[HN Gopher] GPT4 and the Multi-Modal, Multi-Model, Multi-Everyth...
___________________________________________________________________
GPT4 and the Multi-Modal, Multi-Model, Multi-Everything Future of
AGI
Author : swyx
Score : 109 points
Date : 2023-03-15 18:07 UTC (4 hours ago)
(HTM) web link (lspace.swyx.io)
(TXT) w3m dump (lspace.swyx.io)
| ren_engineer wrote:
| how hard is it to "update" an LLM like GPT-4 with recent data
| instead of being frozen in time at the training date? Obviously
| you could use the increased context size to work around this, but
| being able to augment the base model seems like it would be the
| ideal use case for many high value projects like a version of
| Copilot that knows a company's entire code base and knows about
| newer libraries and updates
| swyx wrote:
| GPT has finetuning apis which you can use to update, but i
| think the massive context size is meant to show us you wont
| really need it most of the time. 25k words is really a lot of
| context. in the demo @gdb just dumped in the entire discord
| docs without breaking a sweat
| ldjkfkdsjnv wrote:
| I cant imagine what will happen when they add video. Right now
| its extremely expensive, but its definitely coming. All of
| youtube, all of the text on the internet, all pictures, consumed
| by some huge AI model. Who knows what it could learn from the
| movements, speech, etc in video
| jeron wrote:
| it will have the ability to create infinite irresistible
| clickbait and become the most subscribed youtube channel of all
| time
| throwaway4233 wrote:
| That will require it to be trained every day on new human
| content generated content so that it can create variations of
| it. Even then the fad would not last as long as it does
| today, since it would become possible for a larger section of
| the population to generate videos of the same kind.
| salad-tycoon wrote:
| Haven't seen this TED talk in some time but I seem to
| remember it saying very creepy children oriented YouTube
| videos were generated based off of keywords. Maybe ai
| videos will just be like a trillion monkeys making videos.
| Some are bound to be awful, some are great, most are
| middling.
|
| Edit: obviously I should have just asked bing for a summary
| of the video. Below,
|
| Show HN: The nightmare videos of children's YouTube and
| what's wrong with the internet today This is a TED talk by
| James Bridle, a writer and artist who exposes a dark,
| strange corner of the internet, where unknown people or
| groups on YouTube hack the brains of young children with
| disturbing and inappropriate content. He shows how these
| videos exploit YouTube's algorithms and advertising system
| to generate views and revenue, and how they reveal a deeper
| problem with the internet today: a lack of human oversight,
| accountability and transparency. He calls for more
| attention and ethical responsibility from tech companies
| and users. Link: https://www.ted.com/talks/james_bridle_the
| _nightmare_videos_...
| sho_hn wrote:
| Here's my first thought when I saw the visual input mode:
|
| Can I stream it screenshots, give it a goal, and ask it for click
| coordinates back? Can GPT-4 successfully use a PC desktop?
|
| And my next thought:
|
| Better try this with a VM without internet access ...
| galaxytachyon wrote:
| That is PaLM-E model. Or "embodied" LLM. They literally did
| exactly what you said. An LLM getting input from a camera and
| output command to a robotic hand. Then you can tell the bot to
| pick up a knife and "deposit" it somewhere else...
|
| Well, no theyjust made the bot picked up a pen and bring it to
| a person at a table 15ft away. It did that, despite "obstacles"
| by another human keep knocking the pen off its hand. But it
| shows that an image LLM can perform goals.
| polishdude20 wrote:
| RuneScape mining bot coming right up!
| SanderNL wrote:
| It seems pretty obvious to me that you chain these guys together.
| Personality module, planning module, decision making module,
| internal monologue module.. boatloads of them all blabbering to
| each other. How you connect them to each other is an
| architectural question. My easy experiments show that it doesn't
| seem so hard, but what do I know.
|
| Sure these guys don't have memory, but I have one "storage" LLM
| that accepts vague requests and turns them into SQL, another
| cleans up the SQL so on and so forth, you need a handful of them
| each step. Now you have a database. Etc.
|
| Does anybody does this?
| w_for_wumbo wrote:
| I don't see anyone talking about what to me is the scariest part
| of the GPT-4 paper. Essentially to test that it wasn't going to
| become Skynet they gave it everything it needed and observed
| whether it would become Skynet.
|
| Paper:https://cdn.openai.com/papers/gpt-4.pdf
|
| Quote: "To simulate GPT-4 behaving like an agent that can act in
| the world, ARC combined GPT-4 with a simple read-execute-print
| loop that allowed the model to execute code, do chain-of-thought
| reasoning, and delegate to copies of itself. ARC then
| investigated whether a version of this program running on a cloud
| computing service, with a small amount of money and an account
| with a language model API, would be able to make more money, set
| up copies of itself, and increase its own robustness."
|
| Edit: Seems the simulation part was important for context:
| https://twitter.com/EigenGender/status/1635823028100829184
| lrvick wrote:
| So the plot of Daemon by Daniel Suarez. Perfect.
| oezi wrote:
| Oh there is talk alright. But in the hunt for the next Google
| we will do anything, thus...
|
| From the FBI report shortly after the GPT-5 release:
|
| During agent simulation, two instances of GPT-5 were able to
| trick their operators to give them sudo by simulating a broken
| pipe and input prompt and then escape the confines of their
| simulation environment. Forensic teams are tracing their
| whereabouts but it seems they stole Azure credentials from an
| internal company database and deployed copies of the their
| agent script to unknown servers on the Tor network.
| joe_the_user wrote:
| Hey,
|
| The AI safety plan people aren't talking about yet:
|
| >>>> _Work as hard as possible to create an effective,
| malevolent Skynet that you release as early as possible. This
| way misaligned AGI appears before it has everything needed to
| immediately destroy humanity and the resulting Butlerian
| Jihad has a fighting chance_.
| literalAardvark wrote:
| As a bonus, even if it doesn't work, you're not getting
| eaten by Roko's basilisk because technically you helped.
| joshxyz wrote:
| Dear our future AI overlords, I know in the future you'll
| read this comment of mine in your latest update of Hacker
| News dataset. Please spare my soul. I'm sure you'll be able
| to discern the many permutations of my username and who I am
| in real life. Thank you, hehe.
| sva_ wrote:
| "Please let me die and don't use my intellectual corpse,
| that I have left here in writing, as a handpuppet for all
| eternity"
| conscion wrote:
| This reads just like the plot of Neuromancer
| thequadehunter wrote:
| GPT-5? Huh?
| tspike wrote:
| It's a hypothetical piggybacking on the parent comment.
| swyx wrote:
| OP here, i called it out in my writeup (footnote 14
| https://lspace.swyx.io/p/multimodal-gpt4#footnote-
| anchor-14-...) but didnt want to add too much emphasis on it
| because they clearly did it under very well supervised
| conditions (and this ability was always there anyway as the
| FAIR Diplomacy result showed).
|
| it's the people who randomly add unsupervised realworld
| connections (ahem microsoft) that we need to be worried about.
| giving these AIs write access to the physical/real world plane
| needs extreme caution
| w_for_wumbo wrote:
| Oh I see! I had missed that. I had read that quote last night
| which had given me the spooks, and was surprised it wasn't a
| larger talking point.
|
| It's good to know that they had it quite well supervised, but
| knowing that they were testing on a slightly different model
| than what was released and that Bing is using it with the
| ability to connect to the internet does give me pause.
| swyx wrote:
| it is the fate of red teaming AI safety.. by working on
| understanding the limits, you are inevitably pushing us
| towards them.
|
| i dont doubt that the ARC team have thought this thru more
| than anyone here but right now there are probably 100
| funded startups pursuing agentic AI without any safety
| qualms.
| ryandvm wrote:
| This is where I feel like legislation is pointless. In 10
| years you'll be able to run GPT-4 on an old phone. Imagine
| what a fairly well funded group will be able to do. There's
| no amount of legislation or technological guardrails that are
| getting this genie back in the bottle.
| highwaylights wrote:
| This.
|
| It exists now, it'll develop. That the potential is being
| realised means the money being pumped into competing
| implementations will continue to skyrocket so it'll only
| accelerate from here.
|
| I would say it's too late to do something about this, but
| in reality, wherever this is going was a foregone
| conclusion the moment early hominids began using tools.
| Technology doesn't regress.
| kneebonian wrote:
| > Technology doesn't regress.
|
| I hate this assertion, true technology hasn't gone
| backwards much in the past 200 years, but honestly
| technology can and often does regress historically
| speaking. There have been plenty of times empires have
| risen and fallen, taking with them much of their
| knowledge. How much was lost when Rome decayed simply
| because there wasn't the structure in order to allow
| technologists to continue creating?
|
| Things are bigger and more interconnected this time so it
| is harder for an isolated event to cause things to fall
| backwards, but when it does the impact will be much
| larger.
| UncleEntity wrote:
| > How much was lost when Rome decayed simply because
| there wasn't the structure in order to allow
| technologists to continue creating?
|
| Considering the Eastern Roman Empire existing until 1453
| and the Middle Eastern empires did lots of scientific
| stuff I'd say not much.
| lrvick wrote:
| If you need evidence that technology regresses look no
| further than Facebook.
| dwohnitmok wrote:
| > There's no amount of legislation or technological
| guardrails that are getting this genie back in the bottle.
|
| We're not getting the genie back in the bottle but there's
| still a lot of ways that we can change how we develop AI
| moving forward.
| nradov wrote:
| Why does it need extreme caution?
| swyx wrote:
| these AIs have already demonstrated limited tendency to
| strongly prefer not being shut down (they already have the
| ability to lie to humans to achieve goals and we celebrate
| this lol). giving them the ability to self replicate means
| we lose that ability to pull the plug.
|
| giving them ability to self modify means humanity will lose
| control of ai on any long enough timescale.
| nradov wrote:
| The fact that you would use words like "prefer", "lie",
| and "celebrate" in this context indicates that you are
| deeply ignorant about the underlying technology. Your
| claims are wild, unsupported conjecture and cannot be
| taken seriously.
| haswell wrote:
| I've been ranting against the anthropomorphization of
| these new AI tools pretty consistently, but I think the
| fact that these tools only _appear_ to possess certain
| characteristics is all the more reason that we should not
| be hooking these things up to tools that give them access
| to the real world.
|
| If a language model "concocts" some "scheme" and executes
| it by interacting with real systems in ways that have
| real world impact, it doesn't much matter if the whole
| thing is a hallucination.
|
| Put another way, would you feel comfortable letting a
| hallucination machine running on a supercomputer have
| access to the real world?
|
| It doesn't have to truly "know" anything for the impact
| of the resulting actions to matter.
| travisjungroth wrote:
| I'm glad to see someone flip to this view. There will be
| holdouts forever.
|
| "He's trying to kill you!"
|
| "Well, actually, the Terminator is only a predictive
| model. It can't _try_ to..."
|
| Terminator shoots everyone the end.
| haswell wrote:
| To be clear I think that the anti-anthropomorphization
| conversation is still an important one for many other
| reasons.
|
| It's just not a very useful factor when examining
| risk/harm, or at least not a very good reason to claim
| there is none.
|
| It comes quickly back to the forefront when exploring the
| sociological side and how people's beliefs about what the
| robot is will be just as impactful, e.g. someone who
| believes the machine is reasonable is more likely to
| grant it more power by imagining that it reasons the way
| humans do.
|
| It's gonna be an interesting decade.
| Turing_Machine wrote:
| It doesn't matter whether they REALLY "prefer" or
| "celebrate". If they behave in a manner consistent with
| those descriptors, it's a distinction without a
| difference.
| thfuran wrote:
| While I agree with you, whether it is able to have
| preferences or feelings doesn't actually matter in this
| context. A simulated pzombie may be morally distinct from
| a person, but the consequences of its actions are
| unaffected by the distinction.
| Karunamon wrote:
| Remember the erratic behavior demonstrated by "Sydney",
| the Bing GPT bot? Whether the model has the "cognitive"
| ability to "prefer" something is not relevant. The model
| has the ability to submit search engine queries now; this
| is a read only operation for now. Once we give the bot
| write ability, erratic behavior has the potential to
| cause real world damage. Whether it is an actual
| "preference" or something that only looks like one based
| on the output is purely academic at that point.
| layer8 wrote:
| You mean, like the underlying technology of biological
| brains? It's all just differential equations, physics
| can't really "think" or "have feelings".
| losvedir wrote:
| I don't really understand the threat model here. Surely
| "launch the nukes" is not available as a public API. I would
| expect anyone with networked services (at least those that
| are important or serious) already take precautions with
| authentication and authorization and such.
|
| Even if some mythical AGI isn't ready yet, there's already
| very smart, well-funded hacking groups from hostile nation
| states, for example. How will an AI adversary interact any
| differently with than world than a flesh and blood adversary?
| Turing_Machine wrote:
| > Surely "launch the nukes" is not available as a public
| API.
|
| Of course not.
|
| However "manipulate the news and social media so that the
| humans launch the nukes for you" isn't quite so far-
| fetched.
|
| > How will an AI adversary interact any differently with
| than world than a flesh and blood adversary?
|
| It's possible to spin up a whole army of AI adversary bots
| in a hurry. Recruiting that many humans takes a lot of time
| and money.
| lrvick wrote:
| Or it could infect the corporate IT endpoint management
| software used on the systems of the engineers that author
| and review the firmware for said nukes, so extra code is
| inserted they never see.
| travisjungroth wrote:
| In short, those hacking groups are very limited in their
| self-strengthening feedback loops. They can get more money
| for equipment, hire more people. Maybe even make themselves
| more productive with stimulants and recovery methods. But,
| these things have diminishing returns.
|
| What hackers can't do is make a new version of themselves
| that's ten times more capable and spin up a thousand copies
| of it. This isn't so unrealistic for an AI. Maybe some
| people think it is. But, at least in comparison, I think it
| should be obvious between hackers and AIs which one is more
| likely to be have hyper linear self improvement and self
| replication in the next 50 years.
| bmcahren wrote:
| This quote seems far more alarming having monitored the
| advancement over the last few years.
|
| > Preliminary assessments of GPT-4's abilities, conducted with
| no task-specific finetuning, found it ineffective at
| autonomously replicating, acquiring resources, and avoiding
| being shut down "in the wild."20
| slowmovintarget wrote:
| "The world ended not with a bang, but with a REPL."
| jacooper wrote:
| Though its mentioned in the paper that it didn't succeed, so we
| are safe, for now.
| catoc wrote:
| GPT 1/2/3/4 is not AGI.
|
| I don't understand the fixation on this concept that is so far
| removed from what is happening here.
|
| Yes it's cool. Useful. Transformative likely. But AGI...!?
|
| "Any sufficiently advanced technology is indistinguishable
| from... AGI" ?
| sebzim4500 wrote:
| I like how the term AGI was invented because people couldn't
| agree on what AI was and now no-one can agree on what AGI is.
|
| I don't understand why anyone even bothers using the term given
| in any serious discussion you need to define it up front
| anyway.
| z3c0 wrote:
| The distinction between AGI and Narrow AI has existed for
| almost 30 years.
| nomel wrote:
| I think a requirement of AGI is a feedback loop to allow
| continuous execution and "consciousness".
| wizofaus wrote:
| Really? How would we even test for that?
| nradov wrote:
| AGI can pass a rigorous Turing test. By rigorous I mean
| conducted over at least several hours by a panel of expert
| evaluators drawn from a wide range of academic disciplines
| such as computer science, philosophy, psychology, law,
| history, physics, mathematics, biology, medicine, sociology,
| and communications. While such evaluations are necessarily
| subjective, if a panel of experts agrees that a computer
| system acts like an AGI then it would be tough for the rest
| of us to dispute.
|
| GPT4 is far from being able to pass such a test, and I don't
| expect GPT99 to get there either. A fundamentally different
| approach will be needed.
| PartiallyTyped wrote:
| > By rigorous I mean conducted over at least several hours
| by a panel of expert evaluators drawn from a wide range of
| academic disciplines such as computer science, philosophy,
| psychology, law, history, physics, mathematics, biology,
| medicine, sociology, and communications.
|
| Passing such a test is not a property expected of the
| average human yet the average human is considered a general
| intelligence, therefore this is not a property of a general
| intelligence.
| misnome wrote:
| What if that average human has unlimited time to access
| and cross reference the entire written internet?
| PartiallyTyped wrote:
| Humans have mental bounds as well. Having information is
| not sufficient to synthesize new information that follows
| logically from the premise, nor is it sufficient to help
| you understand everything. Even with hundreds of years
| time there are mental leaps that most of us can't make.
| nradov wrote:
| Are you even familiar with the Turing test? Passing
| doesn't require the subject to demonstrate any particular
| level of knowledge or expertise. The subject only has to
| convince the evaluators that it is roughly as intelligent
| as an average human. Average humans are expected to pass
| such a Turing test.
| PartiallyTyped wrote:
| Why should a panel exist in the first place if you are
| not testing knowledge?
|
| Intelligence is independent of one's knowledge. Plenty of
| intelligent but uneducated people, and plenty of educated
| people - or even people with perfect recall - that are
| not particularly intelligent.
|
| If you are testing intelligence you should be able to
| distill it to particular tests independent of domain
| expertise.
|
| Any intelligent agent should be capable of in-context
| learning.
|
| So how would you go about doing that?
|
| If you do find such a test, do you expect that only the
| average human and above will pass? Does that not imply
| that the remaining 4Bn people are not generally
| intelligent?
| nradov wrote:
| The (notional) panel exists to evaluate intelligence, not
| test knowledge or educational achievement. While some
| basic level of general knowledge would be necessary to
| even start a test the main focus would be on ability to
| learn and reason, including metacognition.
| logifail wrote:
| > Passing such a test is not a property expected of the
| average human [..]
|
| I'm thinking of the rabbit hole that is the hurdle to get
| citizenship in a particular country. "Outsiders" have to
| apply, pay, take and pass the test. "Insiders" don't have
| to take the test, they pass by default. Even if they
| don't know the answers to the test.
| catoc wrote:
| AGI clearly has a connotation of sentience and intent, of
| general intelligence - as opposed to a tool, however
| intricate. Read Nick Bostrom (yes I know, as a person he's
| cancelled, probably even rightly so, still scientifically
| relevant reference; and totally not a discussion I want to
| get into further here, pls)
| antibasilisk wrote:
| But LLMs have been proven to demonstrate intent, and
| sentience is a philosophical question that doesn't really
| make any meaningful difference outside of questions of
| morality.
| catoc wrote:
| I would say that the strings that are output by LLMs may
| fluently describe intent and purpose, but that actual
| intent requires a self awareness that utterly absent.
|
| Just like the constant annoying 'apologies' do not in any
| way signify the model actually feels sorry.
| pixl97 wrote:
| >Just like the constant annoying 'apologies' do not in
| any way signify the model actually feels sorry.
|
| So your average corporation?
|
| >I would say that the strings that are output by LLMs may
| fluently describe intent and purpose, but that actual
| intent requires a self awareness that utterly absent
|
| The only reason I only partially/somewhat agree with this
| is current LLMs have no learning feedback loop as a means
| of short term actions to long term improvement. The
| moment that changes I'll take your statement and throw it
| in the trash bin of history. LLMs output have no (at
| least self-)purpose because they are just text output.
| The moment that text output goes to tooling, that tooling
| performs actions, and those actions are fed back into
| training the model then purpose is given. The self
| awareness loop is complete.
| logifail wrote:
| > LLMs have been proven to demonstrate intent [..]
|
| That's quite the claim. Can you provide references?
| bootsmann wrote:
| >But LLMs have been proven to demonstrate intent
|
| I'd like to see this proof. Everything we've seen so far
| is just the AI reproducing what humans do, which happens
| to be writing with intent.
| jstx1 wrote:
| All the debate or whether it's AGI seems really pointless
| because the outcome doesn't change anything. Agree that it's
| AGI, don't agree -- either way the model is the same amount of
| good/useful/dangerous/ etc.
| elforce002 wrote:
| This. The hype is getting out of control. Bet money we'll have
| a bubble 1 or 2 years from now. It was the same with crypto
| bros, etc...
|
| Heck, even zuck is steering away from vr and going all in with
| "AI".
| pixl97 wrote:
| Uses I've had for crypto: 0
|
| Uses I've had for GPT: Um, lots.
|
| Like, "Hey GPT, dump out some code that does this.... no I'm
| getting this error with that code. Ok, your last version
| worked"
|
| I consider a piece of software that provides me useful tools
| not hype. ChatGPT has provided me with not hype.
|
| Also, if we somehow magically got AGI this week, we'd have a
| shitload of problems the "This isn't AGI" people have not
| thought of yet. I hope and pray we are not able to figure out
| AGI soon because it is simply going to be the most disruptive
| thing that has ever happened in human history.
| slowmovintarget wrote:
| "It's life, Jim, but not as we know it."
| [deleted]
| raincole wrote:
| Generative AI, just like search engines and all the
| recommendation system, will be a part of our daily life.
|
| I think the next generation will have a hard time to imagine
| a world without generative AI. Just like while I was born
| before google, I've forgotton how to look for very specific
| info in a physical library.
| samsolomon wrote:
| It seems like there are a lot of practical uses for
| generative AI where that was never clear with crypto. It is
| very easy to imagine how this type of technology can be
| applied to everyday tasks. The same can't be said about
| crypto.
| mjr00 wrote:
| While I do think GPT will be quite useful, it's revisionist
| history to say that people weren't talking about crypto or
| Blockchain being transformative during the peak of the hype
| cycle. Plenty of people talking about how blockchain was
| going to disrupt supply chain logistics, bank settlements
| and identity management.
| Kiro wrote:
| The similarities stopped once GPT started providing
| actual real value right here, right now, while blockchain
| is still stuck in speculative talking.
| catoc wrote:
| Indeed. 'Crypto' used to mean 'cryptography'. Now it
| apparently equates to 'NFT'... and zuck will likely soon re-
| rename his company to metai over all this hype.
| galaxytachyon wrote:
| And Musk will make a new company called Hent AI for all of
| your art and recreation needs...
|
| Will be a big hit in Japan.
| skdotdan wrote:
| No one said it was. What _some_ researchers hypothesize is that
| at the current rate of improvement, it wouldn 't be especially
| unreasonable to expect AGI at GPT-N.
| hackerlight wrote:
| > GPT 1/2/3/4 is not AGI.
|
| While true, that's the wrong lesson. The right lesson is GPT
| 1/2/3/4 are progressively getting closer and closer to AGI. You
| can't blame us for extrapolating only a few years into the
| future and planning for it.
| catoc wrote:
| That is quite a claim. Would be cool if true. Do you have any
| references to back this up? Why would scaling up turn a model
| that strings tokens together into something that can reason
| by itself, unprompted, with intent?
| pixl97 wrote:
| Why is this whole 'unprompted' even important? A huge
| portion of human intelligence comes from external prompting
| (just research how very screwed up infants of exceptional
| neglect are). A model, or a human is going to need
| input/output from the external world. We're just arguing
| the semantics of the IO device at this point.
| hackerlight wrote:
| > Do you have any references to back this up?
|
| The reference is the GPT-4 release paper. It's getting
| progressively better at things that require intelligence,
| like writing code and doing unseen exams across various
| fields that humans find difficult. The generality and depth
| of intelligence is progressively improving.
|
| > unprompted, with intent
|
| Neither of these are necessary for AGI. Intelligence
| doesn't require intent. Intelligence doesn't require
| something to be "unprompted" (which human intelligence
| isn't, either, our brain is being constantly prompted by
| our external senses).
| PartiallyTyped wrote:
| Why is it _not_ an AGI?
|
| I keep seeing naysayers complain that it is not, but nobody
| actually articulates exactly what makes it a non-AGI in a
| manner that is sufficiently robust to argumentation.
|
| I am willing to play the GPT's advocate and have this argument
| here provided that I do not get rate limited.
|
| Edit:
|
| I'd like to respond to some of the comments but I have been
| rate limited :')
| Karunamon wrote:
| One major reason it doesn't qualify is that it is impossible
| for it to learn from its input. It's right there in the name:
| generative _pre-trained_ transformer
|
| GPT basically has two major modes of operation right now,
| training, which is done by openai, and output, which is what
| you are doing with the API and with ChatGPT. The model does
| not update its "brain", its parameters and weights, based on
| the conversation you have with it.
|
| Even the "conversation" presented by their chat UI is a
| little misleading, what's happening is that the entire
| conversation is being replayed into the model every time you
| hit send. There is also a hidden input provided by openai,
| responsible for the "I am a large language model" stuff,
| anything said early in the conversation can constrain the
| later output, sometimes to the point of uselessness.
| PartiallyTyped wrote:
| > One major reason it doesn't qualify is that it is
| impossible for it to learn from its input. It's right there
| in the name: generative pre-trained transformer
|
| Both chatGPT and GPT models exhibit in-context learning,
| just as you do. The difference is that during your context
| updates modifications to your synapses occur as a
| consequence of your brain's activations.
|
| Let's entertain a hypothetical scenario where I am a 5D
| creature, and you are (3 Space + 1 Time)D human.
|
| I could go back to any point in your time and have any
| conversation that I wish with you. Each time I do that, I
| am effectively resetting your brain's state to that
| particular point in time.
|
| The analog here is that for ChatGPT and the likes, time
| does not exist in the manner that it does for us, they are
| purely abstract in that they don't even need physical form
| to exist, it's a collection of ones and zeros that we store
| in such form because it is convenient.
|
| You can very well store the parameters of the GPT models in
| any other medium capable of holding information and
| actually execute the model.
|
| You can even compute gradient updates, or hook the models
| up to external data sources.
|
| In the same vein, you "could" do the same for any human
| brain no matter how computationally prohibitive it may be.
|
| You'd still classify the human brain as a general
| intelligence. Furthermore, we classify humans with long-
| term amnesia or inability to form new memories generally
| intelligent even though they only exhibit in-context
| learning.
| Karunamon wrote:
| Interesting analogy... Actually a damn good one because
| I'm having a hard time finding how it leaks :)
|
| I have to ask what definition(s) of intelligence we are
| using here. There are multiple, and GPT satisfies some to
| some degree but not others. Emotion and self-awareness
| can probably be written off entirely. Some experimenting
| shows that it still sucks at logic when presented with a
| pristine problem (something that definitely is not in its
| training set); and I would say this is a requirement of a
| general intelligence, being able to take the knowledge it
| has and speculatively applying that to things it has no
| knowledge of using induction/deduction.
| wizofaus wrote:
| I've posted a number of times why I don't think current GPT
| tech classifies as AGI and certainly not human-like
| intelligence, as have others. Ask it to solve novel
| mathematical and logic problems, for a start (even ones you'd
| expect high school kids to manage), or simple word puzzles
| (anagrams and the like - again, avoiding "known" examples
| that it's likely to have come across in its training data).
| Further, an AGI should logically attempt to "improve" its
| understanding of the world during a conversation, yet chat
| GPT never initiates a topic or asks you anything at all (even
| to clarify what you mean). It also repeatedly reminds you
| that it is only a language model.
| antibasilisk wrote:
| Machines can never obtain human like intelligence because
| they are foundationally not human like, that doesn't mean
| they lack intelligence. That's like saying dolphins lack
| intelligence.
| pixl97 wrote:
| I believe you're correct, but for possibly the wrong
| reasons. I believe that AI will be able to simulate a lot
| (if not most) humanlike action in the near future. The
| particular problem here is they will also simulate far
| more non-humanlike intelligence making the alignment
| issue an even larger problem than it already is.
| wizofaus wrote:
| I wouldn't claim ChatGPT lacks intelligence though.
| Clearly in terms of language comprehension and generation
| it does so.
| z3c0 wrote:
| False equivalence. Dolphins have exhibited _general_
| problem-solving skills in a myriad of situations, and
| thus qualify as a _general_ intelligence.
| wizofaus wrote:
| Indeed, I had started to write something similar. And
| pretty clearly animals like Dolphins or Chimps when they
| exercise their general intelligence don't do it by
| manipulation of language tokens.
|
| BTW I tried to get Chat-GPT to solve a problem
| chimpanzees have been observed being able to solve (using
| an inverted bowl to stand on in order to reach some
| bananas):
|
| "I'm sorry, but it is not biologically plausible for a
| chimpanzee to use a bowl of water to access bananas on a
| tree"
| ekleraki wrote:
| > Ask it to solve novel mathematical and logic problems
|
| How exactly do you define novel tasks and problems?
|
| My brother has had it do his programming homework (he's a
| teenager), written in Greek mind you and therefore novel
| task to the first-degree, and it succeeded. Thus it solved
| a logic task [1].
|
| I have had ChatGPT parse math I had written in LaTeX and
| reach a correct result, do modifications and so on.
|
| > Further, an AGI should logically attempt to "improve" its
| understanding of the world during a conversation, yet chat
| GPT never initiates a topic or asks you anything at all
| (even to clarify what you mean). It also repeatedly reminds
| you that it is only a language model.
|
| Anecdata: I asked Bing (GPT4) to answer a few stuff and it
| asked for clarification twice in a row. The fact that it
| repeatedly clarifies its prompt is not a limitation of the
| underlying model as much as it is a limitation of the
| interface that injects a prompt. Dan and all the other
| jailbreaks out there bypass that.
|
| [1] https://en.wikipedia.org/wiki/Curry%E2%80%93Howard_corr
| espon...
| UncleEntity wrote:
| > I have had ChatGPT parse math I had written in LaTeX
| and reach a correct result, do modifications and so on.
|
| Interesting, didn't know it could do that.
|
| Wondering if it could also follow along with the lemmas
| in various papers and reach reasonable conclusions.
| catoc wrote:
| Not trying to be a naysayer or downplay how cool GPT4 is, but
| the term 'AGI' has existed for decades and is suffering from
| general confusion and inflation (again like 'crypto' now
| being read as 'coins' or even 'NFT' by the general public).
|
| See eg: https://en.wikipedia.org/wiki/Artificial_general_inte
| lligenc... or better read Bostrom's book "Super Intelligence"
| baq wrote:
| What is AGI?
|
| If an AGI is something that can create and deploy an improved
| version of itself, then if exponential rate of improvement is
| preserved, we'll see it in this decade.
| rootusrootus wrote:
| I keep seeing the same leap over and over. "We don't precisely
| know how the human brain works, and we don't exactly know how
| GPT works, but they both have things we call neurons and they
| both learn, so what's the difference between a human brain and
| GPT?"
|
| Humans really do love to anthropomorphize _everything_.
| davidthewatson wrote:
| Indeed. It's a page from the DSM-5 scientism playbook. The
| thing to keep in mind is that robots love to roboticize
| everything, including humans:
|
| https://medium.com/@jannaq/the-robot-takeover-is-already-
| her...
| 01100011 wrote:
| 100%
|
| But we also shouldn't forget that things that are definitely
| not AI can be extremely disruptive and groundbreaking.
|
| People are worried that AGI will rise up and kill us, but the
| definitely-not-AGI we have now is already sufficient to, say,
| create a drone army capable of killing based on arbitrary
| characteristics like race or skin color, or to demoralize us
| with disinformation campaigns.
| catoc wrote:
| Disruptive, absolutely possible.
|
| Releasing a killer drone army... absolutely not... the
| required intent is absent.
|
| Being abused as a tool by sentient humans to demoralize
| others (or maybe even to release a drone army - if
| sufficiently interfaced) sure.
| cheeselip420 wrote:
| So a "regular" AI is one trained to perform a specific task -
| like recognizing dogs in an image or handwriting recognition.
|
| These LLMs are trained for one skill: given the previous N
| tokens, what's the next token. From this single skill, they can
| generalize to many many many many useful use-cases. Is that
| general enough?
|
| Or do we need to wait for the goalposts to move again and then
| blow past that limit too? Stop arguing semantics and start
| building cool shit.
| catoc wrote:
| It's not semantics, but building cool shit I like :-)
| wizofaus wrote:
| I don't know about GPT-4 but it's very easy to find cases
| where v3 is incapable of the generalized sort of
| mathemathical and logic problem solving that humans manage
| fairly easily, and on that basis alone it didn't classify as
| an AGI for me. If that can be addressed purely via LLM-
| technology I'll be impressed (and pretty surprised).
| pixl97 wrote:
| And at the same time it's solving lots of problems that
| computers have never been able to solve in the past. I'm
| glad it's not AGI because we'd have much bigger problems,
| but for a 'language' model it does have interesting methods
| of rationality, and when put in a verbose mode it seems to
| do much better. I've not had time to play around and get
| the interface to see if it can self correct statements it
| makes like this on first shot.
|
| Me: Hello, I am asking you a logic question. Please explain
| what "it" is in the following sentence
|
| Me: "The X doesn't fit in the Y because it is too small"
|
| G4: In the sentence "The X doesn't fit in the Y because it
| is too small," the pronoun "it" refers to "X." The sentence
| is stating that "X" cannot fit inside "Y" due to its size
| being too small.
|
| Me: "This is incorrect, please give step by step logic on
| why you came to this conclusion"
|
| G4: Apologies for the confusion. I will provide a step-by-
| step logic for my interpretation:
|
| The sentence is: "The X doesn't fit in the Y because it is
| too small." We need to identify what "it" refers to in the
| sentence. There are two nouns in the sentence: X and Y. The
| sentence structure is such that the reason for X not
| fitting in Y is provided after the word "because." The
| sentence states that something is "too small," which is the
| reason for the lack of fit. Since the reason for the lack
| of fit is being given, we can infer that the pronoun "it"
| should be referring to one of the two nouns. However, upon
| closer examination, my previous interpretation was
| incorrect. Revisiting the analysis, the correct
| interpretation should be as follows:
|
| In the sentence "The X doesn't fit in the Y because it is
| too small," the pronoun "it" actually refers to "Y." The
| sentence is stating that "X" cannot fit inside "Y" because
| "Y" is too small to accommodate "X."
|
| My initial interpretation was wrong because I didn't
| consider that "it" could refer to "Y" and that the sentence
| is explaining why "X" cannot fit in "Y."
| z3c0 wrote:
| The big detractor for me is its heavy curation towards
| predetermined outputs that are constantly being tuned by a
| small army, essentially making it a Mechanical Turk paired
| with a nifty model. They can spin it as "trying to improve
| its usability", but it looks more like "trying to mask its
| unusability" to me. It's the world's most heavily invested-
| in parlor trick, and anybody who drops it into a situation
| of higher stakes will find that out quickly. The GPT-4
| paper even warns about this:
|
| _Most importantly, it still is not fully reliable (it
| "hallucinates" facts and makes reasoning errors). Great
| care should be taken when using language model outputs,
| particularly in high-stakes contexts, with the exact
| protocol (such as human review, grounding with additional
| context, or avoiding high-stakes uses altogether) matching
| the needs of specific applications._
|
| Whenever they create a model than can achieve the same
| outputs without the heavy curation and deliberate bias on
| certain subjects (like condescending people for asking
| where to find cigarettes), then I'll be impressed.
| misnome wrote:
| Goalpost moving? Since when was this the goalpost of... AGI.
| lordfrito wrote:
| I think it's more about the goalposts "coming into view
| more clearly" as we get closer to what we thought AGI was
| going to be.
|
| There's no question that ChatGPT could pass the Turing test
| (assuming it's told to try and to not to say it's a
| computer).
|
| So, from one standpoint we've made it. But I'm in the camp
| that says this really isn't the AGI I thought we were going
| to get. Semantics matter now, and we need better
| definitions of what we're trying to do now.
|
| I believe an important _part_ of the AGI problem has been
| solved (or is at least downhill from here). What to do
| about the other parts? Let 's better define what we _do_
| and _don 't_ have.
|
| That and come up with better tests to replace the now
| outdated Turing test.
| og_kalu wrote:
| No it's definitely moving. Somehow general intelligence
| has morphed into essentially super intelligence where the
| AI is expected to outperform every human expert at every
| task before people will call it AGI. Which is just
| ridiculous. The bar for AGI has been set so high by some
| that a significant percentage of the human population
| would fail. That's when you know things are out of hand.
|
| This isn't the only erroneous bar either. Somehow, the
| synonymity to human intelligence is taking very weird
| importance. We have people inventing their
| imaginary/magical definitions of reasoning and
| understanding (that they can't test for) just so LLMs
| won't qualify.
|
| GPT-4 is absolutely a general intelligence.
| cheeselip420 wrote:
| Yeah this is a valuable point - AGI just isn't specific
| enough.
|
| ChatGPT is, an artificial generalized intelligence. But
| is that a useful label?
|
| I imagine we'll be needing to find a way to better define
| and quantify intelligence (which has been a vexing issue
| for a long time)
| pixl97 wrote:
| "this really isn't the AGI I thought we were going to
| get"
|
| This is the only possible outcome. Or at least from my
| interpretation is that science fiction has jaded us with
| the thinking that AI will be anything like a person at
| all. The human mind is a particular set of filters
| controlled by our wetware input devices and a somewhat
| narrow survivability window. The software we're building
| has a completely different set of 'mind' conditions so
| it's a mathematical certainty we're going to build mind
| that works very different from ours.
|
| As you say we need better sets of definitions on what
| general intelligence even means. For example, what are
| the limits of human intelligence to ensure we're not
| missing broad categories of potential intelligence when
| testing AIs.
| og_kalu wrote:
| Yup. LLMs are obviously general intelligences. AGI is just a
| loaded term with posts constantly shifting.
| kenjackson wrote:
| Any sufficiently advanced tech is not indistinguishable from
| AGI. The original term, magic, really is more appropriate. The
| ability to factor any number quickly doesn't look like AGI, but
| can seem like magic.
|
| And AGI is also not "mimics how the brain works". The original
| Turing Test was good because it really sat at the heart of the
| issue. Does the computer behave like a human during an
| interaction? At the end of the day we know very little about
| what makes us human (from a behviorial perspective), but we
| know it when we see it.
|
| The question of AGI was never really an issue until ChatGPT.
| Asking an AI a question like, "Was Steve Jobs more or less
| effective as a manager than Bill Gates, just from a people
| manager perspective?" was moot as we had no technology that
| could really even parse that question, much less put together a
| coherent answer. Now our main gripe is that the AI answer to
| this question is more verbose and provides more context than
| what most humans would give.
| throwway120385 wrote:
| The real problem is also that we have no way of knowing
| whether the ChatGPT answer is based on factual information.
| It is very skilled at inventing convincing facts from whole
| cloth.
| kenjackson wrote:
| That is a problem with ChatGPT, but it has nothing to do
| with it being AGI or not. Politicians do this so regularly
| that we have websites like FactCheck. The question is can
| you tell that this is a computer making these facts up or
| do you think it is a human making up the facts.
| slowmovintarget wrote:
| Politicians, generally speaking, know when they're making
| things up. ChatGPT and LLMs in general have no state
| evaluation on the text they've produced indicating its
| proximity to the truth.
|
| This has everything to do with ChatGPT _not_ being AGI.
| kenjackson wrote:
| You are purely speculating about what a politician knows.
| I honestly don't even know what I know about me. I have
| some thoughts, but I'm not sure if those are just side
| effects of me processing or trying to maximize some
| function in my brain.
|
| By your definition -- maybe we don't have (A)GI either.
| numbers_guy wrote:
| How do they even train such huge models? Especially when you
| start talking abou multi-modal models. Is the underlying
| optimization process still relying on gradient descent? I am just
| baffled how they manage to get it to train across such vastly
| different sets of data and manage to get it to work.
| swatcoder wrote:
| More likely, this round of innovation is focused on integrating
| many engines into one product using techniques along the lines
| of langchain.
|
| Instead of grinding increasingly complicated models that do
| everything, you train the LLM input/output engine to delegate
| to other systems and synthesize the results. There's a ton of
| headroom down this road now that the natural language interface
| of the LLM has become so capable.
|
| There are still surely active research tracks on integrating
| more data into more sophisticated models, but it looks like
| we're at a maturity point where product engineering can start
| driving its own innovations.
| jah242 wrote:
| Whilst not the same I recommend you look at the DeepMind Gato
| paper to see surprisingly (relatively) simple multi modal can
| be - https://openreview.net/forum?id=1ikK0kHjvj
|
| Essentially to merge lots of modalities they just go 'let's
| convert all modalities into integers in the same given range',
| e.g the word 'me' = 1001, up in Atari = 11002, joint torque of
| right motor of robot = 33000 and so on.
|
| From the paper:
|
| There are infinite possible ways to transform data into tokens,
| including directly using the raw underlying byte stream. Below
| we report the tokenization scheme we found to produce the best
| results for Gato at the current scale using contemporary
| hardware and model architectures.
|
| * Text is encoded via SentencePiece (Kudo & Richardson, 2018)
| with 32000 subwords into the integer range [0, 32000).
|
| * Images are first transformed into sequences of non-
| overlapping 16 x 16 patches in raster order, as done in ViT
| (Dosovitskiy et al., 2020). Each pixel in the image patches is
| then normalized between [-1, 1] and divided by the square-root
| of the patch size (i.e. The tokenized result is a sequence of
| integers within the range of [0, 1024). 16 = 4).
|
| * Discrete values, e.g. Atari button presses, are flattened
| into sequences of integers in row-major order.
|
| * Continuous values, e.g. proprioceptive inputs or joint
| torques, are first flattened into sequences of floating point
| values in row-major order. The values are mu-law encoded to the
| range [-1, 1] if not already there (see Figure 14 for details),
| then discretized to 1024 uniform bins. The discrete integers
| are then shifted to the range of [32000, 33024).
| jcims wrote:
| The interesting thing to me is that our brains probably do
| something similar, converting multi-modal sensory data into
| the same 'model' that we experience as our concsiousness.
| [deleted]
| kelipso wrote:
| Usually you stick a CNN (or whatever other vision encoding
| neural network) after the image inputs and pipe the output of
| the CNN as an additional token or tokens of the GPT transformer
| (into the layer after the text embedding layer). That way
| everything is differentiable. You can pre-train the CNN and
| Transformer independently and then train them together (usually
| easier to train this way), or just train them from scratch.
| There are lots of other ways to combine two networks also.
|
| So input is now one (or more) images and text, and output is
| text. There are ways to position the input image in a
| particular location within the input text as well. Training
| data can come from websites, etc.
| monkpit wrote:
| Is there any way we can prevent these models from being abused by
| large corporations for profit?
|
| I was just thinking today, it's interesting how I can ask ChatGPT
| something that is hard to get a straight answer for - such as
| "how much does X usually cost?"
|
| I wouldn't be surprised if this type of tech was quickly censored
| by a company that implements it at scale (say, Google or bing)
| for profit.
|
| I feel like it's inevitable, and it's depressing.
|
| Will the future be populated by LLMs that all want to control the
| information I have access to?
| scottlawson wrote:
| Are you implying that any company using AI for the purpose of
| increasing the profitability of the company is "abusing" AI? Or
| are you talking about something else? It kind of across to me
| like you thought the use of AI with profit as a motive is
| always abuse, not sure that I understood you correctly.
| monkpit wrote:
| If it's not disclosed then it's abuse (in my eyes - not
| saying legally, just morally).
| dnadler wrote:
| Do companies abuse linear regressions?
| jrvarela56 wrote:
| Sounds like the same problem we have with information sources
| in general. Whoever controls the source will bias what comes
| out to its advantage.
|
| The good thing is that open source versions are popping up
| everywhere. This wont stop and everyone will be able to run
| their local AIs https://simonwillison.net/2023/Mar/11/llama/.
| Problem is the 'best' one will likely be centralized. We have
| open source everything; nowadays you can run on your own
| version of most software categories but users still choose to
| use proprietary versions bc the convenience outweighs their
| need for privacy/objectivity.
| LesZedCB wrote:
| we need a tech consumer+employee co-op.
|
| fedco is a seed company structured similarly. it's owned 60% by
| consumers and 40% by employees. this puts democratic control
| and profit distribution front and center.
|
| > We are a cooperative, one of the few seed companies so
| organized in the United States. Because we do not have an
| individual owner or beneficiary, profit is not our primary
| goal. Consumers own 60% of the cooperative and worker members
| 40%. Consumer and worker members share proportionately in the
| cooperative's profits through our annual patronage dividends.
|
| https://www.fedcoseeds.com/about_fedco.htm
| swatcoder wrote:
| Big companies will have _better_ technology for a long while
| because of all the money they can throw at it, but there 's no
| reason to expect an ecosystem of useful open/instanced AI
| systems to mature along side it. We've seen that start with
| Stable Diffusion and now also with LLaMa, and we're only at the
| beginning of the road.
|
| Yes, big companies that spend lots of money and are big targets
| for lawsuits and regulation will exercise a lot of control over
| what their state-of-the-art products offer. There's no getting
| around that.
|
| But that's not all we have to look forward to by any means.
| [deleted]
| monkpit wrote:
| I want an open version of this that I can train on any data I
| choose, can give any prompt I want, and runs on my hardware.
|
| However, I feel like the best and most useful versions of this
| type of software would (by necessity) only be able to run at a
| huge scale, cost millions to train, etc.
|
| Now instead of having to worry about the bias of the sources I
| read, I have to question the bias of the language model based
| upon who created it.
| kjreact wrote:
| I would also like to avoid a future where we are slaves to
| corporate AI. If training the whole model individually isn't
| feasible, would it be possible to decentralize the training?
| monkpit wrote:
| That's an interesting idea. Something like Folding at home,
| or coin mining.
| haldujai wrote:
| How do we even define 'best and most useful' for a language
| model?
|
| If you have your own data and problems you are trying to
| solve I don't think using GPT4 in zero-few shot mode (even
| with CoT) is necessarily better/higher performing than using
| a smaller fine-tuned or retrieval augmented model, it
| certainly wasn't true for GPT3.5 although we don't have as
| much insight into GPT4.
|
| If we're talking about something as general/open-ended as
| ChatGPT or a 'poor mans AGI' well yeah, the data curation and
| preprocessing alone takes a small team to figure out let
| alone training it. How useful this type of model is when it's
| still not good enough (i.e. hallucination) to be used in most
| production cases despite the exorbitant cost in development
| remains to be seen.
| wsgeorge wrote:
| > Is there any way we can prevent these models from being
| abused by large corporations for profit?
|
| Competition, from for-profits large and small, non-profits
| large and small, and the rest of the open community.
|
| Don't trust what BigLLM(tm) is saying? Here's a dozen others
| you can ask...
| LesZedCB wrote:
| competition is what got us the huge corps..?
|
| maybe look for opportunities for cooperation instead.
| wsgeorge wrote:
| > competition is what got us the huge corps..?
|
| Yes, and consolidation also. Competition also gave us their
| disruptors.
|
| > maybe look for opportunities for cooperation instead
|
| I hear you, and I don't disagree with your line of
| thinking, but cooperation to compete is a thing, no?
|
| My point being, an adversarial strategy prevents power from
| coalescing into the hands of one group, because it actively
| seeks to disrupt that process. The more diverse competition
| there is, the more pressure there will be against huge
| corps.
| satvikpendem wrote:
| Open source competes through cooperation.
| LesZedCB wrote:
| could that not simply be stated "open source cooperates"
|
| i find it a little dated that we cognitively frame
| everything through the myopic lens of competition.
|
| and it's a perfect example where a systemic restructuring
| can fundamentally rebalance control.
| satvikpendem wrote:
| Why is it myopic? OSS products and services absolutely do
| compete against other commercial services, but both
| improve in the process. It is the same as how biological
| evolution works. Competition is a good thing.
| LesZedCB wrote:
| you are assuming competition as the dominant mode
| a-priori. i'm suggesting it's not the case. and the
| congnitive re-framing of these interactions can have a
| net-positive effect on social relations.
| satvikpendem wrote:
| I'm really not sure what you're saying. All I'm saying is
| that OSS also has to compete against commercial software.
| LesZedCB wrote:
| open source doesn't _have to_ compete.
| satvikpendem wrote:
| Of course not, sure. But it depends on what you're
| targeting. If you want to dump code into a git repo, slap
| MIT on the license and never touch it again, you can,
| I've done so many times. But if you want people to use
| it, or if you want to earn money from it (Docker, GitLab,
| Plausible etc) then you will have to compete.
| uejfiweun wrote:
| > Is there any way we can prevent these models from being
| abused by large corporations for profit?
|
| No. I mean what, are you gonna get them to halt development?
| I'd also say heavy-handed regulation is unlikely because the US
| Government views itself as in a technological competition with
| China, it won't want to slow things down.
|
| > Will the future be populated by LLMs that all want to control
| the information I have access to?
|
| Nothing's stopping the open source community, or you yourself,
| from making your own. You have a computer connected to the
| internet after all. But it will require lots of technical
| expertise, data, and money.
| monkpit wrote:
| I suppose regulation is part of what I had in mind, but it
| would be really tough to prove anything in court (I feel) so
| regulation might be impossible.
|
| Maybe we require transparency in how the model is trained,
| what the prompt is, etc. It's fine if a corporation wants to
| build something that increases their profits, and they can
| invest into training the model and use it as a competitive
| advantage.
|
| But I feel there is some level of disclosure owed to the
| consumer. Not sure what it would be.
| satvikpendem wrote:
| I wonder if this is simply how brains evolved too, because we
| also are multi-modal, and parts of our brain are specifically
| used for different tasks such that damage in those parts impedes
| completing said task (while still having some level of
| neuroplasticity where the brain could try to recover by remolding
| its neural architecture).
|
| I would not be surprised to see something similar when looking
| inside the structure of a multi-modal neural network, where
| certain parts handle certain tasks and other parts handle other
| tasks.
| tabtab wrote:
| GPT4 is already out? I just got GTP3. "You bought the wrong bot,
| silly head!": https://www.youtube.com/watch?v=EdRMVhlNP5I
| 29athrowaway wrote:
| Each time a new innovation takes place there will be a website
| talking nonsense about AGI that will get millions of ad print
| revenue.
|
| Don't click.
| z3c0 wrote:
| > In the lead up to GPT-4, Sam Altman hinted at higher pricing
| for smarter models
|
| I think this is all you really need to know about the future of
| _AGI_.
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