Since LLMs are different between each other (and even version of the same family) I'd expect the differences to be explained by each lab idiosincratic biases in the post-training phase rather than by internet corpora characteristics during the pre-training phase.
Ah, over-the-top larger-than-life LLM-isms, they are really funny when you see them in a company blog, but they are vomitive when it's your coworker copy-pasting it and insisting you on reading it.
It adds liquidity for sure, and the option to actually exit. But the implication in these posts is often to exit a bad investment on the back of an ignorant public, explicitly stated in this post.
Is it really such an extraordinary claim to say that they could have solved the problem without copying Buckmaster and Alpoge? It seems very much in the realm of possibilities.
To me, it seems just as extraordinary to claim that they did "cheat". If I were a betting man, I would put the odds around 50/50 from everything I've read on the subject.
But my point is that everyone seems to be presuming guilt.
It is an extraordinary claim, it is a millenium prize problem after all. We don't even know, even if there was no copying, how much human involvement there was in the result.
I mean, a disaster could happen even with properly human-aligned AI. In a "AI makes the shots" world with undecipherable and fast feedback loops, which is the one we are seemingly heading towards, a string of short-sighted decisions made by AI agents may be the only thing separating us from extinction.
They represent different AI usage patterns. OpenAI wants everyone to believe that it was done with a practically autonomous network of thousands of agents with little to no human intervention for 88 hours, while Buckmaster/Alpöge were using AI in a more guided way for months. If OpenAI actually used anything from Buckmaster/Alpöge work they would be misleading the public.
Agree! Not sure I believe that Buckmaster/Alpöge were guiding the AI.
This is just their way of saying that they had something in the process and deserve merit.
Probably an AI-written Lean proof is very different to how a human would write it, and some may say it's more like mathy neuralese. For sure it works but it is not human-friendly and needs to be transformed into something more readable and digestible to be able to extract insights from it.
Not that different from when trying to read an out-of-control vibe coded codebases, or an sloppy AI long email that someone may send you at 9 AM.
Tao has a spiel in his recent interview with Dwarkesh where he says that AIs are very good at explaining things - so just have the AI explain the proof in a human-friendly way.
For sure, but this was supposedly ~18 million dollars of compute, afaik 100 pages paper / lean proof and only god knows how many bytes of chat interactions + thought traces. Scale matters.
I bet it can be decomposed quite nicely though. At the top level, there are probably only like five steps. Dig as deep as you want into any of those steps (i.e. engineering).
And since LLMs are apparently good at circumventing the absence of an API, there's not much incentive to add them now. APIs are for humans. LLMs just break through all the captchas and anti-bot measures.
Yes, but for humans it creates friction. Seeing a captcha makes me think twice and thrice if I really want to visit that site so badly that I'll endure the suckage. LLMs don't care, for them the friction doesn't exist.
For sure. Anyone who thinks that we're in the end state of what progress can be made simply lacks imagination. This is all going to keep changing and iterating for the rest of our natural lives. The only constant is change.
