Have a sneer percolating in your system but not enough time/energy to make a whole post about it? Go forth and be mid - welcome to the Stubsack, your first port of call for learning fresh Awful you’ll near-instantly regret.

Any awful.systems sub may be subsneered in this subthread, techtakes or no.

If your sneer seems higher quality than you thought, feel free to cut’n’paste it into its own post — there’s no quota for posting and the bar really isn’t that high.

The post Xitter web has spawned so many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

Like, there was one dude a while back who insisted that women couldn’t be surgeons because they didn’t believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I can’t escape them, I would love to sneer at them.

last week’s edition

  • scruiser@awful.systems
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    14 hours ago

    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.