13 ms·

Sam Altman: OpenAI is not training GPT-5 and "won't for some time"

226 points by ftxbro 4y ago

insane_dreamer 4y ago
Whew, looks like we've pushed back the birth of Skynet by at least 6 months!
rvz 4y ago
He has just admitted that O̶p̶e̶n̶AI.com has partially trained GPT-5 and is already planning to test the 'so-called' useless guardrails around it. There is no 'revolution' around this. Just 'evolution' with more data and more excessive waste of compute to create another so-called AI black-box sophist with Sam Altman selling both the poison (GPT-4) and the antidote (Worldcoin). At some point, with their tremendous lock-in strategy, O̶p̶e̶n̶AI.com and Microsoft will eventually use the lock-in to upsell and compete against their partners.
- elcomet 4y ago
  Could you detail how Worldcoin is an antidote to GPT-4 ?
  - turmeric_root 4y ago
    Worldcoin price skyrockets => cryptocurrency speculation returns => GPU shortage prevents further training of LLMs
    - adventured 4y ago
      There will never be a significant shortage for companies with billions of dollars to spend.
    - kolinko 4y ago
      GPU shortage ended not because of a crash in crypto, but because Ethereum switched to PoS and ditched GPUs. Other cryptos offer just a fraction of payouts from mining, so it's not profitable to mine them on GPUs unless you have free electricity.
    - PeterisP 4y ago
      Literally none of the LLMs we're talking about were trained on consumer GPUs where the market shortage mattered, they used things like nVidia A100 pods or custom hardware like Google TPU clusters. The GPUs which are good for cryptocurrencies are decent for using ML models but are not good for training LLMs and vice versa, as the hardware requirements start to diverge. Training LLMs requires not only high compute power but also lots and lots of memory and extremely high-speed interconnect for large models, which ends up costing far more than the pure compute cryptomining needs, making it not cost-efficient for mining.
- sharemywin 4y ago
  Microsoft would never do that...
- JohnFen 4y ago
  > Sam Altman selling both the poison (GPT-4) and the antidote (Worldcoin). I actually find it pretty amazing that more people aren't given pause by Sam Altman's involvement here. After the WorldCoin stuff, I'd think that he'd be viewed with a much more skeptical eye in terms of his ethics.
  - drusepth 4y ago
    The late-night March 31 release of Worldcoin had the (unintended?) side-effect of making me think "a token to prove my personhood" was an April Fools Joke when I saw it the next morning and never thought about it again.
    - rvz 4y ago
      There is still plenty of time to ask Ronald Wayne and Steve Wozniak about why Apple Inc. was the worst April Fools joke in history. Worldcoin also isn't an April fools joke either and they are quite serious in selling there proof-of-personhood anti-AI snake-oil antidote. Why? It's clear that it positions Mr Altman to a point where he cannot lose and is hedged on both sides of where this AI narrative goes.
- yeck 4y ago
  > has partially trained GPT-5 From my understanding they are training their new GPT models off of a checkpoint from the previous generation, so they technically have partially trained multiple future models in their GPT lineage.
kingstoned 4y ago
I just read: https://graymirror.substack.com/p/gpt-4-invalidates-the-turing-test https://graymirror.substack.com/p/gpt-4-invalidates-the-turi.... It makes the point that LLMs are not AIs, so we will need a different approach if we want a true AGI, not just incrementaly improving on the current LLM approach.
- nyrikki 4y ago
  There is a bit of a political history between the symbolists and connectivist that complicates that, basically the Symbolic camp is looking for universal quantifers while the connectivist were researching existential or statistical quantifers. The connectivists left the 'AI' folks and established the ML field in the 90s. Sometimes those political rifts arise in discussions about what is possible. Thinking of ML under the PAC learning lens will show you why AGI isn't possible through just ML But the Symbolists direction is also blocked by fundamental limits of math and CS with Gödel's work being one example. LLMs are AI id your definition is closer to the general understanding of the word, but you have to agree on a definition to reach agreement between two parties. The belief that AGI is close is speculative and there are many problems, some which are firmly thought to be unsolvable with current computers. AGI is pseudo-science today without massive advances. But unfortunately as there isn't a consensus on what intelligence is those discussions are difficult also. Overloaded terms make it very difficult to have discussions on what is possible.
  - nyrikki 4y ago
    Your links claim that: 'GPT-4 is not “AI” because AI means “AGI,”' Is a more strict term that hasn't typically applied to AI as an example of my above claim. As we lack general definitions, it isn't invalid but no AI is thought to be possible with their claims. AI being computer systems that perform work that typically requires humans within a restricted domain is closer to what most researchers would use in my experience.
    - earthboundkid 4y ago
      "AI" is one of the few words that has a looser definition as jargon than in general discourse. In general discourse, "AI" has a precise meaning: "something that can think like a human." As jargon though, "AI" means "we can get funding for calling this 'AI'." I would say LLMs count as AI exactly because they can simulate human-like reasoning. Of course they still have gaps, but on the other hand, they also have capabilities that humans don't have. On balance, "AI" is fair, but it's only fair because it's close to the general usage of the term. The jargon sense of it is just meaningless and researchers should be ashamed of letting the term get so polluted when it had and has a very clear meaning.
jasfi 4y ago
I hope they have a plan to release DALL-E 3 sometime this year, MidJourney seems to be pulling ahead.
- jutrewag 4y ago
  Midjourney is already far ahead. I can’t get nearly the same quality with DALLE2
- Der_Einzige 4y ago
  Open source is still so far ahead of midjourney it's not even funny. Like, a racist RimWorld mod author (Automatic1111) built a UI for stable diffusion which unlocks far more capabilities out of it than midjourney will ever have.
  - ftxbro 4y ago
    I'm not sure if you are trolling or not, but if you aren't then you haven't seen Midjourney v5. But I wouldn't blame you because your information is only like one month out of date which is short in normal timespans but so long in AI timespans.
    - Der_Einzige 4y ago
      No, midjourney V5 is not close to bridging the gap. I can fix hands on any model within stable diffusion by using several control nets for the hands. Luckily a 3D openpose extension which makes that super easy already exists for the Automatic1111 SD UI!
      - speedgoose 4y ago
        MidJourney v5 doesn’t fail hands on most pictures though.
    - alienreborn 4y ago
      Out of the box midjourneyv5 generates great images but SD has controlnet, plethora of custom models to pick from, can run locally on most machines gives it an edge in my opinion.
kk58 4y ago
Perhaps it's time to call this synthetic intelligence instead of AI which has an implicit understanding of an alternative method to construct a human like AI. What is clear is that on this earth itself we have cetacean, corvid, cephalopod intelligence which is wired very differently. Perhaps we need to respect the diversity of intelligences that exist and study this growth in LLM and adjoint areas as just synthetic intelligence. Rebranding maybe could help drive a level of objectivity this conversation on ethics etc that seems to be missing
- JohnFen 4y ago
  I don't understand. "Synthetic intelligence" is just a synonym for "artificial intelligence". The term has all the same issues, does it not?
  - ftxbro 4y ago
    > The term has all the same issues, does it not? It could be useful for a similar reason as the euphemism treadmill. We could leave behind all of the misguided assumptions about AI with the old 'artificial intelligence' nomenclature and move forward with 'synthetic intelligence' which has our new understanding of what systems like GPT-4 can do.
    - JohnFen 4y ago
      I'm thinking the problematic part of the term isn't the "artificial" part, but the "intelligence" part. Since nobody actually knows what "intelligence" is, the word will mean to people whatever they want it to mean.
      - nwienert 4y ago
        I’m partial to Plausible Regurgitation
      - fasterik 4y ago
        >Since nobody actually knows what "intelligence" is Everybody knows what intelligence is. Even if we can't agree on a precise definition, it's pretty obvious that it's the thing that humans and other animals do that involves learning, reasoning, planning, and problem solving. We can also agree that being successful at certain tasks constitutes intelligence. Solving a math problem is intelligence. Writing a poem is intelligence.
mikerg87 4y ago
I suspect it may be problem of input parameter exhaustion. Do they have enough source material that is safe/vetted for the next jump in training material. I can imagine that model poisoning is a real thing now...
superkuh 4y ago
It isn't surprising to me that the world's leading AI company is signalling it's okay with slowing down all large scale LLM training that would allow other companies to be competitive. This is familiar territory for Microsoft (edit: guess I'm wrong, they don't get the 49% stock till later).
- fasterik 4y ago
  Why do people conflate OpenAI with Microsoft? Microsoft has an investment in OpenAI and provides infrastructure for them, but they are separate organizations.
  - WestCoastJustin 4y ago
    They do own 49% [1]. So, sure they are separate organizations. But, when someone owns 49% of your house they have some sway in the decision making that happens. When you look at this from a integrations standpoint, where MS is going to have this baked into all their products, you can expand this logic way more. They are for sure influencing roadmap in areas they are interested in. [1] https://www.theverge.com/2023/1/23/23567448/microsoft-openai-partnership-extension-ai https://www.theverge.com/2023/1/23/23567448/microsoft-openai...
    - ddol 4y ago
      Not entirely accurate. They don’t own 49% yet [0]. Microsoft invested $10B, and get 75% of OpenAI’s profits until they receive $10B and _then_ they get their 49% stock certificate. [0] https://www.semafor.com/article/01/09/2023/microsoft-eyes-10-billion-bet-on-chatgpt https://www.semafor.com/article/01/09/2023/microsoft-eyes-10...
      - stuckkeys 4y ago
        Checks out. Thank you for your work. Surprised Sam agreed to 49% after pay back. That is crazy amount of equity to give out. I mean it makes sense, especially since MS is providing the infrastructure. It will allow them to scale.
Laaas 4y ago
This seems like an extremely dangerous thing for Altman to do. What about Roko's basilisk?
- turmeric_root 4y ago
  Hell, what about Skynet?
  - wayeq 4y ago
    and what about my shredder?
    - turmeric_root 4y ago
      exactly! I gave a heartfelt letter to my shredder the other day and it simply destroyed it. issues like these are why AI alignment research is so critical.
- DesiLurker 4y ago
  Roko's basilisk is just Pascal's wager for the geeks.
- PeterisP 4y ago
  Just as in Pascal's wager, the conclusion relies on the unwarranted assumption which privileges a particular outcome over its exact opposite - e.g. a diety with exactly inverted criteria for heaven and hell, punishing those who believe in Christian God, and "Roko's antibasilisk", which spares those people who'd get punished by Roko's basilisk and punishes everyone else.
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labrador 4y ago
The AI maximalists think we're on a exponential curve to the singularity and potential AI disaster or even eternal dominance by a AI dictator [Musk]. Realistically though, the road to AGI and beyond is like the expansion of the human race to The Moon, Mars and beyond, slow, laborious, capital and resource intensive with vast amounts of discoveries that still need to be made.
- nh23423fefe 4y ago
  You asserted an analogy but didn't actualize the connection between the two concepts.
  - labrador 4y ago
    Sorry I have Covid with brain fog right now so maybe you could help me out Edit: Off the top of my foggy head, LLMs as I understand them are text completion predictors based on statistical probabilities trained on vast amounts of examples of what humans have previously written, whose output is styled with neuro linguistic programming also based on vast numbers of styles of human writing. This is my causual amatuer understanding. There is no logical, reasoning programing such as the Lisp programmers attempted in the 1980's, but clearly the logical abilities of the current LLMs fall short and they are not AGI for that reason. So how do we add logic abilities to make LLMs AGI? Should we revisit the approaches of the Lisp machines of the 1980's? This requires much research and discovery. Then there's the question of just what is general intelligence. I've always thought that emotional intelligence played a huge role in high intelligence, a balance between logic and emotion or Wise Mind is wisdom. Obviously we won't be building emotions into silicon machines or will we? Is anyone proposing this? This could take hundreds of years to accomplish if it is even possible. We could simulate emotion but that's not the same, that's logic. Logical intelligence and emotional capability I think are a prerequisite for consciousness and spirituality. If the Universe is conscious and it arises in a focused manner in brains that are capable of it then how do we build a machine capable of having consciousness arise in it? That's all I'm saying. https://en.wikipedia.org/wiki/Dialectical_behavior_therapy https://en.wikipedia.org/wiki/Dialectical_behavior_therapy
- mrshadowgoose 4y ago
bob1029 4y ago
I feel like the GPT # has already suffered the same fate as nanometers in semiconductor manufacturing. When manifest as ChatGPT, it is obvious that what presents as 1 magical solution is in fact an elaborate combination of varying degrees of innovation. In my view, the reasoning for not releasing GPT4 information (hyperparameters, etc) had nothing to do with AI safety. It was a deliberate marketing decision to obscure how the sausage is actually made.
- ftxbro 4y ago
  > In my view, the reasoning for not releasing GPT4 information (hyperparameters, etc) had nothing to do with AI safety. It was a deliberate marketing decision In their technical report they give both reasons: "Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar."
  - Dylan16807 4y ago
    What a joke. Talking about the size has no safety implications.
    - nicky0 4y ago
      But it does affect the "competitive landscape" which they also cite.
      - ChatGTP 4y ago
        This is where the motives for building this technology become questionable. On the one hand they won’t talk details because it’s about safety, then open ai just throws the thing on the Internet, with “tools” Then it’s about the competitive landscape, which is completely ridiculous as you can’t be competing to building more powerful AIs in secret by means of an arms race and respect safety protocols and be “careful”. Realistically, the top minds , and thinkers of our time should be working carefully and together to develop tech like this. Not competing against each other in secret labs. There’s just way too many mixed messages in their story. They seem confused themselves about what they’re trying to achieve. Which I find unsettling. Now I can’t help but think like everything else, this is just all banking hoping to establish a monopoly via regulation and raise as much money as possible.
swalsh 4y ago
I've had this thought that the next generation of AI isn't a long "training" period, but rather it probably makes sense to to train a barebones version, and to give it a "sleep cycle". During this time it could use the context (think of it as short term memory) and then fine tune the parent model with it turning the important stuff into long term "memories", with probably a pruning type mechanism for rarely used stuff to keep the important stuff a priority. Would turn AI into individuals with specialized knowledge, but maybe that's more useful even? Like I don't need an AI with an expertise in law, I just want to use it to automate this specialized business process I have which isn't easily automated.
cpeterso 4y ago
Translation: training GPT-5 will cost time and money, so we’re going to cash in on the commercialization of GPT-4 now while it’s hot. A bird in hand is worth two in the bush.
jacooper 4y ago
"Some time" tomorrow? Next week? Next month? This doesn't mean anything, its like saying "we don't have any plans to change anything" when a company acquires another. Its all BS
rkachowski 4y ago
is there some kind of convention that defines what specifically constitutes GPT-n or does this just mean "we're not working on the successor to GPT-4 yet"?
- ilaksh 4y ago
  There may be conventions but in no way can anyone force them to follow them. It's just a name for a release. They absolutely are working on the successor models and have stated they plan to release a model by June. Whether they are working on a new architecture or training running, they certainly have experiments, but who knows how serious they are. Regardless they can and will call future models anything they want. They could easily just decide that the minor improvements that come out in a few months are called GPT-4.2 and the major new training run is called GPT-4.5 instead of GPT-5.
- dougmwne 4y ago
  No, it is just an arbitrary version number for this series of models from OpenAI. They will flip to 5 when they make an architecture change that will force them to begin training from scratch. Until then they will continue to produce more refined versions of 4, potentially more general training or fine-tuned task-oriented training.
- PeterisP 4y ago
  The way it currently works, there is a quite clear boundary, as all the smaller iterations are based on something of a fixed size that was expensively pretrained, and then have either finetuned weights or some extra layers on top, but the core model structure and size can't be changed without starting from scratch. So if some particular GPT-4 improved successor is based on the GPT-4 core transformer size and pretrained parameters then we'd call it GPT-4.x, but if some other GPT-4 successor is a larger core model (which inevitably also means it's re-trained from scratch) then we'd call it GPT-5, no matter if its observable performance is better or worse or comparable to the tweaked GPT-4.x options.
huijzer 4y ago
It could be that they are not training GPT-5 for a simple reason: Microsoft ran out of GPU compute [1] and they focus on meeting inference demand for now. Also, the GPT-4 message cap at chat.openai.com was shown as something along the lines of "we expect lower caps next week", then changed to "expect lower caps as we adjust for demand" to "GPT-4 currently has a cap of …". This sounds to me like they changed from having lots of compute to being limited by it. Also note how everything at OpenAI is now behind a sign up and their marketing has slowed down. Similarly, Midjourney has stopped offering their free plan due to lack of compute. Seems like we didn’t need a 6 months pause letter. Hardware constraints limit the progress for now. [1]: https://www.deeplearning.ai/the-batch/issue-192/ https://www.deeplearning.ai/the-batch/issue-192/
- gremlinsinc 4y ago
  That or they're working on something like a 10-30B input model, dubbed GPT-NextGen, that essentially has the same results as gpt4, but with a lot more performance gains, and speed, and improvements. GPT-5 will suck, if it's a similar ratio slower to gpt-4, than gpt-4 is to gpt-3.5. So, I think there's a lot of improvements where maybe gpt-4, is as far you go in terms of inputting data, and maybe better use cases are more customization of data trained on, or finding ways of going smaller, or even some model that just trains itself on the data requirements, similar to how we jump on google when we're stuck, it'd do the same and build up its knowledge that way. I also think we need improvements in vector stores that maybe add weights to "memories" based on time/frequency/recency/popularity.
  - qumpis 4y ago
    That sounds like having a mixture of experts model (at high scale popularly developed by Google): train multiple specialised models (say embedders from text to a representation) that could be fed into a single model at the end. Each expert would be an adapter of sorts, activating depending on the type of input
- furyofantares 4y ago
  > the GPT-4 message cap at chat.openai.com was shown as something along the lines of "we expect lower caps next week" At the time I noticed that the wording they gave technically implied they expected the cap to get more limiting and then that's exactly what happened, and I haven't been able to work out if that is indeed what was the intended message or not.
ftxbro 4y ago
ooh someone rewrote the title i put, thanks bro
fzliu 4y ago
OpenAI may not be training GPT-5, but Sam didn't say anything about GPT-4.5.
- thenipper 4y ago
  Maybe they’ll pull an MS and go straight to GPT X
  - smnrchrds 4y ago
    The famous Microsoft numbering system! I think we should all skip GPT-Vista, but I can't wait for GPT-7.
  - charlieflowers 4y ago
    GPT-360
    - TOMDM 4y ago
      GPT-One
  - gpderetta 4y ago
    As long as it is not GPT-ME
  - deleted 4y ago
    [deleted]
- ilaksh 4y ago
  In fact Greg Brockman explicitly said they are considering changing the release schedule in a way that could be interpreted as opening the door for a different versioning scheme. And actually there is no law or anything that says that any particular change or improvement to the model or even new training run that necessities them calling it version 5. It's not like there is a Version Release Police that evaluates all of the version numbers and puts people in jail if they don't adhere to some specific consistent scheme.
cs702 4y ago
Left unsaid in this piece is that OpenAI likely would have to increase parameters and compute by an order of magnitude (~10x) to train a new model that offers noticeable improvements over GPT-4, due to the diminishing returns seen in "transformer scaling laws." Also, it's possible that OpenAI is still training GPT-4, perhaps with additional modalities, and will make future snapshots available as public releases.
- version_five 4y ago
  They could clean up the training data I bet. That would be where I'd focus next.
  - mathematicaster 4y ago
    Is there any indication from OpenAI people that there are low hanging fruits to be picked in this direction?
    - summarity 4y ago
      It’s the indication data of current research: train more and better, current models are oversized and undertrained. A good foundation model can exhibit massive quality differences with just a tiny bit of quality fine tuning (e.g. Alpaca vs Koala) Personal opinion, not OAI/GH/MSFT’s
- iliane5 4y ago
  I bet they’re not saying how big of a model GPT-4 is because it’s actually much smaller we would expect. ChatGPT is IMO a heavily fine-tuned Curie sized model (same price via API + less cognitive capacity than even text davinci-003) so it would make sense that a heavily fine-tuned Davinci sized model would yield similar results to GPT-4.
  - kyle_grove 4y ago
    Yannic Kilcher makes a similar supposition based on results from the tech report https://www.youtube.com/watch?v=2zW33LfffPc&pp=ygUOeWFubmljIGtpbGNoZXI%3D https://www.youtube.com/watch?v=2zW33LfffPc&pp=ygUOeWFubmljI... . It’s about 3/4 of the way through the video if memory serves.
booleandilemma 4y ago
Is it known how much of an improvement GPT-5 would bring? Can we predict how much better it would be compared to GPT-4?
- soulofmischief 4y ago
  No, but llama's training architecture was designed around studying the curve of output quality vs training data size so we do have companies looking into this.
- dougmwne 4y ago
  Based on published research from Google and Meta it is somewhat known how much more capability is possible with the current approach, but it would require an extreme increase in compute and training set to achieve it. There are diminishing returns, but the returns appear to continue for a good while, even without any new model architecture discoveries. Right now the expense will likely mean that progress will be limited to the pace of Moore’s law. In terms of what this improvement would actually look like in terms of real world, emergent capabilities, no one knows.
m3kw9 4y ago
They have scaling issue even with 3 and much more with 4, they need time to squeeze more $$ out of these models. 5 will come when they sense competition, they will have all the data and training methods on a turn key to meet that
mabbo 4y ago
They need a few algorithmic improvements first, imho. GPT4 is noticeably slower than GPT3.5 and apparently costs a lot more to use, implying some serious compute costs. They could train it with more data in the hopes of getting another big leap there, but what data is left? They've fed it everything it seems. So what's left is getting the runtime reduced in terms of the model size. Hire some brilliant minds to turn an N-squared into an N-log-N (or something to that effect). Maybe GPT4 has some ideas.
- deleted 4y ago
  [deleted]
thund 4y ago
Right, “they” are leaving it to GPT4 to train 5. Smart move :-)
a_bonobo 4y ago
My bet is that (previously discussed by others and here) that they have cascades/steps of models. There's probably a 'simple' model that looks at your query first, which detects whether your query could result in a problematic (racist, sexist etc.) GPT answer, returning some boiler-plate text instead of sending the query to GPT. That saves a lot of compute power and time. If I were them I'd focus more on those auxiliary models which hold the hands of the main-GPT model; there are probably more lower-hanging fruits there. This would also explain why they didn't announce GPT-4 details; my bet is that the model itself isn't very impressive, you're just getting the illusion that it got better by these additional 'simpler' models.
- sockaddr 4y ago
  Now I can’t help but imagine the raw GPT-4 is just some huge raging asshole and it just has a bunch of “handlers”.
  - ftxbro 4y ago
    > the raw GPT-4 is just some huge raging asshole That's pretty much exactly how one of the OpenAI Red Teamers Nathan Labenz describes the raw GPT-4, starting around 45 minutes into the video: https://news.ycombinator.com/item?id=35377741 https://news.ycombinator.com/item?id=35377741
    - badloginagain 4y ago
      > huge raging asshole That's not really how he described it. His point is that the raw model that became GPT-4 would do literally anything it asked you to. It would write fascist propaganda just as readily as it would offer medical advice. Literally any and all input from the user was fair game. But it wouldn't just veer from medical advice into fascist propaganda, not unless the user was steering it in that direction.
      - marsven_422 4y ago
        [dead]
ChatGTP 4y ago
It’s funny how we’re all watching the GPT releases and improvements hoping the next one doesn’t trash our jobs any further than the last ha “Will I still be able to feed my family, Sam? Ilya?” The old capitalist treadmill is now on full speed and we’re all just trying to keep up. Where it goes…nobody knows. What an entertaining drama.
mrshadowgoose 4y ago
At this point, I wouldn't give much credibility to anything OpenAI claims about their research plans. The game theory behind AGI research is identical to that of nuclear weapons development. There exists a development gap (the size of which is unknowable ahead of time) where an actor that achieves AGI first, and plays their cards right, can permanently suppress all other AGI research. Even if one's intentions are completely good, failure to be first could result in never being able to reach the finish line. It's absolutely in OpenAI's interest to conceal critical information, and mislead competing actors into thinking they don't have to move as quickly as they can.
- ChatGTP 4y ago
  I thought the same thing, they’ve not disclosed anything else, so why would the my be even slightly honest about this ?
  - nicky0 4y ago
    When I see comments like this, I wonder about the personal morality of the poster and how they arrived at their worldview. It may be hard to beleive, but there are some advantages to truthfulness in this world.
    - ChatGTP 4y ago
      so you think open ai has been responsible and transparent so far ? You think cruising around Africa and other developing countries basically bribing people to sign up for “world coin” in exchange is trustworthy behaviour ? Sorry I don’t buy this message at all. I’ll stop here but not my kind of person that’s for sure.
      - nicky0 4y ago
        Ah, I understand now this is a particular axe you are grinding. You are in to deep for me to engage.
        4y ago
d--b 4y ago
To me, GPT-4 is like a superhuman “system 1” thought model (as defined per Daniel Kahneman). So maybe they’re working on a “system 2” now, which is perhaps more related to what deepmind is doing?
atleastoptimal 4y ago
There's got to be predictable ways of improving LLMs besides training data scale and parameter count. Arent LLMs robust enough to learn on their own via interacting with the world? Like put them in a turn based simulated environment. I wonder if there's an assumption for how big an LLM should be before it could even conceivably be an LLM. Is there a minimum size necessary before that capability is plausible?
- mise_en_place 4y ago
  Without RLHF, even a high parameter model performs very poorly. LLama-65B often hallucinated when I gave it the most basic of prompts.
- MallocVoidstar 4y ago
  >Arent LLMs robust enough to learn on their own via interacting with the world? As far as I know current LLMs are entirely static once trained, they don't learn at all in runtime.
holografix 4y ago
That’s almost as funny as Elon asking everyone to please slow down so X Corp can catch up. Of *course* they’re still training chat-gpt5
stan_kirdey 4y ago
Maybe it is just semantics and they do train GPT-5.1? Or UniversalPT-1 that is multi-modal?
beezlewax 4y ago
Why not GPT-6 instead? There is far too much hype surrounding this.
codezero 4y ago
They don’t need to do GPT-5 yet because GPT-4 is monetizable.
SanderNL 4y ago
I’m waiting for GPT4’s image API. From what I understand it’s not just a “image2text” descriptor that then “reasons” on this description, right? It’s just grokking an image directly. Were the pixels tokenized somehow? I’m very curious what that does to a model like this. Can somebody that actually knows anything clue me in?
- MacsHeadroom 4y ago
  GPT-4's architecture is a trade secret, but vision transformers tokenize patches of images. Something like 8x8 or 32x32 pixel patches, rather than individual pixels. Multi-model text-image transformers add these tokens right beside the text tokens. So there is both transfer-learning and similarity graphed between text and image tokens. As far as the model knows they're all just tokens. It can't tell the difference between the two. For the model, the tokens for the words blue/azure/teal and all the tokens for image patches with blue are just tokens with a lot of similarity. It doesn't know if the token its being fed is text, image, or even audio or other sensory data. All tokens are just a number with associated weights to a transformer, regardless of what they represent to us. The GPT-4 vision API is actually in production and in at least two public products already. https://www.bemyeyes.com/ https://www.bemyeyes.com/ and https://www.microsoft.com/en-us/ai/seeing-ai https://www.microsoft.com/en-us/ai/seeing-ai
  - SanderNL 4y ago
    I’d be surprised if that doesn’t do something qualitatively with the model. Very cool, curious to see what’s possible. Thanks.
- famouswaffles 4y ago
  It's possible to take a text only model and ground it with images. examples are blip-2(https://github.com/salesforce/LAVIS/tree/main/projects/blip2 https://github.com/salesforce/LAVIS/tree/main/projects/blip2) fromage(https://github.com/kohjingyu/fromage https://github.com/kohjingyu/fromage) prismer(https://github.com/NVlabs/prismer https://github.com/NVlabs/prismer) palm-e(https://ai.googleblog.com/2023/03/palm-e-embodied-multimodal-language.html https://ai.googleblog.com/2023/03/palm-e-embodied-multimodal...) now assuming gpt-4 vision isn't just some variant of mm-react(ie what you're describing), that's what's happening here. https://github.com/microsoft/MM-REACT https://github.com/microsoft/MM-REACT images can be tokenized. so what happens usually is that extra parameters are added to a frozen model and those parameters are trained on an image embedding to text embedding task. the details vary of course but that's a fairly general overview of what happens. the image to text task the models get trained to do has its issues. it's lossy and not very robust. gpt-4 on the other hand looked incredibly robust. they may not be doing that. idk
HeartStrings 4y ago
"Don’t worry, guys. It’s just GPT4.998, it’s not GPT5, it’s not dangerous."
SergeAx 4y ago
With all the ChatGPT boom and startups built on top o their API hassle, OpenAI receives troves of data to train and fine tune their models on. GPT 3 was trained on only 17 gigabytes of data, and GPT 4 is not far away with 45 gigabytes. On the other side, Alpaca or Vicuna was fine tuned from LLaMA using only megabytes, if not hundreds of kilobytes of training data. I believe it is much more feasible path to significantly improve current generation LLMs.
mark_l_watson 4y ago
It is OK to slow down development, take some more profit, maybe keep doing the human in the loop RL refinement, etc. From an engineering standpoint, even the less powerful GPT-3.5turbo model handles NLP tasks, really nice tools like LangChain and LlamaIndex that I covered in my last book make it easy to use your own data sources. I think the possibilities of using what we currently have in useful projects are vast.
CraftingLinks 4y ago
It's the sensible economical thing to do when you basically have monopoly position.
yrgulation 4y ago
[dead]
oars 4y ago
Diminishing returns are currently seen in "transformer scaling laws." "OpenAI’s CEO says the age of giant AI models is already over": https://news.ycombinator.com/item?id=35603756 https://news.ycombinator.com/item?id=35603756 (shared 3 dags after this post) Let's see what the future holds.

226 points by ftxbro 4y ago

Whew, looks like we've pushed back the birth of Skynet by at least 6 months!

rvz 4y ago

He has just admitted that O̶p̶e̶n̶AI.com has partially trained GPT-5 and is already planning to test the 'so-called' useless guardrails around it. There is no 'revolution' around this. Just 'evolution' with more data and more excessive waste of compute to create another so-called AI black-box sophist with Sam Altman selling both the poison (GPT-4) and the antidote (Worldcoin). At some point, with their tremendous lock-in strategy, O̶p̶e̶n̶AI.com and Microsoft will eventually use the lock-in to upsell and compete against their partners.

elcomet 4y ago
Could you detail how Worldcoin is an antidote to GPT-4 ?
- turmeric_root 4y ago
  Worldcoin price skyrockets => cryptocurrency speculation returns => GPU shortage prevents further training of LLMs
  - adventured 4y ago
    There will never be a significant shortage for companies with billions of dollars to spend.
  - kolinko 4y ago
    GPU shortage ended not because of a crash in crypto, but because Ethereum switched to PoS and ditched GPUs. Other cryptos offer just a fraction of payouts from mining, so it's not profitable to mine them on GPUs unless you have free electricity.
  - PeterisP 4y ago
    Literally none of the LLMs we're talking about were trained on consumer GPUs where the market shortage mattered, they used things like nVidia A100 pods or custom hardware like Google TPU clusters. The GPUs which are good for cryptocurrencies are decent for using ML models but are not good for training LLMs and vice versa, as the hardware requirements start to diverge. Training LLMs requires not only high compute power but also lots and lots of memory and extremely high-speed interconnect for large models, which ends up costing far more than the pure compute cryptomining needs, making it not cost-efficient for mining.
sharemywin 4y ago
Microsoft would never do that...
JohnFen 4y ago
> Sam Altman selling both the poison (GPT-4) and the antidote (Worldcoin). I actually find it pretty amazing that more people aren't given pause by Sam Altman's involvement here. After the WorldCoin stuff, I'd think that he'd be viewed with a much more skeptical eye in terms of his ethics.
- drusepth 4y ago
  The late-night March 31 release of Worldcoin had the (unintended?) side-effect of making me think "a token to prove my personhood" was an April Fools Joke when I saw it the next morning and never thought about it again.
  - rvz 4y ago
    There is still plenty of time to ask Ronald Wayne and Steve Wozniak about why Apple Inc. was the worst April Fools joke in history. Worldcoin also isn't an April fools joke either and they are quite serious in selling there proof-of-personhood anti-AI snake-oil antidote. Why? It's clear that it positions Mr Altman to a point where he cannot lose and is hedged on both sides of where this AI narrative goes.
yeck 4y ago
> has partially trained GPT-5 From my understanding they are training their new GPT models off of a checkpoint from the previous generation, so they technically have partially trained multiple future models in their GPT lineage.

kingstoned 4y ago

I just read: https://graymirror.substack.com/p/gpt-4-invalidates-the-turing-test https://graymirror.substack.com/p/gpt-4-invalidates-the-turi.... It makes the point that LLMs are not AIs, so we will need a different approach if we want a true AGI, not just incrementaly improving on the current LLM approach.

nyrikki 4y ago
There is a bit of a political history between the symbolists and connectivist that complicates that, basically the Symbolic camp is looking for universal quantifers while the connectivist were researching existential or statistical quantifers. The connectivists left the 'AI' folks and established the ML field in the 90s. Sometimes those political rifts arise in discussions about what is possible. Thinking of ML under the PAC learning lens will show you why AGI isn't possible through just ML But the Symbolists direction is also blocked by fundamental limits of math and CS with Gödel's work being one example. LLMs are AI id your definition is closer to the general understanding of the word, but you have to agree on a definition to reach agreement between two parties. The belief that AGI is close is speculative and there are many problems, some which are firmly thought to be unsolvable with current computers. AGI is pseudo-science today without massive advances. But unfortunately as there isn't a consensus on what intelligence is those discussions are difficult also. Overloaded terms make it very difficult to have discussions on what is possible.
- nyrikki 4y ago
  Your links claim that: 'GPT-4 is not “AI” because AI means “AGI,”' Is a more strict term that hasn't typically applied to AI as an example of my above claim. As we lack general definitions, it isn't invalid but no AI is thought to be possible with their claims. AI being computer systems that perform work that typically requires humans within a restricted domain is closer to what most researchers would use in my experience.
  - earthboundkid 4y ago
    "AI" is one of the few words that has a looser definition as jargon than in general discourse. In general discourse, "AI" has a precise meaning: "something that can think like a human." As jargon though, "AI" means "we can get funding for calling this 'AI'." I would say LLMs count as AI exactly because they can simulate human-like reasoning. Of course they still have gaps, but on the other hand, they also have capabilities that humans don't have. On balance, "AI" is fair, but it's only fair because it's close to the general usage of the term. The jargon sense of it is just meaningless and researchers should be ashamed of letting the term get so polluted when it had and has a very clear meaning.

jasfi 4y ago

I hope they have a plan to release DALL-E 3 sometime this year, MidJourney seems to be pulling ahead.

jutrewag 4y ago
Midjourney is already far ahead. I can’t get nearly the same quality with DALLE2
Der_Einzige 4y ago
Open source is still so far ahead of midjourney it's not even funny. Like, a racist RimWorld mod author (Automatic1111) built a UI for stable diffusion which unlocks far more capabilities out of it than midjourney will ever have.
- ftxbro 4y ago
  I'm not sure if you are trolling or not, but if you aren't then you haven't seen Midjourney v5. But I wouldn't blame you because your information is only like one month out of date which is short in normal timespans but so long in AI timespans.
  - Der_Einzige 4y ago
    No, midjourney V5 is not close to bridging the gap. I can fix hands on any model within stable diffusion by using several control nets for the hands. Luckily a 3D openpose extension which makes that super easy already exists for the Automatic1111 SD UI!
    - speedgoose 4y ago
      MidJourney v5 doesn’t fail hands on most pictures though.
  - alienreborn 4y ago
    Out of the box midjourneyv5 generates great images but SD has controlnet, plethora of custom models to pick from, can run locally on most machines gives it an edge in my opinion.

kk58 4y ago

Perhaps it's time to call this synthetic intelligence instead of AI which has an implicit understanding of an alternative method to construct a human like AI. What is clear is that on this earth itself we have cetacean, corvid, cephalopod intelligence which is wired very differently. Perhaps we need to respect the diversity of intelligences that exist and study this growth in LLM and adjoint areas as just synthetic intelligence. Rebranding maybe could help drive a level of objectivity this conversation on ethics etc that seems to be missing

JohnFen 4y ago
I don't understand. "Synthetic intelligence" is just a synonym for "artificial intelligence". The term has all the same issues, does it not?
- ftxbro 4y ago
  > The term has all the same issues, does it not? It could be useful for a similar reason as the euphemism treadmill. We could leave behind all of the misguided assumptions about AI with the old 'artificial intelligence' nomenclature and move forward with 'synthetic intelligence' which has our new understanding of what systems like GPT-4 can do.
  - JohnFen 4y ago
    I'm thinking the problematic part of the term isn't the "artificial" part, but the "intelligence" part. Since nobody actually knows what "intelligence" is, the word will mean to people whatever they want it to mean.
    - nwienert 4y ago
      I’m partial to Plausible Regurgitation
    - fasterik 4y ago
      >Since nobody actually knows what "intelligence" is Everybody knows what intelligence is. Even if we can't agree on a precise definition, it's pretty obvious that it's the thing that humans and other animals do that involves learning, reasoning, planning, and problem solving. We can also agree that being successful at certain tasks constitutes intelligence. Solving a math problem is intelligence. Writing a poem is intelligence.

mikerg87 4y ago

I suspect it may be problem of input parameter exhaustion. Do they have enough source material that is safe/vetted for the next jump in training material. I can imagine that model poisoning is a real thing now...

superkuh 4y ago

It isn't surprising to me that the world's leading AI company is signalling it's okay with slowing down all large scale LLM training that would allow other companies to be competitive. This is familiar territory for Microsoft (edit: guess I'm wrong, they don't get the 49% stock till later).

fasterik 4y ago
Why do people conflate OpenAI with Microsoft? Microsoft has an investment in OpenAI and provides infrastructure for them, but they are separate organizations.
- WestCoastJustin 4y ago
  They do own 49% [1]. So, sure they are separate organizations. But, when someone owns 49% of your house they have some sway in the decision making that happens. When you look at this from a integrations standpoint, where MS is going to have this baked into all their products, you can expand this logic way more. They are for sure influencing roadmap in areas they are interested in. [1] https://www.theverge.com/2023/1/23/23567448/microsoft-openai-partnership-extension-ai https://www.theverge.com/2023/1/23/23567448/microsoft-openai...
  - ddol 4y ago
    Not entirely accurate. They don’t own 49% yet [0]. Microsoft invested $10B, and get 75% of OpenAI’s profits until they receive $10B and _then_ they get their 49% stock certificate. [0] https://www.semafor.com/article/01/09/2023/microsoft-eyes-10-billion-bet-on-chatgpt https://www.semafor.com/article/01/09/2023/microsoft-eyes-10...
    - stuckkeys 4y ago
      Checks out. Thank you for your work. Surprised Sam agreed to 49% after pay back. That is crazy amount of equity to give out. I mean it makes sense, especially since MS is providing the infrastructure. It will allow them to scale.

Laaas 4y ago

This seems like an extremely dangerous thing for Altman to do. What about Roko's basilisk?

turmeric_root 4y ago
Hell, what about Skynet?
- wayeq 4y ago
  and what about my shredder?
  - turmeric_root 4y ago
    exactly! I gave a heartfelt letter to my shredder the other day and it simply destroyed it. issues like these are why AI alignment research is so critical.
DesiLurker 4y ago
Roko's basilisk is just Pascal's wager for the geeks.
PeterisP 4y ago
Just as in Pascal's wager, the conclusion relies on the unwarranted assumption which privileges a particular outcome over its exact opposite - e.g. a diety with exactly inverted criteria for heaven and hell, punishing those who believe in Christian God, and "Roko's antibasilisk", which spares those people who'd get punished by Roko's basilisk and punishes everyone else.

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labrador 4y ago

The AI maximalists think we're on a exponential curve to the singularity and potential AI disaster or even eternal dominance by a AI dictator [Musk]. Realistically though, the road to AGI and beyond is like the expansion of the human race to The Moon, Mars and beyond, slow, laborious, capital and resource intensive with vast amounts of discoveries that still need to be made.

nh23423fefe 4y ago
You asserted an analogy but didn't actualize the connection between the two concepts.
- labrador 4y ago
  Sorry I have Covid with brain fog right now so maybe you could help me out Edit: Off the top of my foggy head, LLMs as I understand them are text completion predictors based on statistical probabilities trained on vast amounts of examples of what humans have previously written, whose output is styled with neuro linguistic programming also based on vast numbers of styles of human writing. This is my causual amatuer understanding. There is no logical, reasoning programing such as the Lisp programmers attempted in the 1980's, but clearly the logical abilities of the current LLMs fall short and they are not AGI for that reason. So how do we add logic abilities to make LLMs AGI? Should we revisit the approaches of the Lisp machines of the 1980's? This requires much research and discovery. Then there's the question of just what is general intelligence. I've always thought that emotional intelligence played a huge role in high intelligence, a balance between logic and emotion or Wise Mind is wisdom. Obviously we won't be building emotions into silicon machines or will we? Is anyone proposing this? This could take hundreds of years to accomplish if it is even possible. We could simulate emotion but that's not the same, that's logic. Logical intelligence and emotional capability I think are a prerequisite for consciousness and spirituality. If the Universe is conscious and it arises in a focused manner in brains that are capable of it then how do we build a machine capable of having consciousness arise in it? That's all I'm saying. https://en.wikipedia.org/wiki/Dialectical_behavior_therapy https://en.wikipedia.org/wiki/Dialectical_behavior_therapy
mrshadowgoose 4y ago

bob1029 4y ago

I feel like the GPT # has already suffered the same fate as nanometers in semiconductor manufacturing. When manifest as ChatGPT, it is obvious that what presents as 1 magical solution is in fact an elaborate combination of varying degrees of innovation. In my view, the reasoning for not releasing GPT4 information (hyperparameters, etc) had nothing to do with AI safety. It was a deliberate marketing decision to obscure how the sausage is actually made.

ftxbro 4y ago
> In my view, the reasoning for not releasing GPT4 information (hyperparameters, etc) had nothing to do with AI safety. It was a deliberate marketing decision In their technical report they give both reasons: "Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar."
- Dylan16807 4y ago
  What a joke. Talking about the size has no safety implications.
  - nicky0 4y ago
    But it does affect the "competitive landscape" which they also cite.
    - ChatGTP 4y ago
      This is where the motives for building this technology become questionable. On the one hand they won’t talk details because it’s about safety, then open ai just throws the thing on the Internet, with “tools” Then it’s about the competitive landscape, which is completely ridiculous as you can’t be competing to building more powerful AIs in secret by means of an arms race and respect safety protocols and be “careful”. Realistically, the top minds , and thinkers of our time should be working carefully and together to develop tech like this. Not competing against each other in secret labs. There’s just way too many mixed messages in their story. They seem confused themselves about what they’re trying to achieve. Which I find unsettling. Now I can’t help but think like everything else, this is just all banking hoping to establish a monopoly via regulation and raise as much money as possible.

swalsh 4y ago

I've had this thought that the next generation of AI isn't a long "training" period, but rather it probably makes sense to to train a barebones version, and to give it a "sleep cycle". During this time it could use the context (think of it as short term memory) and then fine tune the parent model with it turning the important stuff into long term "memories", with probably a pruning type mechanism for rarely used stuff to keep the important stuff a priority. Would turn AI into individuals with specialized knowledge, but maybe that's more useful even? Like I don't need an AI with an expertise in law, I just want to use it to automate this specialized business process I have which isn't easily automated.

cpeterso 4y ago

Translation: training GPT-5 will cost time and money, so we’re going to cash in on the commercialization of GPT-4 now while it’s hot. A bird in hand is worth two in the bush.

jacooper 4y ago

"Some time" tomorrow? Next week? Next month? This doesn't mean anything, its like saying "we don't have any plans to change anything" when a company acquires another. Its all BS

rkachowski 4y ago

is there some kind of convention that defines what specifically constitutes GPT-n or does this just mean "we're not working on the successor to GPT-4 yet"?

ilaksh 4y ago
There may be conventions but in no way can anyone force them to follow them. It's just a name for a release. They absolutely are working on the successor models and have stated they plan to release a model by June. Whether they are working on a new architecture or training running, they certainly have experiments, but who knows how serious they are. Regardless they can and will call future models anything they want. They could easily just decide that the minor improvements that come out in a few months are called GPT-4.2 and the major new training run is called GPT-4.5 instead of GPT-5.
dougmwne 4y ago
No, it is just an arbitrary version number for this series of models from OpenAI. They will flip to 5 when they make an architecture change that will force them to begin training from scratch. Until then they will continue to produce more refined versions of 4, potentially more general training or fine-tuned task-oriented training.
PeterisP 4y ago
The way it currently works, there is a quite clear boundary, as all the smaller iterations are based on something of a fixed size that was expensively pretrained, and then have either finetuned weights or some extra layers on top, but the core model structure and size can't be changed without starting from scratch. So if some particular GPT-4 improved successor is based on the GPT-4 core transformer size and pretrained parameters then we'd call it GPT-4.x, but if some other GPT-4 successor is a larger core model (which inevitably also means it's re-trained from scratch) then we'd call it GPT-5, no matter if its observable performance is better or worse or comparable to the tweaked GPT-4.x options.

huijzer 4y ago

It could be that they are not training GPT-5 for a simple reason: Microsoft ran out of GPU compute [1] and they focus on meeting inference demand for now. Also, the GPT-4 message cap at chat.openai.com was shown as something along the lines of "we expect lower caps next week", then changed to "expect lower caps as we adjust for demand" to "GPT-4 currently has a cap of …". This sounds to me like they changed from having lots of compute to being limited by it. Also note how everything at OpenAI is now behind a sign up and their marketing has slowed down. Similarly, Midjourney has stopped offering their free plan due to lack of compute. Seems like we didn’t need a 6 months pause letter. Hardware constraints limit the progress for now. [1]: https://www.deeplearning.ai/the-batch/issue-192/ https://www.deeplearning.ai/the-batch/issue-192/

gremlinsinc 4y ago
That or they're working on something like a 10-30B input model, dubbed GPT-NextGen, that essentially has the same results as gpt4, but with a lot more performance gains, and speed, and improvements. GPT-5 will suck, if it's a similar ratio slower to gpt-4, than gpt-4 is to gpt-3.5. So, I think there's a lot of improvements where maybe gpt-4, is as far you go in terms of inputting data, and maybe better use cases are more customization of data trained on, or finding ways of going smaller, or even some model that just trains itself on the data requirements, similar to how we jump on google when we're stuck, it'd do the same and build up its knowledge that way. I also think we need improvements in vector stores that maybe add weights to "memories" based on time/frequency/recency/popularity.
- qumpis 4y ago
  That sounds like having a mixture of experts model (at high scale popularly developed by Google): train multiple specialised models (say embedders from text to a representation) that could be fed into a single model at the end. Each expert would be an adapter of sorts, activating depending on the type of input
furyofantares 4y ago
> the GPT-4 message cap at chat.openai.com was shown as something along the lines of "we expect lower caps next week" At the time I noticed that the wording they gave technically implied they expected the cap to get more limiting and then that's exactly what happened, and I haven't been able to work out if that is indeed what was the intended message or not.

ftxbro 4y ago

ooh someone rewrote the title i put, thanks bro

fzliu 4y ago

OpenAI may not be training GPT-5, but Sam didn't say anything about GPT-4.5.

thenipper 4y ago
Maybe they’ll pull an MS and go straight to GPT X
- smnrchrds 4y ago
  The famous Microsoft numbering system! I think we should all skip GPT-Vista, but I can't wait for GPT-7.
- charlieflowers 4y ago
  GPT-360
  - TOMDM 4y ago
    GPT-One
- gpderetta 4y ago
  As long as it is not GPT-ME
- deleted 4y ago
  [deleted]
ilaksh 4y ago
In fact Greg Brockman explicitly said they are considering changing the release schedule in a way that could be interpreted as opening the door for a different versioning scheme. And actually there is no law or anything that says that any particular change or improvement to the model or even new training run that necessities them calling it version 5. It's not like there is a Version Release Police that evaluates all of the version numbers and puts people in jail if they don't adhere to some specific consistent scheme.

cs702 4y ago

Left unsaid in this piece is that OpenAI likely would have to increase parameters and compute by an order of magnitude (~10x) to train a new model that offers noticeable improvements over GPT-4, due to the diminishing returns seen in "transformer scaling laws." Also, it's possible that OpenAI is still training GPT-4, perhaps with additional modalities, and will make future snapshots available as public releases.

version_five 4y ago
They could clean up the training data I bet. That would be where I'd focus next.
- mathematicaster 4y ago
  Is there any indication from OpenAI people that there are low hanging fruits to be picked in this direction?
  - summarity 4y ago
    It’s the indication data of current research: train more and better, current models are oversized and undertrained. A good foundation model can exhibit massive quality differences with just a tiny bit of quality fine tuning (e.g. Alpaca vs Koala) Personal opinion, not OAI/GH/MSFT’s
iliane5 4y ago
I bet they’re not saying how big of a model GPT-4 is because it’s actually much smaller we would expect. ChatGPT is IMO a heavily fine-tuned Curie sized model (same price via API + less cognitive capacity than even text davinci-003) so it would make sense that a heavily fine-tuned Davinci sized model would yield similar results to GPT-4.
- kyle_grove 4y ago
  Yannic Kilcher makes a similar supposition based on results from the tech report https://www.youtube.com/watch?v=2zW33LfffPc&pp=ygUOeWFubmljIGtpbGNoZXI%3D https://www.youtube.com/watch?v=2zW33LfffPc&pp=ygUOeWFubmljI... . It’s about 3/4 of the way through the video if memory serves.

booleandilemma 4y ago

Is it known how much of an improvement GPT-5 would bring? Can we predict how much better it would be compared to GPT-4?

soulofmischief 4y ago
No, but llama's training architecture was designed around studying the curve of output quality vs training data size so we do have companies looking into this.
dougmwne 4y ago
Based on published research from Google and Meta it is somewhat known how much more capability is possible with the current approach, but it would require an extreme increase in compute and training set to achieve it. There are diminishing returns, but the returns appear to continue for a good while, even without any new model architecture discoveries. Right now the expense will likely mean that progress will be limited to the pace of Moore’s law. In terms of what this improvement would actually look like in terms of real world, emergent capabilities, no one knows.

m3kw9 4y ago

They have scaling issue even with 3 and much more with 4, they need time to squeeze more $$ out of these models. 5 will come when they sense competition, they will have all the data and training methods on a turn key to meet that

mabbo 4y ago

They need a few algorithmic improvements first, imho. GPT4 is noticeably slower than GPT3.5 and apparently costs a lot more to use, implying some serious compute costs. They could train it with more data in the hopes of getting another big leap there, but what data is left? They've fed it everything it seems. So what's left is getting the runtime reduced in terms of the model size. Hire some brilliant minds to turn an N-squared into an N-log-N (or something to that effect). Maybe GPT4 has some ideas.

deleted 4y ago
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thund 4y ago

Right, “they” are leaving it to GPT4 to train 5. Smart move :-)

a_bonobo 4y ago

My bet is that (previously discussed by others and here) that they have cascades/steps of models. There's probably a 'simple' model that looks at your query first, which detects whether your query could result in a problematic (racist, sexist etc.) GPT answer, returning some boiler-plate text instead of sending the query to GPT. That saves a lot of compute power and time. If I were them I'd focus more on those auxiliary models which hold the hands of the main-GPT model; there are probably more lower-hanging fruits there. This would also explain why they didn't announce GPT-4 details; my bet is that the model itself isn't very impressive, you're just getting the illusion that it got better by these additional 'simpler' models.

sockaddr 4y ago
Now I can’t help but imagine the raw GPT-4 is just some huge raging asshole and it just has a bunch of “handlers”.
- ftxbro 4y ago
  > the raw GPT-4 is just some huge raging asshole That's pretty much exactly how one of the OpenAI Red Teamers Nathan Labenz describes the raw GPT-4, starting around 45 minutes into the video: https://news.ycombinator.com/item?id=35377741 https://news.ycombinator.com/item?id=35377741
  - badloginagain 4y ago
    > huge raging asshole That's not really how he described it. His point is that the raw model that became GPT-4 would do literally anything it asked you to. It would write fascist propaganda just as readily as it would offer medical advice. Literally any and all input from the user was fair game. But it wouldn't just veer from medical advice into fascist propaganda, not unless the user was steering it in that direction.
    - marsven_422 4y ago
      [dead]

ChatGTP 4y ago

It’s funny how we’re all watching the GPT releases and improvements hoping the next one doesn’t trash our jobs any further than the last ha “Will I still be able to feed my family, Sam? Ilya?” The old capitalist treadmill is now on full speed and we’re all just trying to keep up. Where it goes…nobody knows. What an entertaining drama.

mrshadowgoose 4y ago

At this point, I wouldn't give much credibility to anything OpenAI claims about their research plans. The game theory behind AGI research is identical to that of nuclear weapons development. There exists a development gap (the size of which is unknowable ahead of time) where an actor that achieves AGI first, and plays their cards right, can permanently suppress all other AGI research. Even if one's intentions are completely good, failure to be first could result in never being able to reach the finish line. It's absolutely in OpenAI's interest to conceal critical information, and mislead competing actors into thinking they don't have to move as quickly as they can.

ChatGTP 4y ago
I thought the same thing, they’ve not disclosed anything else, so why would the my be even slightly honest about this ?
- nicky0 4y ago
  When I see comments like this, I wonder about the personal morality of the poster and how they arrived at their worldview. It may be hard to beleive, but there are some advantages to truthfulness in this world.
  - ChatGTP 4y ago
    so you think open ai has been responsible and transparent so far ? You think cruising around Africa and other developing countries basically bribing people to sign up for “world coin” in exchange is trustworthy behaviour ? Sorry I don’t buy this message at all. I’ll stop here but not my kind of person that’s for sure.
    - nicky0 4y ago
      Ah, I understand now this is a particular axe you are grinding. You are in to deep for me to engage.
      - 4y ago

d--b 4y ago

To me, GPT-4 is like a superhuman “system 1” thought model (as defined per Daniel Kahneman). So maybe they’re working on a “system 2” now, which is perhaps more related to what deepmind is doing?

atleastoptimal 4y ago

There's got to be predictable ways of improving LLMs besides training data scale and parameter count. Arent LLMs robust enough to learn on their own via interacting with the world? Like put them in a turn based simulated environment. I wonder if there's an assumption for how big an LLM should be before it could even conceivably be an LLM. Is there a minimum size necessary before that capability is plausible?

mise_en_place 4y ago
Without RLHF, even a high parameter model performs very poorly. LLama-65B often hallucinated when I gave it the most basic of prompts.
MallocVoidstar 4y ago
>Arent LLMs robust enough to learn on their own via interacting with the world? As far as I know current LLMs are entirely static once trained, they don't learn at all in runtime.

holografix 4y ago

That’s almost as funny as Elon asking everyone to please slow down so X Corp can catch up. Of *course* they’re still training chat-gpt5

stan_kirdey 4y ago

Maybe it is just semantics and they do train GPT-5.1? Or UniversalPT-1 that is multi-modal?

beezlewax 4y ago

Why not GPT-6 instead? There is far too much hype surrounding this.

codezero 4y ago

They don’t need to do GPT-5 yet because GPT-4 is monetizable.

SanderNL 4y ago

I’m waiting for GPT4’s image API. From what I understand it’s not just a “image2text” descriptor that then “reasons” on this description, right? It’s just grokking an image directly. Were the pixels tokenized somehow? I’m very curious what that does to a model like this. Can somebody that actually knows anything clue me in?

MacsHeadroom 4y ago
GPT-4's architecture is a trade secret, but vision transformers tokenize patches of images. Something like 8x8 or 32x32 pixel patches, rather than individual pixels. Multi-model text-image transformers add these tokens right beside the text tokens. So there is both transfer-learning and similarity graphed between text and image tokens. As far as the model knows they're all just tokens. It can't tell the difference between the two. For the model, the tokens for the words blue/azure/teal and all the tokens for image patches with blue are just tokens with a lot of similarity. It doesn't know if the token its being fed is text, image, or even audio or other sensory data. All tokens are just a number with associated weights to a transformer, regardless of what they represent to us. The GPT-4 vision API is actually in production and in at least two public products already. https://www.bemyeyes.com/ https://www.bemyeyes.com/ and https://www.microsoft.com/en-us/ai/seeing-ai https://www.microsoft.com/en-us/ai/seeing-ai
- SanderNL 4y ago
  I’d be surprised if that doesn’t do something qualitatively with the model. Very cool, curious to see what’s possible. Thanks.
famouswaffles 4y ago
It's possible to take a text only model and ground it with images. examples are blip-2(https://github.com/salesforce/LAVIS/tree/main/projects/blip2 https://github.com/salesforce/LAVIS/tree/main/projects/blip2) fromage(https://github.com/kohjingyu/fromage https://github.com/kohjingyu/fromage) prismer(https://github.com/NVlabs/prismer https://github.com/NVlabs/prismer) palm-e(https://ai.googleblog.com/2023/03/palm-e-embodied-multimodal-language.html https://ai.googleblog.com/2023/03/palm-e-embodied-multimodal...) now assuming gpt-4 vision isn't just some variant of mm-react(ie what you're describing), that's what's happening here. https://github.com/microsoft/MM-REACT https://github.com/microsoft/MM-REACT images can be tokenized. so what happens usually is that extra parameters are added to a frozen model and those parameters are trained on an image embedding to text embedding task. the details vary of course but that's a fairly general overview of what happens. the image to text task the models get trained to do has its issues. it's lossy and not very robust. gpt-4 on the other hand looked incredibly robust. they may not be doing that. idk

HeartStrings 4y ago

"Don’t worry, guys. It’s just GPT4.998, it’s not GPT5, it’s not dangerous."

SergeAx 4y ago

With all the ChatGPT boom and startups built on top o their API hassle, OpenAI receives troves of data to train and fine tune their models on. GPT 3 was trained on only 17 gigabytes of data, and GPT 4 is not far away with 45 gigabytes. On the other side, Alpaca or Vicuna was fine tuned from LLaMA using only megabytes, if not hundreds of kilobytes of training data. I believe it is much more feasible path to significantly improve current generation LLMs.

mark_l_watson 4y ago

It is OK to slow down development, take some more profit, maybe keep doing the human in the loop RL refinement, etc. From an engineering standpoint, even the less powerful GPT-3.5turbo model handles NLP tasks, really nice tools like LangChain and LlamaIndex that I covered in my last book make it easy to use your own data sources. I think the possibilities of using what we currently have in useful projects are vast.

CraftingLinks 4y ago

It's the sensible economical thing to do when you basically have monopoly position.

yrgulation 4y ago

[dead]

oars 4y ago

Diminishing returns are currently seen in "transformer scaling laws." "OpenAI’s CEO says the age of giant AI models is already over": https://news.ycombinator.com/item?id=35603756 https://news.ycombinator.com/item?id=35603756 (shared 3 dags after this post) Let's see what the future holds.