• 6 Posts
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Joined 3 years ago
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Cake day: August 29th, 2023

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  • He describes textbook insane cult stuff, but still feels the need to say stuff like:

    Again I’ll say: there was a great deal of good at MAPLE.

    The way I’ve described it to friends is that it was the best decision I ever made to go there; the second best, however, being to leave.

    There was the same dynamic in the writing of the ex-leverage member that got posted here a few weeks ago. She also felt the need to emphasize the “good” parts. Is the cult programming that hard to break? Is it some form of sunk cost or rationalization or need to claim something positive about the experience?





  • The blogger simultaneously elevates mathematics to some mystical endeavor and fixates on novel theorem proving as the key element of that and believes LLM-based AI will replace human mathematicians at theorem proving in a matter of years… that is quite a combination. I can imagine how 1.5 of those things fit together (although I disagree with that view point obviously), but the whole package is really quite an odd combination.

    Also, in the fantasy scenarios where AI really is capable of totally replacing mathematicians, aren’t we supposed to get post-scarcity abundance, freeing up your time to pursue mathematics out of pure desire for enlightenment? Maybe the blogger doesn’t believe that part? Or they are so attached to themselves personally getting to discover novel theorems first they don’t care that the post-scarcity era would on net free up a lot more people to pursue pure mathematics as a hobby.



  • Great article! I think everyone here is probably already well aware of the way Silicon Valley keeps deliberately misunderstanding sci-fi for their hype (don’t invent the torment nexus), but this article does a good job wrapping together a lot of examples.

    And I realized this website is also the place where a year ago I read a great article on the history of nanotech as a real science vs. Drexler’s fantasies (the magic nanobot lesswrong still believes in) The Nanobots pipedream. So it looks like a pretty good newsletter, I might keep an eye on it going forward!







  • (2) has a big “if” in there

    Its a super big if, but it is one lesswrong (and Anthropic, with their “model welfare” pseudoscience) is allegedly seriously considering as a possibility (since, you know, they think LLMs are already AGI and Eliezer was accusing AI-dungeon, you know, GPT-2, of deliberately scheming). If anything, it speaks to some possible hypocrisy/motivated reasoning that they consider LLMs AGI but not possibly morally relevant.

    conceptualized capitalism

    This seems to be a lesson most lesswrongers have had rubbed in their faces repeatedly over the past 5 years with everything about LLM company’s behavior, but they just don’t want to learn.







  • I believe the main ingredient is Lean, which is a formal language resembling a programming language. Math proofs written in Lean can be verified deterministically with a computer, which really helps mitigate the hallucination problems of LLMs.

    100% this. Also, looking back at an earlier example that was actually written up in more detail, AlphaGeometry 1 got 28/30 problems, but entirely stripping out the LLM from the system, the symbolic logic proportion alone could get 14/30, and replacing the LLM with different heuristic methods could get 18/30 and 21/30 (for different methods).

    Even if math research works out perfectly well (which is a still big if), it’s not going to pay the bills. They would need to find a use case in the real world, where hallucinations can cause serious damage and cannot be formally prevented. And they have certainly tried. Math will not change the fact that all of this will collapse.

    The boosters and LLM companies still believe LLMs get their current level of performance by generalizing and not just memorizing facts (and maybe a wide shallow pool of weak heuristics). So they are hoping by pushing the LLM performance up in some narrow domain they can churn out synthetic data for, they will see some large general improvements in LLM performance.