
| If there is some kind of really bad behavior being exposed, I
| think the role of the media is to help do that. But I don't
| think their role should be to expose any leaked internal
| document they can get their hands on.
| UncleMeat wrote:
| This is exactly that. This doc is apparently a leaked
| internal doc.
| opportune wrote:
| I know that, my point is that it's not indicating anything
| nefarious enough to be worth exposing, it's just juicy.
|
| I don't think the media should share stuff like this just
| because it's interesting. They're making a market for
| corporate espionage to sell clicks.
| jiggywiggy wrote:
| Im a noob. But the time for Wikipedia language models &
| training models seems ripe.
| PeterCorless wrote:
| * https://en.wikipedia.org/wiki/Large_language_model#List_of_
| l...
|
| * https://en.wikipedia.org/wiki/List_of_datasets_for_machine-
| l...
| visarga wrote:
| I've been saying the same things for weeks, right here and in
| the usual places. Basically - OpenAI will not be able to
| continue to commercialise chatGPT-3.5, they will have to move
| to GPT-4 because the open source alternatives will catch up.
| Their island of exclusivity is shrinking fast. In a few months
| nobody will want to pay for GPT-4 either when they can have
| private, cheap equivalents. So GPT-5 it is for OpenAI.
|
| But the bulk of the tasks can probably be solved at 3.5 level,
| another more difficult chunk with 4, I'm wondering how many of
| the requests will be so complex as to require GPT-5. Probably
| less than 1%.
|
| There's a significant distinction between web search and
| generative AI. You can't download "a Google" but you can
| download "a LLaMA". This marks the end of the centralisation
| era and increased user freedom. Engaging in chat and image
| generation without being tracked is now possible while
| searching, browsing the web or torrenting are still tracked.
| com2kid wrote:
| > I've been saying the same things for weeks, right here and
| in the usual places. Basically - OpenAI will not be able to
| continue to commercialise chatGPT-3.5, they will have to move
| to GPT-4 because the open source alternatives will catch up.
| Their island of exclusivity is shrinking fast. In a few
| months nobody will want to pay for GPT-4 either when they can
| have private, cheap equivalents. So GPT-5 it is for OpenAI.
|
| It is worth $20 a month to have one UI on one service that
| does everything.
|
| Unless specialized models can far exceed what GPT4 can do,
| being general purpose is amazing.
|
| IMHO the future is APIs written for consumption by LLMs, and
| then natural language interfaces and just telling an AI
| literally anything you want done.
| Barrin92 wrote:
| >It is worth $20 a month to have one UI on one service that
| does everything.
|
| competition will drive profit margins and prices down to
| nothing because the number of companies that can spin up an
| UI is unlimited. Markets don't pay you what something is
| worth, they pay what the cheapest participant is willing to
| sell it for.
| bryanrasmussen wrote:
| >Markets don't pay you what something is worth, they pay
| what the cheapest participant is willing to sell it for.
|
| I believe 'what something is worth' is defined as what
| the market is willing to pay.
|
| And sometimes the customer will pay for something that
| isn't the cheapest of something, which is why I'm writing
| this on a mac.
| birdyrooster wrote:
| That last argument is a tautology btw
| com2kid wrote:
| > competition will drive profit margins and prices down
| to nothing
|
| I strongly suspect the profit margin on ChatGPT is
| already pretty low!
|
| > Markets don't pay you what something is worth, they pay
| what the cheapest participant is willing to sell it for.
|
| Correction: Markets pay what companies are able to
| convince consumers to pay. Some products bring negative
| value to the buyer, but are still sold for hundreds of
| millions of dollars (see: enterprise sales and
| integrations, which oftentime fail).
| dragonwriter wrote:
| > It is worth $20 a month to have one UI on one service
| that does everything.
|
| Today it is. When there is an open source, capable "one UI
| for everything" that runs locally and can consume external
| services as needed (but keeps your data locally otherwise),
| will it still be?
| xiphias2 wrote:
| I'm paying but hate the UI. I had to add labels myself as a
| Tampermonkey extension, but it would be much better if they
| would give API access to what I'm paying for and let UIs
| compete.
| huijzer wrote:
| I also would like to believe that, but there are countless
| examples which show the difference. Companies have no time to
| figure out which of the open source offerings is the best.
| Even worse, they don't have the time to switch from one
| project to the other or back to OpenAI if OpenAI releases a
| new state-of-the-art model.
| deanc wrote:
| And where are these open source models where I can go to a
| url and do all the things I can do in ChatGPT or through api
| keys for OpenAI? I googled a couple of weeks ago to find
| hosted versions of these open source models to try, and every
| one was either down or woefully poor.
|
| OpenAI and MS are going to win because they have a package to
| go and it's ready and available and working well - they have
| set the benchmark. I'm not seeing any evidence of this in the
| OSS community thus far.
|
| Until I can spin up a docker image capable of the same as
| OpenAI in hetzner for 30 bucks a month - it's not in the same
| league.
| icyfox wrote:
| One issue with the current generation of open source models
| is most have been based on some llama core architecture,
| and that's not licensed for commercial use. Once you get to
| the point of spinning up a full and easy API, and selling
| API credentials, you're entering into the commercial
| clause. Once we have a llama alternative (or a more
| permissively licensed separate architecture) I guarantee
| hosting providers like Render or Model are going to come in
| with an API offering. Just waiting on those core models to
| improve licensing, would be my guess.
| dragonwriter wrote:
| > Until I can spin up a docker image capable of the same as
| OpenAI in hetzner for 30 bucks a month - it's not in the
| same league.
|
| Yes, you are right
|
| That's irrelevant to the point of this, which is about the
| dynamics of the market over a longer window than "what is
| available to use immediately today", because a "moat" is a
| different thing than "a current lead".
| MacsHeadroom wrote:
| >Until I can spin up a docker image capable of the same as
| OpenAI in hetzner for 30 bucks a month
|
| I do exactly this with https://github.com/nsarrazin/serge
|
| Hetzner will install any hardware you send them for $100.
| So you can send them a $200 P40 24GB to run 33B parameter
| GPU models at ChatGPT speeds without increasing your
| monthly cost.
| deanc wrote:
| That $200 card's price seems to have been hit hard by
| inflation in Finland [1]
|
| [1] https://www.proshop.fi/Naeytoenohjaimet/HP-
| Tesla-P40-24GB-GD...
| digging wrote:
| > I'm wondering how many of the requests will be so complex
| as to require GPT-5
|
| I am not sure the pessimism is warranted. True that few
| people have the need to upgrade from GPT-3.5 to GPT-4 now,
| but if GPT-5 is another serious leap in capabilities, it
| might have an effect closer to the difference between old
| chatbots (useless, interesting) and ChatGPT (immediate
| economic impact, transforming some jobs). Or at any rate, we
| should expect such a leap to occur soon, even if it's not
| GPT-5.
| ngngngng wrote:
| Also significant to note that much of this AI boom was due
| to the UI of ChatGPT that gave everyone easy access to the
| model. Perhaps much of the improvements to be had in GPT-5
| will also be found in the UI. I mean UI in the broadest
| possible sense, I'm sure we'll come up with very creative
| ways to interact with this over the coming years.
|
| But the moat problem addressed in the article remains. Good
| luck patenting your amazing UI change in such a way that
| open source models can't catch up within a few weeks.
| seydor wrote:
| a lot of people have said similar things here
| raydiatian wrote:
| So when you see anti AI legislation, now we know it's for the
| sake of turning a buck for fucking Google
| rcme wrote:
| I think OpenAI has a defensible moat by having the first movers'
| advantage. As the ease of producing written content declines, we
| can expect the amount of written content to increase in a
| consummate fashion. Due to OpenAI's position, a vast majority of
| the newly generated data will come from OpenAI's models. When it
| comes time to train new models with superior network structures
| or with new data, no one else is going to be able to
| differentiate human-generated text from LLM generated text.
| OpenAI's training data should become far superior to others.
| sgt101 wrote:
| Anyone got a link to "Data Doesn't Do What You Think"?
| arnavsahu336 wrote:
| The only moat in technology are the founders and team. I think
| this concept of having a moat sounds great when VCs write
| investment memos - but in reality, cold, hard execution everyday
| is what matters and that all comes from the quality and tenacity
| of the team.
|
| Every piece of application software is a wrapper on other
| software with a set of opinionated workflows built on top.
|
| Yes, there are some companies that made it hard to switch from -
| Snowflake, Salesforce - because there are data stores and its a
| pain to move your record of data. But even they don't have true
| moats - its just sticker.
|
| So I think Google is right in saying there is no moat. But given
| their size, Google has layers and bureaucracy, which makes it
| hard to execute in a new market. That's why OpenAI I think will
| win - because they are smaller, can move fast, have a great team
| and can hence, execute...till the day they become a big company
| too and get disrupted by a new startup, which is the natural
| circle of life in technology.
| mark_l_watson wrote:
| Copied from other thread: I tend to agree. For now the OpenAI
| APIs are so very easy to use and effective. I do try to
| occasionally use HF models, mostly running locally in order to
| keep my options open. My bet is that almost everyone wants to
| keep their options open. I am very much into auxiliary tools like
| LangChain and LlamaIndex, the topic of my last book, but I also
| like building up my own tools from scratch (mostly in Common Lisp
| and Swift for now), and I bet most devs and companies are doing
| the same.
| tootie wrote:
| Hypothesis: We are about to begin the painful journey to a post-
| scarcity economy. AI will become incredibly powerful and
| uncontainable. Not in the Skynet way, but rather in the Star Trek
| way.
| cube2222 wrote:
| FWIW I posted Simon's summary because it's what I encountered
| first, but here's the leaked document itself[0].
|
| Some snippets for folks who came just for the comments:
|
| > While our models still hold a slight edge in terms of quality,
| the gap is closing astonishingly quickly. Open-source models are
| faster, more customizable, more private, and pound-for-pound more
| capable. They are doing things with $100 and 13B params that we
| struggle with at $10M and 540B. And they are doing so in weeks,
| not months.
|
| > A tremendous outpouring of innovation followed, with just days
| between major developments (see The Timeline for the full
| breakdown). Here we are, barely a month later, and there are
| variants with instruction tuning, quantization, quality
| improvements, human evals, multimodality, RLHF, etc. etc. many of
| which build on each other.
|
| > This recent progress has direct, immediate implications for our
| business strategy. Who would pay for a Google product with usage
| restrictions if there is a free, high quality alternative without
| them?
|
| > Paradoxically, the one clear winner in all of this is Meta.
| Because the leaked model was theirs, they have effectively
| garnered an entire planet's worth of free labor. Since most open
| source innovation is happening on top of their architecture,
| there is nothing stopping them from directly incorporating it
| into their products.
|
| > And in the end, OpenAI doesn't matter. They are making the same
| mistakes we are in their posture relative to open source, and
| their ability to maintain an edge is necessarily in question.
| Open source alternatives can and will eventually eclipse them
| unless they change their stance. In this respect, at least, we
| can make the first move.
|
| [0]: https://www.semianalysis.com/p/google-we-have-no-moat-and-
| ne...
| davidguetta wrote:
| Seems to be the Open Source who is the real winner overall..
| After OpenAI became basically ClosedAI it's an excellent news
| Levitz wrote:
| I'm not sure? Placing ethics constraints on a company under a
| capitalist system is hard. Placing them on open source is
| impossible.
| 0898 wrote:
| How can I get to a point where I can understand the linked
| article? Is there a book or course I can take? I feel like I have
| a lot of catching up to do.
| hammock wrote:
| The non-public moat is big multiyear government contracts with
| dark money. And there is room there for both players :)
| bitL wrote:
| Microsoft will likely acquire OpenAI at some point and will
| dominate AI landscape due to its corporate reach, automating away
| most of the MBA BS.
| rosywoozlechan wrote:
| OpenAI is a nonprofit, it owns the for profit org that it
| created. It's not acquirable.
| sgdh wrote:
| [dead]
| joezydeco wrote:
| _" Many of the new ideas are from ordinary people."_
|
| Yeah. Google can fuck right off. Maybe this attitude is what got
| them in the weeds in the first place.
| uptownfunk wrote:
| I was quite unimpressed when I interviewed with them recently.
| It's no surprise their lunch is getting eaten.
| GartzenDeHaes wrote:
| Yes, it's very telling.
| _trackno5 wrote:
| I get the feeling that at this point, the best thing Google could
| do is to go all in an open source their models and weights.
| They'd canibalize their own business, but they'd easily wipe out
| most of the competition.
| madsbuch wrote:
| I would lean towards agreeing. And I definitely think AI
| companies should not try to make their money on inference.
|
| If there is a well performing model being deployed it is possible
| to train a similar model while not having to eat the cost of
| exploration. Ie. it is only the the cost of training said model.
|
| ChatGPT would probably die in a couple of weeks, if an
| equivalent, free, product came out that people could run on their
| computers.
| lee101 wrote:
| [dead]
| GartzenDeHaes wrote:
| > Paying more attention to their work could help us to avoid
| reinventing the wheel.
|
| There's nothing us humans love more than reinventing the wheel.
| I've seen it over and over again, years of work and hundreds of
| millions of dollar spent re-solving problems and re-writing
| systems -- only to replace them with a new set of slightly
| different problems. I think we greatly over estimate the ability
| of our species to accumulate knowledge, which is perhaps where
| these generative systems come into play.
| sgdh wrote:
| [dead]
| [deleted]
| vlovich123 wrote:
| I think that analogy is flawed to try to undercut OpenAI's lead.
| The reason it's flawed is that the search business is really
| lucrative and OpenAI is trying to completely disrupt Google's
| business there. So while the AI isn't a moat, establishing a lead
| in search is because you obviously will use that to inject ads in
| the commercial space and capture the market.
| kyaghmour wrote:
| Google's moat is its data set. Imagine training an generative AI
| LLM on the entire set of YouTube training videos. No one else has
| this.
| dopeboy wrote:
| This is the glaring omission in this piece.
|
| Googles know _so much_ about me. Is it not reasonable to assume
| powerful llm + personal data = personal tuned LLM?
| RecycledEle wrote:
| The entire set of YouTube training videos needs to be re-
| transcribed before they are useful for training LLMs.
| duckkg5 wrote:
| [flagged]
| swyx wrote:
| > shared anonymously on a public Discord server
|
| whichdiscord?
| DethNinja wrote:
| If OpenAI has no moat, how come nobody has built a better
| alternative to GPT-4 yet?
| okasaki wrote:
| [flagged]
| hammock wrote:
| There is a huge (non-public) moat. It's big multiyear government
| contracts with dark money. And there is room there for both
| players :)
| neycoda wrote:
| When people start becoming emotionally attached to their AI
| helpers, they'll fight for them to have sentient rights.
| minimaxir wrote:
| Having enough scale to perpetually offer free/low-cost compute is
| a moat. The primary reason ChatGPT went viral in the first place
| was because it was free, with no restrictions. Back in 2019,
| GPT-2 1.5B was made freely accessible by a single developer via
| the TalkToTransformers website, which was the very first time
| many people talking about AI text generation...then the owner got
| hit with sticker shock from the GPU compute needed to scale.
|
| AI text generation competitors like Cohere and Anthropic will
| never be able to compete with Microsoft/Google/Amazon on marginal
| cost.
| dragonwriter wrote:
| > Having enough scale to perpetually offer free/low-cost
| compute is a moat.
|
| Its a moat for services, not models, and its only a moat for AI
| services as long as that compute isn't hobbled by being used
| for models which are so inefficient compared to SOTA as to
| waste the advantage, which underlines why leaning into open
| source the way this piece urges is in Google's interests, the
| same way open source has worked to Google and Amazon's benefits
| as service providers in other domains.
|
| (Not so much "the ability to offer free/low-cost compute" but
| "the advantages of scale and existing need for widely
| geographically dispersed compute on the cost of both marginal
| compute and having marginal compute close to the customer where
| that is relevant", but those are pretty close to differenly-
| focussed rephrasings of the same underlying reality.)
| seydor wrote:
| That's what a lot of people think until they run Vicuna 13B or
| equivalent. We're just 5 months in this, there will be many
| leaps.
| bilbo0s wrote:
| Yes there will, that's the problem HN User Minimaxir is
| talking about.
|
| It will only get less and less expensive for Microsoft in
| terms of cost. And more and more effective for Microsoft in
| terms of results delivered.
|
| How do you compete with free? That's the question. The
| previous internet experience has already shown us that "also
| be free" is not really a sustainable or even effective
| answer. You have to be better in some fundamental dimension.
| [deleted]
| [deleted]
| BiteCode_dev wrote:
| What makes you think open ai won't look at the FOSS
| improvements, include them in their tech, and make their GPU
| farm way cheaper, rendering their service even more
| competitive?
|
| Not to mention it's easy to run stable diffusion, but
| midjourney is still a good business. I can run sd on my
| laptop, I still pay for midjourney because it's convenient,
| the out of the box experience is better than any competition,
| and it keeps improving.
| syntheweave wrote:
| The reason why proprietary software ever had a moat simply
| comes down to: software startups could dump investment
| capital onto the development process and achieve results
| much faster, with better user interfaces, allowing them to
| achieve path dependence in their customer base. Thus we had
| a few big application verticals that were ultimately won by
| MS Office, Adobe Photoshop, etc.
|
| If the result here is as marginal as it seems - a few
| months of advantage in output quality and a slightly more
| sleek UI - the capital-intensive play doesn't work. The
| featuresets that industrial users want the most depend on
| having more control over the stack, not on UI or output
| quality. The open source models are stepping up to this
| goal of "cheap and custom". Casual users can play with the
| open models without much difficulty either, provided they
| take a few hours to work through an installation tutorial -
| UI isn't a major advantage when the whole point is that
| it's a magic black box.
| seydor wrote:
| that's like saying that apple and MS can look into linux
| and steal ideas. Yes they can do that but it doesnt make
| linux any less useful. If anything they learned to
| contribute back to the common pile, because everyone
| benefits from it. It would be a problem if this was a one-
| way relationship , which it doesnt seem to be. If Open
| source is making them more money, why kill it
| BiteCode_dev wrote:
| You are making my point: linux, mac and windows coexist,
| despite the overwhelming strength of open source, and the
| proprietary platforms are quite profitable.
| seydor wrote:
| But the point is not to kill commercial software because
| then OSS will die too because people will have to find
| other jobs
| Tyr42 wrote:
| I mean, read the article, the author is concerned about
| that, and wants Google to open source more so it's not just
| Facebook's lama that gets open source building on it.
| freediver wrote:
| > AI text generation competitors like Cohere and Anthropic will
| never be able to compete with Microsoft/Google/Amazon on
| marginal cost.
|
| Anthropic already does, with its models. They are same price or
| cheaper than OpenAI, with comparable quality.
|
| > Having enough scale to perpetually offer free/low-cost
| compute is a moat.
|
| Rather than a moat it is a growth strategy. At one point in
| time you need to start to monetize and this is the moment when
| rubber hits the road. If you can survive monetization and
| continue to grow, now you have a moat.
| BiteCode_dev wrote:
| And ChatGPT has a super low barrier to entry while open source
| alternatives have a high one.
|
| Creating a service that can compete with it on that regard
| implies you can scale GPU farms in a cost effective way.
|
| It's not as easy as it sounds.
|
| Meanwhile, openai still improves their product very fast, and
| unlike google, it's their only one. It's their baby. It has
| their entire focus.
|
| Since for most consumers, AI == ChatGPT, they have the best
| market share right now, which mean the most user feedback to
| improve their product. Which they do at a fast pace.
|
| They also understand that to get mass adoption, they need to
| censor the AI, like MacDonald and Disney craft their family
| friendly image. Which irritate every geeks, including me, but
| make commercially sense.
|
| Plus, despite the fact you can torrent music and watch it with
| VLC, and that Amazon+Disney are competitors, netflix exists.
| Having a quality service has value in itself.
|
| I would not count open ai as dead as a lot of people seem to
| desperately want it to be. Just because Google missed the AI
| train doesn't mean wishful thinking the market to be killed by
| FOSS is going to make it so.
|
| As usual with those things it's impossible to know in advance
| what's going to happen, but odds are not disfavoring chatgpt as
| much as this article says.
| FemmeAndroid wrote:
| Charity is only a moat if it's not profitable.
| moron4hire wrote:
| In other words, engage in anti-competitive behavior.
| r00fus wrote:
| There's "immediately profitable" and "eventually profitable".
| Vast compute scale allows collection of customer generated
| data so the latter is possible, AI as of yet is not the
| former.
|
| So GP point still stands. FAAMG can run much larger immediate
| deficits in order to corner the market on the eventual
| profitability of AI.
| indymike wrote:
| > . FAAMG can run much larger immediate deficits in order
| to corner the market on the eventual profitability of AI.
|
| This assumes that there is a corner-able market.
| Previously, the cost of training was the moat. That appears
| to have been more of a puddle under the gate than an actual
| moat.
| Tostino wrote:
| The amount of valuable data generated from professionals
| using these services to work through their problems and
| find solutions to industry problems is immense. It
| essentially gives these companies the keys to automating
| many industries by just...letting people try and make their
| jobs easier and collecting all data.
| cushpush wrote:
| All this talk that every investment pays off in the end is
| faulty and dangerous. Many investments don't pan out, 95%
| of the firms you see in the ticker this decade might be
| gone, and yet everyone is very confident is underwriting
| these "losses for future gains" but really it's economies
| of scale. It doesn't cost MSFT much more to run the GPU
| than to turn it on in the first place.
| sharemywin wrote:
| This is the timeline that's scaring the shit out of them:
|
| Feb 24, 2023: Meta launches LLaMA, a relatively small, open-
| source AI model.
|
| March 3, 2023: LLaMA is leaked to the public, spurring rapid
| innovation.
|
| March 12, 2023: Artem Andreenko runs LLaMA on a Raspberry Pi,
| inspiring minification efforts.
|
| March 13, 2023: Stanford's Alpaca adds instruction tuning to
| LLaMA, enabling low-budget fine-tuning.
|
| March 18, 2023: Georgi Gerganov's 4-bit quantization enables
| LLaMA to run on a MacBook CPU.
|
| March 19, 2023: Vicuna, a 13B model, achieves "parity" with
| Bard at a $300 training cost.
|
| March 25, 2023: Nomic introduces GPT4All, an ecosystem
| gathering models like Vicuna at a $100 training cost.
|
| March 28, 2023: Cerebras trains an open-source GPT-3
| architecture, making the community independent of LLaMA.
|
| March 28, 2023: LLaMA-Adapter achieves SOTA multimodal
| ScienceQA with 1.2M learnable parameters.
|
| April 3, 2023: Berkeley's Koala dialogue model rivals ChatGPT
| in user preference at a $100 training cost.
|
| April 15, 2023: Open Assistant releases an open-source RLHF
| model and dataset, making alignment more accessible.
| int_19h wrote:
| This really ought to mention
| https://github.com/oobabooga/text-generation-webui, which
| was the first popular UI for LLaMA, and remains one for
| anyone who runs it on GPU. It is also where GPTQ 4-bit
| quantization was first enabled in a LLaMA-based chatbot;
| llama.cpp picked it up later.
| sharemywin wrote:
| this doesn't even include the stuff around agents and/or
| langchain
| politician wrote:
| The post mentions that they consider "Responsible
| Release" to be an unsolved hard problem internally. It's
| possible that they are culturally blind to agents.
| ByThyGrace wrote:
| Interesting! It's like nothing has happened on the field
| for the last three weeks heh
| newswasboring wrote:
| OpenLlaMa came out last week I think.
| Tyr42 wrote:
| The doc was written a bit ago.
| deelowe wrote:
| It seems the plan is to be a loss leader until scale is
| sufficient to reach near AGI levels of capability.
| nirav72 wrote:
| There was some indication recently that OpenAI was spending
| over $500k/day to keep it running. Not sure how long thats
| going to last. AGI is still a pipe dream. Sooner or later ,
| they're going to have to make money.
| cmelbye wrote:
| Assuming you're talking about the free ChatGPT product,
| it's important to consider the value of the training data
| that users are giving them.
|
| Beyond that, they are making a lot of money from their
| enterprise offerings (API products, custom partnerships,
| etc.) with more to come soon, like ChatGPT for Business.
| phatfish wrote:
| I know there are use cases out there, so it's not a dig.
| I'm curious how many enterprises are actually spending
| money with OpenAI right now to do internal development.
| Have they released any figures?
| blihp wrote:
| Oh no, they're going belly up in 20,000 days! (i.e. $10B
| / 500k) Compute is going to keep getting cheaper and
| they're going to keep optimizing it to reduce how much
| compute it needs. I'm more curious about their next steps
| rather than how they're going to keep the lights on for
| ChatGPT.
| adrianmonk wrote:
| https://www.youtube.com/watch?v=z9OUZNicTGU&t=123s
| Workaccount2 wrote:
| $500k/day for a large tech company is absolutely peanuts.
| Open.AI could probably even get away with justifying
| $5M/day right now.
| bickfordb wrote:
| A good example of this is Youtube
| fnordpiglet wrote:
| The moat comes by integrated LLM and generative AI into classical
| technique feedback cycles, finetuning in specialized domains, and
| other "application" of LLM where LLM acts as an abstract semantic
| glue between subsystems, agents, optimizers, and solvers. The
| near obsessive view that generative AI is somehow an end rather
| than an enabler is one of the more shortsighted sides I see in
| this whole discussion of generative AIs over the last several
| years, peaking recently with ChatGPT
| [deleted]
| homeless_engi wrote:
| I don't understand. ChatGPT cost an estimated 10s of millions ot
| train. ChatGPT 4.0 has much better performance than the next best
| model. Isn't that a moat?
| mirekrusin wrote:
| Spot on.
|
| I think author forgot to mention StableLM?
| sounds wrote:
| Repeating myself from
| https://news.ycombinator.com/item?id=35164971 :
|
| > OpenAI can't build a moat because OpenAI isn't a new vertical,
| or even a complete product.
|
| > Right now the magical demo is being paraded around, exploiting
| the same "worse is better" that toppled previous ivory towers of
| computing. It's helpful while the real product development
| happens elsewhere, since it keeps investors hyped about
| something.
|
| > The new verticals seem smaller than all of AI/ML. One company
| dominating ML is about as likely as a single source owning the
| living room or the smartphones or the web. That's a platitude for
| companies to woo their shareholders and for regulators to point
| at while doing their job. ML dominating the living room or
| smartphones or the web or education or professional work is
| equally unrealistic.
| photochemsyn wrote:
| ML dominating education seems pretty realistic to me. E.g. this
| series of prompts for example:
|
| > "Please design a syllabus for a course in Computer
| Architecture and Assembly language, to be taught at the
| undergraduate level, over a period of six weeks, from the
| perspective of an professor teaching the material to beginning
| students."
|
| > "Please redesign the course as an advanced undergraduate six-
| month Computer Architecture and Assembly program with a focus
| on the RISC-V ecosystem throughout, from the perspective of a
| professional software engineer working in the industry."
|
| > "Under the category of Module 1, please expand on
| "Introduction to RISC-V ISA and its design principles" and
| prepare an outline for a one-hour talk on this material"
|
| You can do this with any course, any material, any level of
| depth - although as you go down into the details,
| hallucinations do become more frequent so blind faith is
| unwise, but it's still pretty clear this has incredible
| educational potential.
| sounds wrote:
| Fortunately, what I said was that a single company becomes
| the sole source for the ML in education; not the same thing
| and thus I have no conflict with your statement.
| chinchilla2020 wrote:
| This is not a leaked google memo. I can't believe hackernews
| believes an article like this is a memo at google. Kudos to the
| authors for finding a sneaky way to get traffic.
| Gatsky wrote:
| Yeah this doesn't quite sit right. It lacks any detail about
| what Google is actually doing.
| seydor wrote:
| Not only they have no moat, Open source models are uncensored and
| this is huge. Censorship is not just political , it cripples the
| product to basically an infantile stage and precludes so many
| applications. For once, it is a liability
|
| But this article doesn't state the very obvious: When will google
| (the inventor of Transformer, and "rightful" godfather of modern
| LLMs) , release a full open source, tinkerable model better than
| LLaMa?
|
| (To the dead comment below, there are many uncensored variations
| of vicuna)
| UncleEntity wrote:
| > When will google release a full open source, tinkerable model
| better than LLaMa?
|
| Arguably, Facebook released llama because it had no skin in the
| game.
|
| Google, on the other hand, has a lot of incentive to claw back
| the users who went to Bing to get their AI fix. Presumably
| without being the place for "Ok, google, write me a 500 word
| essay on the economic advantages of using fish tacos as
| currency" for peoples' econ 101 classes causing all kinds of
| pearl clutching on how they're destroying civilization.
|
| The open source peeps are well on the path of recreating a
| llama base model so unless google does something spectacular
| everyone will be like, meh.
| thomas34298 wrote:
| [dead]
| 0xbadcafebee wrote:
| Innovation is faster in the Bazaar. Nobody is beholden to anyone,
| there is no budget, there is no mandate, there is no hierarchy.
| Money can not compete with morale and motivation. A bunch of
| really smart nerds working overtime for free with flat hierarchy
| will always win.
| sashank_1509 wrote:
| Cringe, haven't seen a single Open Source come even close to the
| ability of Bard, let alone ChatGPT. Seems like wishful thinking
| to think decentralized open source can beat centralized models
| that cost 100M+ to train!
| lapinot wrote:
| > Seems like wishful thinking to think decentralized open
| source can beat centralized models that cost 100M+ to train!
|
| Because surely price = quality. Solid argumentation there.
| Hippocrates wrote:
| I'd agree they aren't close, but they are way better than I
| expected to see in a short few months. At this rate they'll be
| approaching "good enough" for me pretty soon. I don't always
| need a dissertation out of it unless I'm fooling around. I want
| quick facts and explainers around difficult code and
| calculations. Been playing with Vicuna-7b on my iPhone through
| MLC Chat and it's impressive.
|
| I use DDG over Google for similar reasons. It's good enough,
| more "free" (less ads), and has better privacy.
| akomtu wrote:
| Once distributed training is solved, all those big LLMs will
| be left in the dust.
| Hippocrates wrote:
| I figured that. I would love to contribute compute to such
| a thing. Is there any effort or development in progress?
| What are the hurdles?
| Art9681 wrote:
| If all you've done is download the model and perform basic
| prompts then I understand why you think this. There is a lot
| more going on behind Bard and GPT than a chat window passing
| the inputs to the model.
|
| Edit for clarity: You're comparing a platform (Bard, GPT) to a
| model (llama, etc). The majority of folks playing with local
| models are missing the platform.
|
| In order to close the gap, you need to hook up the local models
| to LangChain and build up different workflows for different use
| cases.
|
| Consequently, this is also when you start hitting the limits of
| consumer hardware. It's easy to download a torrent, double
| click the binary and pass some simple prompts into the basic
| model.
|
| Once you add memory, agents, text splitters, loaders, vector
| db, etc, is when the value of a high end GPU paired with a
| capable CPU + tons of memory becomes evident.
|
| This still requires a lot of technical experience to put
| together a solution beyond running the examples in their docs.
| alsodumb wrote:
| All the things you mentioned make it a platform, but even as
| a model, none of the smaller open-source models come close to
| GPT 3.5 or 4 in my experience. You can test it by using the
| GPT3.5 or 4 with their API. They outputs are waaaay better
| than anything I get from the open source models.
| crazyedgar wrote:
| Are you sure? I have yet to see any evidence that anyone at
| all (including Google) has built a model (or a "platform" as
| you prefer to refer to them) that can follow instructions as
| well as 50% of ChatGPT, let alone GPT-4. I don't think any
| amount of work in LangChain and vector databases is enough to
| fix this: you really need a strong base model that is trained
| to align with human intentions well. Of course if you just
| want a bot that can answer free-form simple questions, then
| maybe people can't tell the difference. Just give them some
| real work to do and it becomes glaringly obvious.
| fzliu wrote:
| Vector databases such as Milvus are only there to help
| reduce/minimize hallucinations rather than get rid of them
| completely. Until we have a model architecture that can
| perform completion from the _prompt only_ rather than pre-
| training data, hallucinations will always be present.
| vlovich123 wrote:
| Is there any reason to think that zero-shot learning and better
| models/more effient AI won't drastically reduce those costs
| over time?
| ebiester wrote:
| Think a little more laterally.
|
| If we're talking about doing _everything_ well, I think that 's
| true. However, if I want to create my own personal "word
| calculator," I could take, for example, my own work (or
| Hemingway, or a journalist) and feed an existing OSS model my
| of samples, and then take a set of sources (books, articles,
| etc), I might be able to build something that could take an
| outline and write extended passages for me, turning me into an
| editor.
|
| A company might feed its own help documents and guidance to
| create its own help chat bot that would be as good as what
| OpenAI could do and could take the customer's context into the
| system without any privacy concerns.
|
| A model doesn't have to be better at everything to be better at
| something.
| tshadley wrote:
| From the article:
|
| "April 3, 2023 - Real Humans Can't Tell the Difference Between
| a 13B Open Model and ChatGPT
|
| Berkeley launches Koala, a dialogue model trained entirely
| using freely available data.
|
| They take the crucial step of measuring real human preferences
| between their model and ChatGPT. While ChatGPT still holds a
| slight edge, more than 50% of the time users either prefer
| Koala or have no preference. Training Cost: $100."
| crazyedgar wrote:
| This is hugely misleading. If your bot just memorizes
| Shakespeare and output segments from memorization, of course
| nobody can tell the difference. But as soon as you start
| interacting with them the difference can't be more
| pronounced.
| e63f67dd-065b wrote:
| The test was conducted as such:
|
| >With these two evaluation sets, we conducted a blind
| pairwise comparison by asking approximately 100 evaluators
| on Amazon Mechanical Turk platform to compare the quality
| of model outputs on these held-out sets of prompts. In the
| ratings interface, we present each rater with an input
| prompt and the output of two models. They are then asked to
| judge which output is better (or that they are equally
| good) using criteria related to response quality and
| correctness.
|
| No, it's not just memorising shakespeare, real humans
| interacted with the models and rated them.
| crazyedgar wrote:
| That's not what I meant by interaction. The evaluator had
| to ask the models to do tasks for them that they thought
| of by their own. Otherwise there are just too many ways
| that information could have leaked.
|
| OpenAI's model isn't immune from this either, so take any
| so-called evaluation metrics with a huge grain of salt.
| This also highlights the difficulties of properly
| evaluating LLMs: any metrics, once set up, can become a
| memorization target for LLMs and lose their meaning.
| zoiksmeboiks wrote:
| [dead]
| DonHopkins wrote:
| >Research institutions all over the world are building on each
| other's work, exploring the solution space in a breadth-first way
| that far outstrips our own capacity.
|
| BroadMind beats DeepMind!
| drcode wrote:
| dissaproving_drake.jpg: Giving evidence you can match the
| capabilities of OpenAI
|
| approving_drake.jpg: Saying everything OpenAI does is easy
| ad404b8a372f2b9 wrote:
| I'm feeling strangely comforted to have pictured the
| mythological creature before the meme.
| hannofcart wrote:
| Yes. Same here. I had flashes of Battle of Wesnoth. Then I
| realized...
| CSMastermind wrote:
| I remember I was at Microsoft more than a decade ago now and at
| the time there was a lot of concern about search and how far Bing
| lagged behind Google in geospatial (maps).
|
| After some initial investment in the area I was at a presentation
| where one of the higher ups explained that they'd be abandoning
| their investment because Google Maps would inevitably fall behind
| crowdsourcing and OpenStreetMap.
|
| Just like Encarta and Wikipedia we were told - once the open
| source community gets their hands on something there's just no
| moat from an engineering perspective and once it's crowdsourced
| there's no moat from a data perspective. You simply can't
| compete.
|
| Of course it's more than a decade later now and I still use
| Google Maps, Bing Maps still suck, and the view times I've tried
| OpenStreetMaps I've found it far behind both.
|
| What's more every company I've worked at since has paid Google
| for access to their Maps API.
|
| I guess the experience made me skeptical of people proclaiming
| that someone does or does not have a moat because the community
| will just eat away at any commercial product.
| purpleblue wrote:
| Open source will never defeat a company in areas where the work
| is very, very boring and you have to pay someone to do the
| grunt work. The last 20% of most tasks are extremely boring so
| things like data quality can only be accomplished through paid
| labor.
| Scubabear68 wrote:
| I stopped using Google Maps in my car with CarPlay, because the
| map would lag by about 5 seconds to reality, which is really
| bad at say 55 mph in a place where you're not familiar.
|
| Been using Apple Maps now for six months, and very happy with
| it. No lag, and very useful directions like "turn left at the
| second stop light from here".
| IIAOPSW wrote:
| I've been using osm more and more recently. Google just makes a
| bunch of frustrating decisions that really pushed me to look
| elsewhere. Especially in the public transport layer, but more
| generally in being really bad at deciding when to hide details
| with no way to override it and say "TELL ME THE NAME OF THIS
| CROSS STREET DAMNIT THATS THE ONLY REASON I KEEP ZOOMING IN
| HERE!!!".
| thepasswordis wrote:
| One unbelievably annoying thing about seemingly every map
| provider is that they don't like showing state or national
| boundaries.
|
| On google maps, these national boundaries have the same line
| weight and a similar style to highways. It's really annoying.
| CamperBob2 wrote:
| This. My car uses Google Maps for its built-in nav system,
| and I've spent a lot of time on road trips wondering just
| what state I was in. It's insane that Google hasn't added
| something as trivial and important as state borders.
| wilkystyle wrote:
| > _generally in being really bad at deciding when to hide
| details with no way to override it and say "TELL ME THE NAME
| OF THIS CROSS STREET DAMNIT THATS THE ONLY REASON I KEEP
| ZOOMING IN HERE!!!"._
|
| Stuff like this is the main reason I end up switching to
| Apple Maps on the occasions that I do so. Another example is
| refusing to tell me the number of the upcoming exit I'm
| taking.
|
| In general I would say Google Maps is still superior to Apple
| Maps, but between the aforementioned baffling design
| decisions and Google maps now including ads in destinations
| search results, I find myself experiencing more and more
| mental friction whenever I use it.
| LatticeAnimal wrote:
| There is a spot in NYC where zooming in on my iPhone in
| Apple Maps in satellite view causes the app to crash
| somewhat reliably. It has been happening for the last few
| months.
| IIAOPSW wrote:
| That section of Queens is uncomputable and even crashes
| human minds on occasion
| inferiorhuman wrote:
| The inability to easily get a street name is one of my
| biggest pet peeves with Apple Maps, it's up there with the
| generally poor quality of turn-by-turn navigation (at least
| in the Bay Area).
| Nick87633 wrote:
| That's funny because when driving in the bay area,
| inability to get the -name- of the upcoming exit from
| google maps was driving me nuts! The exit numbers are not
| listed on the upcoming exit/distance signs on 280.
| amluto wrote:
| Both apps seem to get the names of exits consistently
| wrong in the Bay Area. I don't care what a map thinks the
| name should be -- I care what the sign says.
| RajT88 wrote:
| Google maps is at least getting better about screen real
| estate. I have an android head unit, and Maps clearly
| assumed you'd always be using Maps in portrait mode,
| because the bottom bar would clutter up the bottom of the
| screen with "local stuff near by you might be interested
| in" if you weren't actively navigating.
|
| Eventually switched to Waze, which is now also cluttering
| things up with (basically) ads.
| tasuki wrote:
| Google maps is good at navigation, finding business names etc.
| OpenStreetMap is much more detailed wherever I've gone.
|
| When I'm lost in a forest, I look at OSM to see where the
| footpaths are.
| kerkeslager wrote:
| The difference being, in this case, the author is giving
| examples of places where their product is clearly behind.
|
| This isn't a prediction, it's an observation. There's no moat
| because the castle has already been taken.
| pphysch wrote:
| Data is still valuable and you can build a moat with it. But
| this discussion isn't about data, it's about models.
|
| A better analogy would be paywalled general-purpose programming
| languages, where _any_ access to running code is restricted.
| Such a programming language would get virtually no mindshare.
|
| This Google employee is just saying, let's not make that
| mistake.
|
| Even if Google fired all AI researchers tomorrow and just used
| open source models going forward, they could still build killer
| products on them due to their data moat. That's the takeaway.
| araes wrote:
| The problem with a lot of open source is the long term issue.
|
| The people doing many of these projects often want the short
| term kudos, upvotes, or research articles. They may iterate
| fast, and do all kinds of neat advancements, except in a month
| they'll move to the next "cool" project.
|
| Unfortunately, with a lot of open source projects, they don't
| want to deal with the legalese, the customer specific
| integration, your annoying legacy system, the customer support
| and maintenance, or your weird plethora of high-risk data types
| (medical industry I'm looking at you)
|
| Not sure what the Wikipedia reference is, since how many people
| use any form of encyclopedia other than crowdsourced Wikipedia?
|
| However, to note, there are some examples of successful long
| term open source. Blender for example being a relatively strong
| competitor for 3D modeling (although Maya still tends to be
| industry dominant).
| valine wrote:
| Open source works well when the work is inherently cool and
| challenging enough to keep people engaged. Linux and Blender
| are two of the most successful open source projects, and the
| thing they have in common is that problems they solve are
| problems engineers enjoy working on.
|
| Mapping intersections is extremely boring in comparison. The
| sheer quantity of boring work needed to bring open street maps
| up to the quality of google maps in insurmountable.
|
| LLMs are freaking cool, and that bodes well for their viability
| as open source projects.
| Certhas wrote:
| My impression is that open street maps problem is not the map
| quality. In areas I have used it, it often has details (e.g.
| small hiking paths, presence of bike lanes) that google maps
| doesn't have.
|
| The issue is search. Searching for things that you don't know
| precisely (music bars in this area). This type of
| data/processing on top of the geospatial was always subpar
| and very hit or miss in my experience.
| valine wrote:
| That's not my experience. I work in downtown Minneapolis
| and open street maps is missing basic things like entrances
| to public parking lots. Open street maps has a problem if
| it can't get details right in population dense areas.
| moffkalast wrote:
| It's very hit and miss, as it's dependant on how many
| perfectionistic mapping enthusiasts that edit OSM as a
| hobby are in your area.
| danhor wrote:
| It really depends, but in germany (has a large OSM
| community) OSM has so much better quality & detail for
| almost everything except buisnesses. It suffers from poor
| search, routing that doesn't take traffic jams or
| roadworks into account and a lack of high quality apps
| and thus only "nerds" use it instead of Google Maps or
| others.
| jimsimmons wrote:
| Databases are another data point that fit this pattern.
| They're not sexy and commercial players like Oracle have
| moat.
| badpun wrote:
| Databases are very sexy? They're super interesting from
| programming/CS perspective for multiple reasons.
| HillRat wrote:
| That's ... probably not the best example, given the fact
| that there are a shedload of open-source databases of
| various types that have forced major commercial vendors
| like MSFT and ORCL into a corner. ORCL's moat is that they
| have a large portfolio of random solutions, are incumbent
| at a lot of organizations where switching costs are very
| high, and they have an exceptionally aggressive sales
| organization that doesn't seem to worry too much about
| legalities.
| slondr wrote:
| Have you heard of PostgreSQL, MariaDB, or SQLite? They have
| very high market share.
| kelsolaar wrote:
| And arguably Blender is much more innovative and achieving
| faster progress than proprietary and commercial software such
| as Autodesk Maya.
| [deleted]
| tpmx wrote:
| Is that a relevant comparison? The moat in maps is primarily
| capital-intensive real-world data collection/licensing.
|
| The (supposedly) leaked article attempts to show that this
| aspect isn't that relevant in the AI/LLM context.
| jeffreyrogers wrote:
| I think the difference is that Maps is a product and its hard
| to copy a whole product and make it good without someone
| driving the vision. But a model is just a model, in terms of
| lines of code they aren't even that large. Sure the ideas
| behind the are complicated and take a lot of thought to come up
| with, but just replicating it or iterating it is obviously not
| the challenging based on recent developments.
| boh wrote:
| This isn't an apt comparison. Maps need to be persistently
| accurate and constantly updated regardless of community
| involvement, AI just has to be somewhat applicable to the paid
| version (which, given its stochastic nature, the open source
| alternatives are close enough). Microsoft obviously
| misunderstood the needs of maps at the time and made the wrong
| conclusion. The lack of moat for AI is closer to the
| Encarta/Wikipedia scenario than the maps scenario.
| LanternLight83 wrote:
| Just anacdotally, I see OSM mentioned a lot, guides for
| contributing, use in HomeLab and Raspberry Pi articles--
| haven't check it out myself in a long time, but I wouldn't be
| surprised if it's continued growth really is inevitable, or
| even has a cumulative snowball-ball component
| moffkalast wrote:
| OSM's main problem is that it has no open sourced satelite
| imagery dataset to display, they're only using borrowed data
| to build its vector maps on. It just doesn't exist. Until
| that becomes a thing it'll stay a second rate map app for the
| average person, unfortunately.
|
| It's the only map anyone can actually integrate into anything
| without an api key and a wallet with a wad of greens in it,
| so that keeps it relevant for now. Maybe if/when Starship
| lowers cost to orbit, then we'll see non-profit funded
| satellites that can source that dataset and keep it up to
| date.
| ElevenLathe wrote:
| Do you happen to know why there isn't any U.S. Government
| satellite imagery? I understand the really high-resolution
| stuff is probably from spysats and so classified, but
| anything else should be public domain, no?
| kevin_thibedeau wrote:
| Everything under NASA's and NOAA's purview is public
| domain. High resolution stuff is left to commercial and
| secret applications. Some states also have high res
| aerial photography. This was notably obvious in the early
| days of gmaps when the whole US was Landsat only with
| aerial for just Massachusetts.
| holmesworcester wrote:
| This sounds right to me and was similar to my reaction. The
| doubt I had reading this piece is that GPT4 is so substantially
| better than GPT3 on most general tasks that I feel silly using
| GPT3 even if it could potentially be sufficient.
|
| Won't any company that can stay a couple years ahead of open
| source for something this important will be dominant as long as
| it can do this?
|
| Can an open source community fine tuning on top of a smaller
| model consistently surpass a much larger model for the long
| tail of questions?
|
| Privacy is one persistent advantage of open source, especially
| if we think companies are too scared of model weights leaking
| to let people run models locally. But copyright licenses give
| companies a way to protect their models for many use cases, so
| companies like Google _could_ let people run models locally for
| privacy and still have a moat, if that 's what users want, and
| anyway most users will prefer running things in the cloud for
| better speed and to not have to store gigabytes of data on
| their devices, no?
| astridpeth wrote:
| wrong.
|
| Crowdsource is significantly different from open source.
|
| Open source is Linux winning because you don't need to pay
| Microsoft, anyone can fork, Oracle/IBM and Microsoft's enemies
| putting developers to make it better and so on. Today .NET runs
| on Linux.
|
| Crowdsource is the usual bs that either through incentives
| (like crypto) or by heart, people will contribute to free
| stuff. It doesn't have the openness, liberty or economic
| incentives open source has.
|
| And Google has lots of crowdsourced data on Maps, I know lots
| of people who loves to be a guide there.
| qwertox wrote:
| Google Maps 3D view is unmatched compared to anything open
| source has to offer.
|
| Let alone the panning and zooming, there is no open source
| solution which is capable of doing it with such a correctness,
| even if we ignore Google's superb "satellite" imagery with its
| 3D conversion. I have no access to Apple Maps, so I can't
| compare (DuckDuckGo does not offer Apple's 3D view).
| [deleted]
| yafbum wrote:
| This is an excellent point. I think the memo is making a
| different kind of case though - it's saying that large
| multipurpose models don't matter because people already have
| the ability to get better performance on the problems they
| actually care about from isolated training. It's kind of a PC-
| vs-datacenter argument, or, to bring it back to Maps, it'd be
| like saying mapping the world is pointless because what
| interests people is only their neighborhood.
|
| I don't buy this for Maps, but it's worth highlighting that
| this isn't the usual "community supported stuff will eat
| commercial stuff once it gets to critical mass" type of
| argument.
| aamar wrote:
| This is an instructive error. From my perspective, there was
| plenty of evidence even 15 years ago that community efforts
| (crowd-sourcing, OSS) only win sometimes, on the relevant
| timeframes.
|
| So the "higher ups" were using too coarse a heuristic or maybe
| had some other pretty severe error in their reasoning.
|
| The right approach here is to do a more detailed analysis. A
| crude start: the community approach wins when the MVP can be
| built by 1-10 people and then find a market where 0.01% of the
| users can sufficiently maintain it.[1]
|
| Wikipedia's a questionable comparison point, because it's such
| an extraordinary outlier success. Though a sufficiently
| detailed model could account for it.
|
| 1. Yochai Benkler has done much more thorough analysis of
| win/loss factors. See e.g. his 2006 book:
| https://en.m.wikipedia.org/wiki/The_Wealth_of_Networks
| hgomersall wrote:
| In terms of data, OSM is so far ahead of Google maps in my
| experience. The rendering is much better too. What's not there
| is obvious and easy to use tooling that anyone can interact
| with. I mean, there might be, but I don't know about it.
| aidenn0 wrote:
| Fairly regularly an address I'm searching for just won't be
| in OSM, but it is in Google. This happens often enough to be
| a well-known issue.
| unethical_ban wrote:
| Is there a recommendation for OSM on mobile? IIRC they don't
| have an official app.
|
| Also looking at their bike routing - it gives me an idea.
| Road should be rated on whether they have a dedicated bike
| lane and on the danger of riding on said road at particular
| times of day. I just input a src/dest and it gave me a really
| busy road with tons of "paperboy" level risky side roads on
| it. I would never want someone to take that route at 5pm on a
| weekday.
| digging wrote:
| Magic Earth might be the best, but it's honestly pretty
| clunky compared to Apple or Google maps
| Karrot_Kream wrote:
| OSM is fundamentally just a DB for place locations and
| geometries. Directions use routing engines which choose
| roads and paths between locations based on constraints. The
| main landing page for OSM lets you choose between OSM,
| Grasshopper, and the Valhalla routing engines.
|
| To figure out why directions are bad you need to see which
| criteria the routing engine is using to create the route
| and decide either to change the constraints used to
| generate the bike route or what added data you need to
| place on the streets for the routing engine to avoid/prefer
| certain streets.
|
| Does this sound like an opaque nightmare? Yes. That's why
| very few people use it. Apple has been doing some great
| work doing mapping and adding it into the OSM DB, which
| they use for their own maps, but they have their own
| proprietary routing system for directions. If you're
| looking for a good app to use just OSM data, I use OSMAnd
| for Android. I still prefer Google Maps because their
| routing and geocoding tend to be much better for urban
| areas but for hikes and country bike rides, OSM tends to
| outperform GMaps.
| criddell wrote:
| I just looked at OSM for the first time and for my
| neighborhood it's much worse than Google and Apple. It
| doesn't have satellite or street view data.
| ryukafalz wrote:
| OSM is a database of map data (streets/buildings/etc), so
| satellite and street view imagery is outside of its scope.
| Individual map applications that _use_ OSM data might also
| support satellite imagery (and some do, like OSMAnd).
| rretet5555 wrote:
| The completeness and quality of OSM depends on the local
| community, and it varies greatly depending on where you live
| and use it.
| digging wrote:
| I don't have google maps on my phone at all unless I visit in
| the browser, and I use OSM through Magic Earth. I wouldn't go
| back, but it is a huge pain and sometimes I do have to just
| open google maps in a browser window. It doesn't usually have
| hours of operation, doesn't usually have links to websites.
| It can't find businesses by name easily (it often seems to
| require the exact name to by typed in), and it definitely
| can't find businesses by service (searching for "sandwiches"
| will not show you a list of local sandwich shops, it will do
| something like teleport you to a street called "Sandwiches"
| in Ireland). And even if I have the exact address, I will
| still sometimes end of thousands of miles away or with no
| hits because the street name was written differently.
| Honestly, it's of very little use to me because it can rarely
| take me to a new place.
| btilly wrote:
| My experience is the opposite.
|
| People in the real world care about things like hours of
| operation. Google makes it really easy for businesses to keep
| them up to date on things like holiday closures. OSM makes it
| a nightmare.
| progval wrote:
| > OSM makes it a nightmare.
|
| While the generic interface is pretty bad (you have to edit
| the machine-readable values), StreetComplete provides a
| very nice UI
| digging wrote:
| Using a second app to perform a function in the primary
| app is a non-starter for >99% of people who don't already
| use OSM
| btilly wrote:
| A nice UI is completely and utterly useless for a
| business attempting to create an automated workflow from
| a spreadsheet for things like business hour updates and
| letting map publishers know when new stores are going to
| open.
|
| So yeah, OSM is a nightmare for businesses to deal with.
| And unless that changes, its access to business
| information that people expect will remain severely
| limited.
| vanattab wrote:
| How do they make it a nightmare? Are we sure it's not just
| that 96% of business owners use Google maps or maybe Apple
| maps and don't even know what OpenStreetMaps exists. I
| think this is more about network effects then anything. If
| they really want to break googles geo spacial business data
| monopoly. I think if Apple/Microsoft/OSM should band
| together and make a simple tool for business owners that
| can update your details on Google, Bing, Apple Maps, and
| osm simultaneously. Although I am not sure if Google
| exposes that through apis or not.
| kpw94 wrote:
| For starter, as a business owner, how do you claim full
| ownership of a given business on OSM?
|
| What prevents a nasty competitor from making daily false
| updates to your opening hours?
|
| If you're a verified business owner in a non-
| collaborative platform, you can update your holiday
| hours/one-off closure with a simple edit on that
| platform's business management page/API. How is OSM even
| in same category as Apple maps/bing/Google maps?
|
| Examples:
|
| - https://businessconnect.apple.com/
|
| - https://www.bingplaces.com/
|
| - https://business.google.com/
| btilly wrote:
| I am very sure that OSM does not get this information
| because they make it hard for businesses to give it. I
| know this because figuring out how to get that
| information published was my job a few years ago.
|
| Specifically I was a developer for a company whose job
| was to update business information in Google Maps, Apple,
| Facebook and so on. We'd get the data from companies like
| Cheesecake Factory, Walmart and Trader Joe's, then we
| would update all of the sites for them.
|
| All of the sites have some sort of API or upload
| mechanism that makes it easy to do things like publish
| phone numbers, hours of operation, hours for specific
| departments and so on. All of them were happy to let us
| automate it. All were happy to accept data based on
| street addresses.
|
| I tried to make it work for OSM. It was a disaster. I
| have an address. Google et al understand that a street
| often has multiple names. If the address I was given
| named the street something else, Google took care of
| understanding that route 33 is also such and so street
| and they accepted the data. If I said that there was a
| restaurant inside of a mall, Google didn't insist that I
| know more than that. If I was publishing holiday hours,
| Google accepted us as the default authority. (And gave
| ways of resolving it if someone else disagreed.)
|
| OSM did NONE of that. It was all roadblocks. If I didn't
| have the One True Name that OSM in its wisdom determined
| was right, good luck matching on address. If I couldn't
| provide OSM with the outline of the restaurant on the
| floor plan, OSM had no way to accept that there was a
| restaurant in the mall. If a random OSM contributor had
| gone to the location and posted store hours, OSM refused
| to accept my claim of its reduced hours on Christmas Day.
| And so on.
|
| All of the brands that I named and more don't publish to
| OSM for one reason, and one reason only. OSM make it
| impossible for businesses to work with them in any useful
| way to provide that information. And therefore OSM is not
| on the list of sites that that data gets published to.
|
| In short, if it isn't perfect, OSM doesn't want your
| data. And the data off of a spreadsheet some business
| uses to manage this stuff usually is nothing like
| perfect. I respect how much work went into getting OSM
| just right. But they made it impossible for real
| businesses to work with them, and so they don't get that
| business data.
| Ajedi32 wrote:
| What if instead of Microsoft abandoning their investment they'd
| invested directly in OpenStreetMap? Because that seems more
| analogous to the course of action the article is recommending.
| BiteCode_dev wrote:
| Agreed, even the best open source projects, like Linux or
| Firefox, in their wonderful success, didn't render proprietary
| competition unable to have there piece of the market share.
|
| And even in markets with very dominant free offers like video
| consumption, programming languages or VCS, you can still make
| tons of money by providing a service around it. E.G: github,
| netflix, etc.
|
| OpenAI has a good product, a good team, a good brand and a good
| moving speed.
|
| Selling them short is a bit premature.
| [deleted]
| lanza wrote:
| I mean... your argument is structurally the same as his. "I
| once saw X happen and thus X will happen again."
| Krasnol wrote:
| > Of course it's more than a decade later now and I still use
| Google Maps, Bing Maps still suck, and the view times I've
| tried OpenStreetMaps I've found it far behind both.
|
| The sheer size of the OSM project is staggering. Putting it
| next to Wikipedia, where missing content at some point wouldn't
| cause much fuss, makes it a bad example.
|
| Besides that, your limited knowledge of the popularity of OSM
| gives you a wrong picture. OSM is already the base for popular
| businesses. Like Strava for example. TomTom is on board with
| it. Meta for longer with their AI tool, same as Microsoft. In
| some regions of the world where the community is very active,
| it IS better than Google Maps. Germany for example where I
| live. In many regions of the world, it is the superior map
| model for cycling or nature activities in general. Sometimes
| less civilised areas of the world have better coverage too
| because Google doesn't care about those regions. See parts of
| Africa or weird countries like North Korea.
|
| One should also not forget the Humanitarian OpenStreetMap Team
| which provides humanitarian mapping in areas Google didn't
| care. You can help out too. It's quite easy:
| https://www.hotosm.org/
|
| > What's more every company I've worked at since has paid
| Google for access to their Maps API.
|
| Many others have switched away after google lifted their
| prices. They'll lose the race here too. A simple donation of
| up-to-date world satellite imaginary would already be enough
| for an even faster grow.
| selimthegrim wrote:
| I think ex YU states and former Soviet bloc also really shine
| in OSM, as well as areas along PRC border where regime forces
| map jitter (see HK/PRC border road junctions for example)
| 123pie123 wrote:
| I think a lot of people use one type of mapping application
| that doesn't seem to work for them and then say OSM is not
| great.
|
| I've had to try a fair few mapping applications that works for
| me (I can recommend Organic Maps on android)
|
| OSM map data easy exeeds Google map data, the only time I do
| use google maps is for street view images and satalite info.
|
| Bing is good in the UK because that has Ordnance survey maps -
| OS mapping data is generally better than OSM (for what I need
| it for)
| kpw94 wrote:
| The higher up failed to see the difference in "users", as well
| as use cases.
|
| In Wikipedia, the user is same as the content creator: the
| general public, with a subset of it contributing to the
| Wikipedia content.
|
| In OpenStreetMaps, one category of users are also creators:
| general public needs a "map" product, and a subset of them like
| contributing to the content.
|
| But there's another category of users: businesses, who keep
| their hours/contact/reviews updated. OpenStreetMap doesn't have
| a nice UX for them.
|
| As for use cases: underlying map data sure, but one needs
| strong navigation features, "turn right after the Starbucks",
| up-to-date traffic data.
|
| This all makes it so different from Wikipedia vs Encarta.
| dtech wrote:
| OSM is quite popular through commercial providers, mainly
| Mapbox. Why you're not using it daily is because there's no
| concentrated effort to make a consumer-friendly product from
| it, like Wikipedia mostly is for Encyclopedia. Too early to
| tell what will be the case for LLM.
| badpun wrote:
| > Bing Maps
|
| TIL
| LesZedCB wrote:
| what this proves to me without a doubt is that silo'd and
| proprietary iteration i still very clearly _also_ a massive
| disadvantage. i really hope companies internalize that. if they
| just keep scooping up and hiding open-source improvements they
| very well may still be left behind.
|
| the final quote from the doc:
|
| > And in the end, OpenAI doesn't matter. They are making the same
| mistakes we are in their posture relative to open source, and
| their ability to maintain an edge is necessarily in question.
| Open source alternatives can and will eventually eclipse them
| unless they change their stance. In this respect, at least, we
| can make the first move.
| picometer wrote:
| "Some of the most interesting questions about CAS [Complex
| Adaptive Systems] have to do with their relations to one another.
| We know that such systems have a tendency to spawn others. Thus
| biological evolution gave rise to thinking, including human
| thought, and to mammalian immune systems; human thought gave rise
| to computer-based CAS; and so on."
|
| - Murray Gell Mann, "Complex Adaptive Systems"
| shmerl wrote:
| In that context, OpenAI would be more fitting to be called
| ClosedAI.
| beardyw wrote:
| This is such an interesting read. It makes a compelling case,
| though how the likes of Google should react feels less like an
| adjustment and more like a revolution.
| prakhar897 wrote:
| > "We have no moat, and neither does OpenAI"
|
| and neither does Coca Cola and Cadbury. Yet biggest monopolies
| are found in these places. Because the competitors will not be
| differentiated enough for users to switch from the incumbent.
|
| But G-AI is still nascent and there's lots of improvements to be
| had. I suspect better tech is a moat but ofcourse Google is
| oblivious to it.
| csallen wrote:
| Brand loyalty _is_ a moat. So I wouldn 't say that Coca-Cola
| doesn't have a moat. In addition, economies of scale allow them
| to produce more cheaply + advertise more + distribute wider
| than competitors. Compare Coca-Cola to some beverage company I
| start tomorrow:
|
| - Nobody's tasted my beverage, therefore nobody is craving its
| taste. Whereas billions of people are "addicted" to coke: they
| know what it tastes like and miss it when it's gone.
|
| - Nobody's ever heard of my business. I have zero trust or
| loyalty. Whereas people have trusted code for a century, and
| actually consider themselves loyal to that company over others
| with similar goods.
|
| - I have no money to buy ads with. Coke is running Super Bowl
| commercials.
|
| - I have no distribution partnerships. Coke is in every vending
| machine and every restaurant. They've spread to almost every
| country, and even differentiated the taste to appeal to local
| taste buds.
| oars wrote:
| Leaked document. What a document.
| summerlight wrote:
| This looks like a personal manifesto from an engineer who doesn't
| even attempt to write it on behalf of Google? The title is
| significantly misleading.
| opportune wrote:
| 99% of media coverage like "Tech employee/company says
| <provocative or controversial thing>" are exactly like that.
| capableweb wrote:
| Agree, misleading title. The introduction makes the context
| clear, but probably too late to not call the article click-
| bait.
|
| > [...] It originates from a researcher within Google. [...]
| The document is only the opinion of a Google employee, not the
| entire firm. [...]
| dpflan wrote:
| Completely agree. It is interesting, but the gravitas of it
| seems lower than of course if an executive said this and
| corroborated it. I do feel that opensource for AI is going to
| be really interesting and shake things up.
| ghaff wrote:
| And (probably) through no fault of their own they'll get
| totally thrown under the bus for this--whether directly but
| when raises/promotions come around or not.
| ljlolel wrote:
| This reads like a psy-op "leak" to try to convince OpenAI execs
| to open source GPT4 weights
| uptownfunk wrote:
| OpenAI is further along than most of us are aware.
|
| The ability to connect these models to the web, to pipe up API
| access to different services and equip LLMs to be the new
| interface to these services and to the worlds information is the
| real game changer.
|
| Google cannot out innovate them because they are a big Corp rife
| with googly politics and challenges of overhead that come with
| organizational scale.
|
| I would be curious to see if there are plans to spin off the
| newly consolidated AI unit with their own PnL to stimulate that
| hunger to grow and survive and then capitalize them accordingly.
| Otherwise they are en route to die a slow death once better
| companies come along.
| lhl wrote:
| I think from the perspective of a Google researcher/engineer, it
| must be alarming to see the crazy explosion going on w/ LLM
| development. We've gone from just one or two weirdos implementing
| papers (eg https://github.com/lucidrains?tab=repositories who's
| amazing) to now an explosion where basically every dev and PhD
| student is hacking on neat new things and having a field day and
| "lapping" (eg productizing) what Google Research was previously
| holding back.
|
| And we're also seeing amazing fine-tunes/distillations of very
| useful/capable smaller models - there's no denying that things
| have gotten better and more importantly, cheaper way faster than
| anyone expected. That being said, most of these are being trained
| with the help of GPT-4, and so far nothing I've seen being done
| publicly (and I've been spending a lot of time tracking these
| https://docs.google.com/spreadsheets/d/1kT4or6b0Fedd-W_jMwYp...)
| gets close in quality/capabilities to GPT-4.
|
| I'm always rooting for the open source camp, but I think the
| flip-side is that there are still only a handful of organizations
| in the world that can train a >SoTA foundational model, and that
| having a mega-model is probably a huge force multiplier if you
| know how to take advantage of it (eg, I can't imagine that OpenAI
| has been able to release software at the pace they have been
| without leveraging GPT-4 for co-development; also can you distill
| or develop capable smaller models without a more capable
| foundational model to leverage?). Anthropic for example has
| recently taken the flip side of the "no moat" argument, arguing
| that there is a potential winner-take-all scenario where the lead
| may become insurmountable if one group gets too far ahead in the
| next couple years. I guess what we'll just have to see, but my
| suspicion, is that the crux to the "moat" question is going to be
| whether the open source approach can actually train a GPT-n++
| system.
| tehjoker wrote:
| This is likely the reason for the propaganda push about delaying
| AI research 6 months, which makes no sense for the stated reasons
| (it's far too short even if you take the scare tactic seriously).
| However, it may be enough time to delay the competition and
| consolidate product lines.
| aresant wrote:
| "People will not pay for a restricted model when free,
| unrestricted alternatives are comparable in quality. . ."
|
| I'll take the opposite side of that bet - MSFT / Goog / etc in
| the providers side will drive record revenues on the back of
| closed / restricted models:
|
| 1 - Table stakes for buying software at enterprise level is
| permissions based management & standardized security / hardening.
|
| 2 - The corporate world is also the highest value spender of
| software
|
| 3 - Corp world will find the "proprietary trained models" on top
| of vanilla MSFT OpenAI or Goog Bard pitch absolutely irresistible
| - creates a great story about moats / compounding advantages etc.
| And the outcome is going to most likely be higher switching costs
| to leave MSFT for a new upstart etc
| paxys wrote:
| > The document is only the opinion of a Google employee, not the
| entire firm
|
| The title makes it seem like this is some official Google memo.
| The company has 150K employees and 300K different opinions on
| things. Can't go chasing down each one and giving it importance.
| jdelman wrote:
| While this post champions the progress made by OSS, it also
| mentions that a huge leap came from Meta releasing Llama. Would
| the rapid gains in OSS AI have came as quickly without that? Did
| Meta strategically release Llama knowing it would destroy Google
| & OpenAI's moats?
| mlboss wrote:
| I think it would have been some other model if not Meta.
| Stablility AI also released a OSS model, Cerebras released
| another.
| phyllistine wrote:
| [dead]
| vlaaad wrote:
| This looks very fake to me. I might be wrong. Yet, there is no
| "document" that was leaked, the original source is some blog
| post. If there is a document, share the document. Shared by
| "anonymous individual on discord who granted permission for
| republication"... I don't know. If it was shared by anonymous,
| why ask for permission? Which discord server?
| lysecret wrote:
| So I use ChatGPT every day. I like it a lot and it is useful but
| it is overhyped. Also from 3.5 to 4 the jump was nice but seemed
| relatively marginal to me.
|
| I think the head start OpenAi has will vanish. Iteration will be
| slow and painful giving google or whoever more than enough time
| to catch up.
|
| ChatGPT was a fantastic leap getting us say 80% to Agi but as we
| have seen time and time again the last 20% are excruciatingly
| slow and painful (see Self driving cars).
| whimsicalism wrote:
| % of what lol
| jimsimmons wrote:
| Then it's not 20% then
| annoyingnoob wrote:
| I think this person is referring to the 80/20 rule. Here are
| a few examples:
|
| 20% of a plant contains 80% of the fruit
|
| 80% of a company's profits come from 20% of customers
|
| 20% of players result in 80% of points scored
|
| I've heard this stated as you can complete 80% of a project
| with 20% of the effort, and the last 20% of completeness will
| require 80% of the effort.
| UncleEntity wrote:
| The Pareto principle...
| com2kid wrote:
| > So I use ChatGPT every day. I like it a lot and it is useful
| but it is overhyped.
|
| It is incorrectly hyped. The vision most pundits have is
| horribly wrong. It is like people who thought librarians would
| be out of work because of ebooks, barking up the wrong tree.
|
| ChatGPT does amazing things, but it is also prone to errors,
| but so are people! So what, people still get things done.
|
| Imaging feeding ChatGPT an API for smart lights, a description
| of your house, and then asking it to turn on the lights in your
| living room. You wouldn't have to name the lights "living
| room", because Chat GPT knows what the hell a living room is.
|
| Meanwhile, if I'm in my car, and I ask my phone to open
| Spotify, it will occasionally open Spotify _on my TV back
| home_. Admittedly it hasn 't done for quite some time, I
| presume it may have been a bug Google fixed, but that bug only
| exists because Google Assistant is, well, not smart.
|
| Here is an app you could build right now with ChatGPT:
|
| 1. Animatronics with voice boxes, expose an API with a large
| library of pre-canned movements and feed the API docs to
| ChatGPT
|
| 2. Ask ChatGPT to write a story, complete with animations and
| poses for each character.
|
| 3. Have ChatGPT emit code with API calls and timing for each
| character
|
| 4. Feed each character's lines through one of the new
| generation of TTS services, and once generation is done, have
| the play performed.
|
| Nothing else exists that can automate things to that extent. A
| specialized model could do some of it, but not all of it. Maybe
| in the near future you can chain models together, but right now
| ChatGPT does it all, and it does it _really_ well.
|
| And ChatGPT does all sorts of cool things like that, mixing
| together natural language with machine parsable output (JSON,
| XML, or create your own format as needed!)
| moffkalast wrote:
| I also felt this way initially, like "that's it?". But overall
| the massive reduction in hallucinations and increase in general
| accuracy makes it almost reliable. Math is correct, it follows
| all commands far more closely, can continue when it's cut off
| by the reply limit, etc.
|
| Then I tried it for writing code. Let's just say I no longer
| write code, I just fine tune what it writes for me.
| Tostino wrote:
| Personally, the difference between GPT4 and 3.5 is, pretty
| immense for what I am using it for. I can use GPT 3.5 for
| things like summarization tasks (as long as the text isn't too
| complex), reformatting, and other transformation type tasks
| alright. I don't even bother with using it for logical or
| programming tasks though.
| killthebuddha wrote:
| One way that I've been framing this in my head (and in an
| application I'm building) is that gpt-3 will be useful for
| analytic tasks but gpt-4 will be required for synthetic
| tasks. I'm using "analytic" and "synthetic" in the same way
| as in this writeup
| https://github.com/williamcotton/empirical-
| philosophy/blob/m...
| crazyedgar wrote:
| This is my experience too. While I'd really love the Open
| Source models to catch up, currently they struggle even with
| dead-simple summarization tasks: they hallucinate too much,
| or omit essential points. ChatGPT don't often hallucinate
| when summarizing, only when answering questions.
| burnished wrote:
| Would you please be more explicit? I'm curious about the
| relative strength's and weaknesses other's see
| Tostino wrote:
| I can use GPT 4 for to work through problems that I have
| not actually figured out previously by talking to co-
| workers who work in my industry. I need to feed it contacts
| for my industry explicitly within the prompt and ensure
| that it understands and doesn't hallucinate its answers.
| However, that doesn't mean it's not useful, it just means
| you need to you understand the limitations.
| burnished wrote:
| I don't think I understand the process you are describing
| because it lowkey sounds like you are giving it
| information about your peers and using that as a basis to
| ask questions of chatGPT but get the benefit of the real
| people's perspectives?
|
| Also I agree it can be super useful, its just that my own
| use of it is very limited (basically as the research AI I
| always wanted), so I am trying to broaden my perspective
| on what is possible
| SkyPuncher wrote:
| GPT feels like an upgrade from MapQuest to Garmin.
|
| Garmin was absolutely a better user experience. Less mental
| load, dynamically updating next steps, etc, etc.
|
| However, both MapQuest and Garmin still got things wrong.
| Interestingly, with Garmin, the lack of mental load meant
| people blindly followed directions. When it come something
| wrong, people would do really stupid stuff.
| beepbooptheory wrote:
| Perhaps something that gets the bulk of its value from the
| retroactive "participation" of every single person in the world
| who has written text for one public or another is just not meant
| to be monetized. Beyond even ethical maxims, that is, perhaps its
| simply not compatible in its very nature with capitalistic
| enterprise. I know this is probably naive, but it would be a
| beautiful outcome to me.
| skybrian wrote:
| This gets attention due to being a leak, but it's still just one
| Googler's opinion and it has signs of being overstated for
| rhetorical effect.
|
| In particular, demos aren't the same as products. Running a demo
| on one person's phone is an important milestone, but if the
| device overheats and/or gets throttled then it's not really
| something you'd want to run on your phone.
|
| It's easy to claim that a problem is "solved" with a link to a
| demo when actually there's more to do. People can link to
| projects they didn't actually investigate. They can claim
| "parity" because they tried one thing and were impressed.
| Figuring out if something works well takes more effort. Could you
| write a product review, or did you just hear about it, or try it
| once?
|
| I haven't investigated most projects either so I don't know, but
| consider that things may not be moving quite as fast as demo-
| based hype indicates.
| Animats wrote:
| It comes across as something from an open source enthusiast
| outside Google. Note the complete lack of references to
| monetization. Also, there's no sense of how this fits with
| other Google products. Given a chat engine, what do you do with
| it? Integrate it with search? With Gmail? With Google Docs?
| LLMs by themselves are fun, but their use will be as components
| of larger systems.
| skybrian wrote:
| Yeah, but there are open source enthusiasts inside Google,
| too. People don't necessarily change their opinions much when
| they start working at Google.
| vlaaad wrote:
| This looks very fake to me. I might be wrong. Yet, there is no
| "document" that was leaked, the original source is some blog
| post. If there is a document, share the document. Shared by
| "anonymous individual on discord who granted permission for
| republication"... I don't know. If it was shared by anonymous,
| why ask for permission? Which discord server?
| simonw wrote:
| Did you read it?
|
| I honestly don't care if it's really a leak from inside Google
| or not: I think the analysis stands on its own. It's a
| genuinely insightful summary of the last few months of activity
| in open source models, and makes a very compelling argument as
| to the strategic impact those will have on the incumbent LLM
| providers.
|
| I don't think it's a leak though, purely because I have trouble
| imagining anyone writing something this good and deciding NOT
| to take credit for the analysis themselves.
| ftxbro wrote:
| > It's a genuinely insightful summary of the last few months
| of activity in open source models
|
| Yes this is an amazing summary! Just for its summary alone,
| it is probably one of the top five writings I saw on LLMs and
| I read every one!
|
| > because I have trouble imagining anyone writing something
| this good and deciding NOT to take credit for the analysis
| themselves.
|
| Not everyone has a substack that they spam onto hacker news
| every time a thought enter their head. Or imagine that INTP
| exist. In my opinion the best take ever on LLMs is the
| simulators essay https://generative.ink/posts/simulators/ and
| the author is so shy they went pseudonymous and put their
| twitter as private and don't even want their name in
| conferences.
| heliophobicdude wrote:
| I think the another great paper is RLHF article from Chip
| Huyen
|
| https://huyenchip.com/2023/05/02/rlhf.html
| ftxbro wrote:
| Thanks for sharing it but I'm sorry I don't agree that
| it's so important. In my opinion almost every interesting
| thing about LLMs comes from the raw base model, which is
| before the RLHF is applied.
|
| For example the simulators paper was written before
| ChatGPT was even released, based on research with the
| GPT-3 base model that only had text completion and no
| instruction tuning or any kind of RLHF or lobotomization.
| In another example, in the interviews with the people who
| had access to the base model of GPT-4 like the red
| teamers and the ones at microsoft who integrated it with
| bing, they consistently explain that the raw base
| pretrained model has the most raw intelligence which is
| deadened as they put RLHF and guardrails onto it.
| 16bitvoid wrote:
| Coder Radio podcast uploaded the document to the show notes for
| their latest episode[1]. The first link[2] in the PDF does link
| to some internal Google resource that requires an @google.com
| email address.
|
| 1:
| https://jblive.wufoo.com/cabinet/af096271-d358-4a25-aedf-e56...
|
| 2: http://goto.google.com/we-have-no-moat
| jsnell wrote:
| Presumably they weren't getting permission in the sense of
| "this publication is authorized by the original author, or by
| Google" but in the sense of "thanks for leaking the document;
| can we publish it more widely, or will you get into trouble?"
| Alifatisk wrote:
| What Facebook did to the community and their leaked torrent
| accelerated everything.
| QLazuli wrote:
| _puts on tinfoil hat_ They probably intentionally published this
| to raise awareness of how viable it is for individuals to
| outperform OpenAI and Meta. Google seems to be the farthest
| behind, they have the most to gain by the others losing their
| lead to individuals.
| rvz wrote:
| > The premise of the paper is that while OpenAI and Google
| continue to race to build the most powerful language models,
| their efforts are rapidly being eclipsed by the work happening in
| the open source community.
|
| Another magnificent unsurprising set of correct prediction(s) [0]
| [1] [2] and as triumphantly admitted by Google themselves on open
| source LLMs eating both of their (Google) and OpenAI's lunch.
|
| "When it is the race to the bottom, AI LLM services, like
| ChatGPT, Claude (Anthropic), Cohere.ai, etc are winning the race.
| Open source LLMs are already at the finish line."
|
| [0] https://news.ycombinator.com/item?id=34201706
|
| [1] https://news.ycombinator.com/item?id=35661548
|
| [2] https://news.ycombinator.com/item?id=34716545
| hintymad wrote:
| > They are doing things with $100 and 13B params
|
| Not that I disagree with the general belief that OSS community is
| catching up, but this specific data point is not as impactful as
| it sounds. Llama cannot be used for commercial purposes, and that
| $100 was spent on ChatGPT, which means we still depended on
| proprietary information of OpenAI.
|
| It looks to me that the OSS community needs a solid foundation
| model and a really comprehensive and huge dataset. Both require
| continuous heavy investment.
| bhickey wrote:
| https://www.together.xyz/blog/redpajama
| Garcia98 wrote:
| The author is overly optimistic with the current state of open
| source LLMs, (e.g., Koala is very far away from matching ChatGPT
| performance). However, I agree with their spirit, Google has been
| one of the most important contributors to the development of LLMs
| and until recently they've been open sharing their model weights
| under permissive licenses, they should not backtrack to closed
| source.
|
| OpenAI has a huge lead in the closed source ecosystem, Google's
| best bet is to take over the open source ecosystem and build on
| top of it, they are still not late. Llama based models don't have
| a permissive license, and a free model that is mildly superior to
| Llama could be game changing.
| MichaelRazum wrote:
| I don't buy it. It is so expensive to train LLM, so that the only
| hope is to rely on Foundation Models that are open sources by
| google, msft or facebook.
| IceHegel wrote:
| Of course, the natural next step is "But OpenAI isn't worth $1.33
| trillion."
| Otto31337 wrote:
| [dead]
| bottlelion wrote:
| OpenAI may not have a moat, but Microsoft does with their
| Enterprise Agreements.
| kccqzy wrote:
| > They are doing things with $100 and 13B params that we struggle
| with at $10M and 540B.
|
| Does this mean Bard took $10M to train and it has 540B
| parameters?
| squishylicious wrote:
| Bard is based on PaLM:
| https://ai.googleblog.com/2022/04/pathways-language-model-
| pa.... They haven't published training costs but estimates have
| been in the $10-20M range, so that seems reasonable.
| Reubend wrote:
| Great read, but I don't agree with all of these points. OpenAI's
| technological moat is not necessarily meaningful in a context
| where the average consumer is starting to recognize ChatGPT as a
| brand name.
|
| Furthermore, models which fine-tune LLMs are still dependent on
| the base model's quality. Having a much higher quality base model
| is still a competitive advantage in scenarios where
| generalizability is an important aspect of the use case.
|
| Thus far, Google has failed to integrate LLMs into their products
| in a way that adds value. But they do have advantages which could
| be used to gain a competitive lead: - Their crawling
| infrastructure could allow their to generate better training
| datasets, and update models more quickly. - Their TPU hardware
| could allow them to train and fine-tune models more quickly. -
| Their excellent research divisions could give them a head start
| with novel architectures.
|
| If Google utilizes those advantages, they could develop a moat in
| the future. OpenAI has access to great researchers, and good
| crawl data through Bing, but it seems plausible to me that 2 or 3
| companies in this space could develop sizeable moats which
| smaller competitors can't overcome.
| kevinmchugh wrote:
| I'll also mark myself as skeptical of the brand-as-moat. I
| think AskJeeves and especially Yahoo probably had more brand
| recognition just before Google took over than ChatGPT or openai
| has today.
| ealexhudson wrote:
| Consumers recognizing ChatGPT might just end up like vacuum
| cleaners; at least in the UK, people will often just call it a
| "hoover" but the likelihood of it being a Hoover is low.
|
| It is difficult to see where the moat might exist if it's not
| data and the majority of the workings are published /
| discoverable. I don't think the document identifies a readily
| working strategy to defend against the threats it recognises.
| dmoy wrote:
| > end up like vacuum cleaners
|
| The term of art is Generic Trademark
|
| https://en.m.wikipedia.org/wiki/Generic_trademark
|
| In US common law (and I'd imagine UK too), it's usually
| something companies want to avoid if at all possible.
|
| Relevant case for Google itself:
| https://www.intepat.com/blog/is-google-a-generic-trademark/
| akiselev wrote:
| See also the "Don't Say Velcro" [1] campaign from the
| eponymous hook and loop fastener company.
|
| [1] https://m.youtube.com/watch?v=rRi8LptvFZY
| Mistletoe wrote:
| This reminds me of Lego's constant campaign about "don't
| call them Legos" that was similar and it always made me
| think the Lego company is very pretentious and I avoid
| them. I don't think that was their desired effect.
|
| https://www.adrants.com/2005/09/lego-gets-pissy-about-
| brand-...
| ealexhudson wrote:
| Well, except that there's no evidence that OpenAI are using
| the name in a trademark sense, let alone registered it?
|
| Can't really genericise that which was never made
| specific...
| russellbeattie wrote:
| > _ChatGPT as a brand name_
|
| You're forgetting the phenomenon of the fast follower or second
| to market effect. Hydrox and Oreos, Newton and Palm, MySpace
| and Facebook, etc. Just because you created the market doesn't
| necessarily mean you will own it long term. Competitors often
| respond better to customer demand and are more willing to
| innovate since they have nothing to lose.
| JohnFen wrote:
| > in a context where the average consumer is starting to
| recognize ChatGPT as a brand name.
|
| That brand recognition could hurt them, though. If the
| widespread use of LLMs results in severe economic disruption
| due to unemployment, ChatGPT (and therefore OpenAI) will get
| the majority of the ire even for the effects of their
| competition.
| egonschiele wrote:
| This nicely outlines all the reasons I'm building Chisel [1].
| There are other writing apps out there, but they are closed
| source. It's not clear to me what value they are adding, as the
| biggest value add -- LLMs -- are already open to the public. It
| makes a lot more sense to me to develop an open source writing
| app, where others can pitch in and everyone can reap the
| benefits.
|
| I think it is fundamentally important to have an open source
| option. I'd love to have more people pitch in to make it better.
| One big limitation right now is, users are limited to 50k tokens
| a month, because everyone is using my API key. I'd like to move
| it to an electron app where users can put in their own API key,
| or even use a model they have set up locally.
|
| [1] https://chiseleditor.com
| [deleted]
| murtio wrote:
| I agree that both Google and OpenAI are losing the race to open-
| source in AI research. However, a more critical issue to Google
| is their struggle to compete with OpenAI in LLM-based search
| engines. Google's entire business model mostly relies on ads
| (77.6% in Q4 2022). OpenaAI is developing LLM-based products that
| people apparently love (100M users in 2 months) and seem to use
| it as search engines. This poses a greater risk to Google than
| just losing ground in research since it could ultimately lead to
| the loss of their ad-generated income.
| endisneigh wrote:
| it'll be fun to see the pikachu face when engineers are expected
| to do more, with the aid of these tools, but are not paid any
| more money.
| com2kid wrote:
| Kind of like every other improvement in technology? From
| interactive terminals, to compilers, to graphical debuggers?
|
| Nothing new there.
|
| What productivity improvements have opened up is more
| opportunities for developers. Larger and more complex systems
| can be built using better tooling.
| endisneigh wrote:
| > Larger and more complex systems can be built using better
| tooling.
|
| to what end, make rich people richer?
| com2kid wrote:
| > to what end, make rich people richer?
|
| So, in perfect theory land, people get paid because they
| provide value. That obviously breaks down at the extremes.
|
| But, for sake of example, let's take Uber, super easy to
| hate on them, but they have had a measurable impact on
| reducing deaths from drunk driving. That obviously provides
| a lot of value to people.
|
| Likewise, it is hard to overstate the value people have
| gained from smartphones, Apple has made a lot of money but
| they have also provided a lot of value. Arguments over if
| the individual value brought is long term good or bad for
| society are a separate topic, but people value their
| iPhones and therefor they pay for them. No way could
| something as complicated as an iPhone have been made with
| 1970s software engineering technology.
| endisneigh wrote:
| I'm not arguing that. I'm saying the bar is higher and
| pay relative to value has decreased for all other than at
| the upper end. Easiest way to think about this is look at
| percentage revenue paid to engineers.
| codq wrote:
| If they're able to produce twice the work in half the time,
| wouldn't it make sense to pay them less?
| photochemsyn wrote:
| In that situation it would be reasonable to expect to be paid
| twice as much while also being able to devote half the
| working day to personal/open-source projects.
| int_19h wrote:
| The nice thing about the new tools is that you can radicalize
| them by talking to them.
| joe_the_user wrote:
| It seems like everyone is so focused on LLMs are magic smartness
| machines that there isn't much analysis of them as better search
| (maybe "search synthesis"). And original search was a
| revolutionary technology, LLM as just better search are
| revolutionary.
|
| Like original search, the two application aspects are roughly
| algorithm and interface. Google years ago won by having a better
| interface, an interface that usually got things right the first
| time ( _good defaults_ are a key aspect of any successful UI).
| ChatGPT is has gotten excitement by taking a LLM and making it
| generally avoid idiocy - again, fine-tuning the interface. Google
| years ago and ChatGPT got their better results by human labor,
| human fine tuning, of a raw algorithm (In ChatGPT 's case, you
| have RLHF with workers in Kenya and elsewhere, Google has human
| search testers and years ago used DMOZ, an open source, human
| curated portal).
|
| Google's "Moat" years ago was continuing to care about quality.
| They lost this moat over the last five years imo by letting their
| search go to shit, become focused always on some product for any
| given search. This is what has made ChatGPT especially
| challenging for Google (it would be amazing still but someone
| comparing to Google ten years ago could see ways Google was
| better, present day Google has little over ChatGPT as UI. If
| Google had kept their query features as they added AI features,
| they'd have a tool that could claim virtues through still not as
| good).
|
| And this isn't even considering of updating a model and the
| question of how the model will be monetized.
| seydor wrote:
| Google search seems to optimize for "What?" (... is the best
| phone) and the list of results allows some variation, while GPT
| chats seem to answer "How?" , and tend to give the same
| average, stereotypical answer every time you ask.
|
| Maybe google has an advantage because it can answer "What?"
| with ads, but i haven't used chatGPT for any product searches
| yet
| api wrote:
| This has been my speculation about the people pushing for
| regulation in this space: it's an attempt at regulatory capture
| because there really is little moat with this tech.
|
| I can already run GPT-3 comparable models on a MacBook Pro. GPT-4
| level models that can run on at least higher end commodity
| hardware seem close.
|
| Models trained on data scraped from the net may not be defensible
| via copyright and they certainly are not patentable. It also
| seems possible to "pirate" models by training a model on another
| model. Defending against this or even detecting it would be as
| hard as preventing web scraping.
|
| Lastly the adaptive nature of the tech makes it hard to achieve
| lock in via API compatibility. Just tell the model to talk a
| different way. The rigidity of classical von Neumann computing
| that facilitates lock in just isn't there.
|
| So that leaves the old fashioned way: frighten and bribe the
| government into creating onerous regulations that you can comply
| with but upstarts cannot. Or worse make the tech require a permit
| that is expensive and difficult to obtain.
| a-user-you-like wrote:
| Act like a socialist and then blame it on capitalism, American
| playbook 101
| mark_l_watson wrote:
| I tend to agree. For now the OpenAI APIs are so very easy to use
| and effective. I do try to occasionally use HF models, mostly
| running locally in order to keep my options open.
|
| My bet is that almost everyone wants to keep their options open.
|
| I am very much into auxiliary tools like LangChain and
| LlamaIndex, the topic of my last book, but I also like building
| up my own tools from scratch (mostly in Common Lisp and Swift for
| now), and I bet most devs and companies are doing the same.
| EGreg wrote:
| Wow, an open source gift economy beating the closed-source
| capitalistic model? You don't say.
|
| Wikipedia handily beat Britannica (the most well-known and
| prestigious encyclopedia, sold door to door) and Encarta
| (supported by Microsoft)
|
| The Web beat AOL, CompuServe, MSN, newspapers, magazines, radio
| and TV stations, etc.
|
| Linux beat closed source competitors on tons of environments
|
| Apache and NGinX beat Microsoft Internet Information Server and
| whatever else proprietary servers.
|
| About the only place it doesn't beat, is consumer-facing
| frontends. Because open-source does take skill to use and
| maintain. But that's why the second layer (sysadmins, etc.) have
| chosen it.
| ZFH wrote:
| "I have no moat, and I must scream"
| geepytee wrote:
| A lot of good points made here, thank you for sharing!
| [deleted]
| hello_computer wrote:
| I think YouTube is a damn fine moat.
| huijzer wrote:
| As many point out in this thread, there are very valid counter
| arguments against the ideas presented in this memo.
|
| This "AI war" starts to look like Russian vs. American "leaks".
| Any time something leaks, you have basically no information
| because it could be true, it could be false, or it could be false
| with some truth sprinkled in.
| telmop wrote:
| Does this mean Google will be releasing OSS LLMs? They could
| justify it as "commoditizing your competitors business".
| dragonwriter wrote:
| > Does this mean Google will be releasing OSS LLMs? They could
| justify it as "commoditizing your competitors business".
|
| That's what this piece _argues for_. I predict it will not be
| reflected in Google's strategy in the next, say, six months, or
| morw to the point until and unless the apparent "Stable
| Diffusion" moment in LLMs becomes harder to ignore, such as via
| sustained publicity on concrete commercially significant non-
| demonstration /non-research use.
| shanebellone wrote:
| Moat == War Chest
| kyaghmour wrote:
| Google's moat is its data set. Imagine training an generative AI
| LLM on the entire set of YouTube training videos. No one else has
| this.
| knoxa2511 wrote:
| I'm always shocked by how many people don't view branding as a
| moat.
| OscarTheGrinch wrote:
| Pepsi is catching up to us in terms of inserting sugar into
| water.
|
| WE HAVE NO MOAT!
| aabajian wrote:
| I don't know if I agree with the article. I recall when Google
| IPO'ed, nobody outside of Google really knew how much traffic
| they had and _how much money they were making._ Microsoft was
| caught off-guard. Compare this to ChatGPT: My friends, parents,
| grandparents, and coworkers (in the hospital) use ChatGPT. None
| of these people know how to adapt an open source model to their
| own use. I bet ChatGPT is vastly ahead in terms of capturing the
| market, and just hasn 't told anyone just how far. Note that they
| have grown faster in traffic than Instagram and TikTok, and they
| are used across the demographics spectrum. They released
| something to the world that astounded the average joe, and that
| is the train that people will ride.
| hospitalJail wrote:
| I find it strange people are saying facebook's leak was the
| 'Stable Diffusion' moment for LLMs. The license is awful and
| basically means it can't be used in anything involving money
| legally.
|
| Facebook has a terrible reputation, and if they can open source
| their model, it would transform their reputation at least among
| techies.
|
| https://github.com/facebookresearch/llama/pull/184
| hatsix wrote:
| The author's timeline makes it clear that they feel it was a
| catalyst. They're separating out "Stable Diffusion" the
| software from the "Stable Diffusion" moment.
|
| The community has created their own replacement for LLaMA
| (Cerebras) with none of the encumberance. Even if LLaMA is
| deleted tomorrow, the LLaMA Leak will still be a moment when
| the direction dramatically shifted.
|
| The "people" are not talking about the future of where this
| software is going. They're talking about a historical event,
| though it was recent enough that I remember what I ate for
| lunch that day.
| oiejrlskjadf wrote:
| > Facebook has a terrible reputation, and if they can open
| source their model, it would transform their reputation at
| least among techies.
|
| Have you ever heard of PyTorch? React? Jest? Docusaurus?
|
| If none of those changed their reputation among "techies" I
| doubt awesome contribution open source project X + 1 would.
| cldellow wrote:
| I think the spirit of the Stable Diffusion moment comment is
| that there is a ton of work blossoming around LLMs, largely
| because there's a good base model that is now available.
|
| And that's undeniable, IMO -- llama.cpp, vicuna are some really
| prominent examples. People are running language models on
| Raspberry Pis and smartphones. Anyone who wants to tinker can.
|
| Now, all the stuff that's built on top of LLaMa is currently
| encumbered, yes.
|
| But all of that work can likely be transferred to an
| unencumbered base model pretty easily. The existence of the
| ecosystem around LLaMa makes it much more likely that someone
| will create an unencumbered base model. And it seems like that
| is already happening, for example, the Red Pajama folks are
| working on this.
| hospitalJail wrote:
| I dont know why you are downvoted. This is mostly correct.
| tiniuclx wrote:
| I've been using Stable Diffusion to generate cover images for the
| music I release & produce for others. It's a massive time saver
| compared to comping together the release art using image editing
| software, and a lot cheaper than working with artists, which just
| doesn't make sense financially as an independent musician.
|
| It's a little bit difficult to get what you want out of the
| models, but I find them very useful! And while the output
| resolution might be quite low, things are improving & AI
| upscaling also helps a lot.
| benjaminsky2 wrote:
| > artist whose domain has not yet been disrupted by AI fires
| artist in favor of AI
| tiniuclx wrote:
| I'm already using AI to make my music production process more
| efficient! Namely, I'm using a program called Sononym which
| listens to my tens of thousands of audio samples and lets you
| search by audio similarity through the entire library, as
| well as sort by various sonic qualities.
|
| I think I'd still go for a human artist for a bigger release
| such as an album! It's a lot less hassle than sorting through
| (often rubbish) AI output & engineering your prompts, though
| it does cost PSPSPS which is the main thing making it
| prohibitive for single releases.
| glitcher wrote:
| > artist who can't afford to iterate his cover art ideas
| multiple times with a professional finds a creative solution
| echelon wrote:
| Everyone is getting disrupted by AI sooner or later.
|
| The trick is to use AI to do things it would take you five
| lifetimes to learn. It's a tool to lower opportunity cost,
| financial capital, and human capital. That gives anyone
| leveraging it a much bigger platform, and the ability to
| dream big without resources.
|
| If you can become your own "studio", you're the indie artist
| of the future. You don't need Disney or Universal Music
| backing.
|
| Anyone can step up and do this. The artists being threatened
| can use these tools to do more than they've ever done by
| themselves.
| JohnFen wrote:
| I don't think that will do a whole lot to protect you from
| the economic harm. If everyone is producing more, the value
| of the works are reduced. At best, nobody will will make
| more money, they'll just be working harder to stay at the
| same place. More likely, there will simply be no room in
| the market for as many people and most will be out of work.
| mlboss wrote:
| I disagree. Youtube model has shown that multiple people
| can produce videos and still earn profit from it. There
| are thousands of niches that creators can target which
| big studios don't even touch because masses might not be
| interested in it.
|
| We can a Big Bang without all the stupid romantic stuff.
| We can have different ending versions of Game of Thrones.
| So much stuff is never made because it takes so resources
| to produce them.
|
| I think the market will only grow when this technology is
| available to everybody.
| nebula8804 wrote:
| In the music industry that appears to have been the case
| since iTunes hit the scene. The ease of distribution has
| enabled countless artists that nobody has ever heard of
| and will never listen to. Yet some have risen up and
| become hits despite this.
| jprete wrote:
| The problem isn't capabilities, it's having a market that's
| saturated with supply twice over - once by the ability to
| make infinite copies of the product, the other where
| there's an infinite supply of distinct high-quality
| products.
|
| Subcultures used to provide a counterbalancing force here,
| but they aren't doing so well these days.
| echelon wrote:
| My interests _still_ are not being catered to.
|
| I watch films and media, listen to music, and I'm only
| truly fully satisfied a single digit number of times a
| year. That's a consequence of not enough being created
| and experimented with.
|
| The long tail is longer than you can imagine, and that's
| what form fits to your personal interest graph.
| joenot443 wrote:
| And the rest of the world was better off for it.
|
| If we'd prevented new technologies from influencing our
| artwork, our paintings would never have left the cave wall.
| I'm a musician with live published albums as well; if there
| comes a time when I think AI will help with my creative
| process, you can bet that I'll be using it.
| coolspot wrote:
| > And the rest of the world was better off for it.
|
| Except the single mom in a studio apartment trying to get
| some pay from her art gigs.
| ipaddr wrote:
| Are single mom's a special class we should treat
| differently from others? You have single fathers..
| childless couples, singles, parents with kids who have a
| disability, healthcare workers, transgendered singles,
| frail elders, mute single males..
|
| Who should you protect?
| lkbm wrote:
| "I think we should ban ATMs, online banking, and direct
| deposit so I can get work as a bank teller" said no one
| ever. (Well, maybe someone when these were new.)
|
| Displaced workers need support to ensure they can weather
| these transitions, but it doesn't make sense to
| artificially create demand by fighting new conveniences.
| If we want to ensure people have money, the solution is
| to give them money, not give them money in exchange for
| busywork.
| thegrimmest wrote:
| This line of thinking was shared by the original group
| who called themselves luddites.
| 0x457 wrote:
| Jobs come and go all the time. No one is special.
| simonw wrote:
| Posted a few notes on this here:
| https://simonwillison.net/2023/May/4/no-moat/
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