~15 years ago I was active in the transhumanist* movement and went to conferences like the Singularity Summit. IIRC the tentative date we bounced around for when we would see rapid technological self-improvement was ~2038. I think we have just entered the first phase of the Singularity since a few weeks back. The LLMs are now capable of advances in maths and software development that can be used to make them even more capable. Rinse and repeat. This is a good thing. It is what will give us a "Star Trek future". *) NOT the silicon valley broligarch style. They weren't even hangarounds to the discussions back then and those I know are appalled at how they've shaped popular discourse on the subject since
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A hot take on the OpenAI math drop: the model's results are fundamentally a search across humanity's mathematical curiosities. This is user-data search + tools + deterministic verification, not a paradigm shift into superintelligence. I predict we will see the rate of new results slowing in the near future, reversing the 2026 trend.
When I'm thinking about AI in mathematics I end up thinking about the moon landings. It's not a perfect analogy. But there are some parallels. We tend to look back at them as a somewhat collective achievement of humanity; we're right to, I think. But the concentration of wealth in one place due to an arms race is what got us over the line. LLMs don't just stand on the shoulders of human mathematicians, they sort of *are* a distillation of everything we've written. And right now the AI industry is in a massive PR war.
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I think it's at least plausible that this period ends rather quickly, as the moon landings did. I wonder how many articles were written in 1969 about how we'd all be travelling to the moon one day. Another parallel is: what is the inherent value of putting someone on the moon? I think it's quite similar to a landmark theorem. It broadens our horizons, maybe even enables further research, but it doesn't have much to do with the price of fish. #ai #math #llm #science
Nevertheless it seems also clear that the #LLM is mimicking more than just bits and pieces of its training materials. One is taken with the sense that LLMs and the whole "Generative #AI" phenomenon are built to mimic how the typical #tech geek tends to solve problems--their intellectual approach to, well, everything basically, an intellectual approach practically devoid of intellect because its ultimate goal is to do away with thinking altogether. Thinking is time-consuming, emotionally expensive, and thus bad for #efficiency in the John Carmack or Elon Musk sense.
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The elite techlords don't want to do ANY of it; they want to think that correct decisions and infallible snap-assessments are just gushing out of them all the time, like they're wired directly into the Truth of All Things...like they're a prophet in other words. Ultimately this fallacy has a religious nature: the high-tech "gurus" (remember, they called themselves that appropriated religious word) really have become like a priesthood of Technology[tm], technology turned into an artificial magic system like in Isaac Asimov's Foundation. Which, you know, they probably think of as aspirational. If "thinking" is the word. It's this quality of instantaneous snap answers that has been impressed onto all the stochastic #GenAI thingummies. Of necessity the techlords are compelled to claim that their thing is (almost) supremely intelligent to a degree impossible for the puny human meatbrain to comprehend...because that's the only way to support the premise that the LLM isn't merely emitting trash but unparalleled wisdom. (more)
