601–610 of 644 posts
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Which is arguably a good thing (having AGI spread amongst multiple entities rather than one leader).
How is that good? An arms race increases the pressure to go fast and disregard alignment safety, non proliferation is essential.
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> question that requires logical reasoning This is the tough part to tell - are there any such questions that exist that have not already been asked? The reason Chat-GPT works is its scale. to me, that makes me question how "smart" it is. Even the most idiotic idiot could be pretty decent if he had access to the entire works of mankind and infinite memory. Doesn't matter if his IQ is 50, because you ask him something…
Of course there are such questions. When it comes to even simple puzzles, there are infinitely many permutations possible wrt how the pieces are arranged, for example - hell, you could generate such puzzles with a script. No amount of precanned training data can possibly cover all such combinations, meaning that the model has to learn how to apply the concepts that make solution possible (which includes things such a…
> we fundamentally changed how AI systems learn and reason through complex problems I'm not an AI researcher, have they done this? The commentary I've seen on o1 is basically that they incorporated techniques that were already being used. I'd also be curious to learn: what fundamental contributions to research has OpenAI made? The ChatGPT that was released in 2022 was based on Google's research, and IMO the internal…
Ilya was the Google researcher..
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Saying "it's just autocomplete" is not really saying anything meaningful since it doesn't specify the complexity of completion. When completion is a correct answer to the question that requires logical reasoning, for example, "just autocomplete" needs to be able to do exactly that if it is to complete anything outside of its training set.
> question that requires logical reasoning This is the tough part to tell - are there any such questions that exist that have not already been asked? The reason Chat-GPT works is its scale. to me, that makes me question how "smart" it is. Even the most idiotic idiot could be pretty decent if he had access to the entire works of mankind and infinite memory. Doesn't matter if his IQ is 50, because you ask him something…
I'm highly confident that the "adjacent possible" of what is achievable/discoverable today, leveraging what we already know, is constantly changing.
I'm highly confident that AGI will never reach superhuman levels of creativity and discovery if we model it only on artifacts representing what humans have done in the past, rather than modelling it on human brains and what we'll be capable of achieving in the future.
> we fundamentally changed how AI systems learn and reason through complex problems I'm not an AI researcher, have they done this? The commentary I've seen on o1 is basically that they incorporated techniques that were already being used. I'd also be curious to learn: what fundamental contributions to research has OpenAI made? The ChatGPT that was released in 2022 was based on Google's research, and IMO the internal…
Personal opinion: I think this means we've probably exhausted all the low hanging fruit in LLM land. This was the last thing I was reserving judgement for. When the most hyped up big idea openai has rn is basically "we're just gonna have the model dump out a massive wall of semi-optimized chain of thought every time and not send it over the wire" we're officially out of big ideas. Like I mean it obviously works... but that's more or less what we've _been_ doing for years now! Barring a total rethinking of LLM architecture, I think all improvements going forward will be baby steps for a while, basically moving at the same pace we've been going since gpt-4 launched. I don't think this is the path to AGI in the near term, but there's still plenty of headroom for minor incremental change.
By analogy, i feel like gpt-4 was basically the same quantum leap we got with the iphone 4: all the basic functionality and peripherals were there by the time we got iphone 4 (multitasking, facetime, the app store, various sensors, etc.), and everything since then has just been minor improvements. The current iPhone 16 is obviously faster, bigger, thinner, and "better" than the 4, but for the most part it doesn't really do anything extra that the 4 wasn't already capable of at some level with the right app. Similarly, I think gpt-4 was pretty much "good enough". LLMs are about as they're gonna get for the next little while, though they might get a little cheaper, faster, and more "aligned" (however we wanna define that). They might get slightly less stupid, but i don't think they're gonna get a whole lot smarter any time soon. Whatever we see in the next few years is probably not going to be much better than using gpt-4 with the right prompt, tool use, RAG, etc. on top of it. We'll only see improvements at the margins.
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That's not quite how o1 was trained, they say. o1 was trained specifically to perform reasoning. Or rather, it was trained to reproduce the patterns within internal monologues that lead to correct answers to problems, particularily STEM problems. While this still uses text at some level, it's no longer regurgitation of human-produced text, but something more akin to AlphaZero's training to become superhuman at games…
> While this still uses text at some level, it's no longer regurgitation of human-produced text, but something more akin to AlphaZero's training to become superhuman at games like Go or Chess. How did you know that? I've never seen that anywhere. For all we know, it could just be a very elaborate CoT algorithm.
https://x.com/_jasonwei/status/1834278706522849788
Notice that the CoT is trained via RL, meaning the CoT itself is a model (or part of the main model).
Also, RL means it's not limited to the original data the way traditional LLM's are. It implies that the CoT processes itself is trained based on it's own performance, meaning the steps of the CoT from previous runs are fed back into the training process as more data.
Will probably start her own company and raise a billy like her old pal Iyla. I wouldn't blame her, there's been so many articles that technical people should just start their own company instead of being CTO.
Now I’m curious. Can you share some example articles please?
tl;dr If you're going to be a CTO or founding engineer, make sure you are getting well compensated, either through salary (which start-ups generally can't do) or equity (which the founder won't generally give away).
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Look at the sample chain-of-thought for o1-preview under this blog post, for decoding "oyekaijzdf aaptcg suaokybhai ouow aqht mynznvaatzacdfoulxxz". At this point, I think the "fancy autocomplete" comparisons are getting a little untenable. https://openai.com/index/learning-to-reason-with-llms/
It depends on how well you understand how the fancy autocomplete is working under the hood. You could compare GPT-o1 chain of thought to something like IBM's DeepBlue chess-playing computer, which used MTCS (tree search, same as more modern game engines such as AlphaGo)... at the end of the day it's just using built-in knowledge (pre-training) to predict what move would most likely be made by a winning player. It's n…
Bob McGrew, head of research just quit too. "I just shared this with OpenAI" https://x.com/bobmcgrewai/status/1839099787423134051 Barret Zoph, VP Research (Post-Training) "I posted this note to OpenAI." https://x.com/barret_zoph/status/1839095143397515452 All used the same template.
I wonder if this is just continued creative guerilla tactics to stir the "talk about them maybe finding AGI" pot.
That or we're playing an inverse Roko's Basilisk.