You ever go through a wignats posts and realize dude can literally be eviscerated out of existence and nobody would remember because any LLM diarrhea generator can produce anything of more substance 
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@subnetter incidentally I was arguing with Opus 4.8 and it's really good at looking at your arguments and picking apart if they have methodological flaws. I've found it really useful
@sun okay but what do you actually mean by methodological flaws because I cannot imagine LLMs actually being able to map out that logic considering they're token predictors and the correctness of an argument is determined by its validity
And sorry, everyone keeps saying stuff about LLM this and that, if it's run by the same incestuous pool of sociopaths I want nothing to do with the product. I'm good. I like my life the way it is without promoting a chat bot regularly for a dopamine rush.
I will never be at any point in my life where I am trying to have conversations with myself through an LLM. I studied philosophy logic quite a bit, that's something I should do and a skill I would like to continue to refine, not delegate to a clanker.
And sorry, everyone keeps saying stuff about LLM this and that, if it's run by the same incestuous pool of sociopaths I want nothing to do with the product. I'm good. I like my life the way it is without promoting a chat bot regularly for a dopamine rush.
I will never be at any point in my life where I am trying to have conversations with myself through an LLM. I studied philosophy logic quite a bit, that's something I should do and a skill I would like to continue to refine, not delegate to a clanker.
@subnetter there is a metric fuckton of secret sauce layered over top of LLMs and I think that is the difference. I don't have a good explanation for why sometimes LLMs seem to work unreasonably good at tasks that don't seem at all like they are solvable with token prediction.
So as an example I made a statement of fact and it pushed back. I elucidated further and got more concessions and pushback, but it accused me of, whenever a wrinkle in my argument appeared, I just expanded the scope of the cause until I started with a very small testable thing and ended up with a worldwide conspiracy. And I go back through my conversation and that is in fact exactly what I did. So again I don't know why it was able to detect that, based on "stochastic parrot mathematics" but it worked good enough to correct me, who was actually trying to use human logic and failing.
So as an example I made a statement of fact and it pushed back. I elucidated further and got more concessions and pushback, but it accused me of, whenever a wrinkle in my argument appeared, I just expanded the scope of the cause until I started with a very small testable thing and ended up with a worldwide conspiracy. And I go back through my conversation and that is in fact exactly what I did. So again I don't know why it was able to detect that, based on "stochastic parrot mathematics" but it worked good enough to correct me, who was actually trying to use human logic and failing.
@sun @subnetter this effect is not because the LLM has secret sauce, it's because you haven't thought hard enough about how what it does is pattern matching and fuzzy correlation between a and b
for me they consistently cannot elucidate holes in actual formal arguments that _require_ step-by-step reasoning to respond to, because they are incapable of that, but ofc looser statements about politics or world events they can generate seemingly meaningful output in response to
for me they consistently cannot elucidate holes in actual formal arguments that _require_ step-by-step reasoning to respond to, because they are incapable of that, but ofc looser statements about politics or world events they can generate seemingly meaningful output in response to
@whiteline @subnetter @sun there has been some work to bodge around this. mostly involving having them write their own tool calls (emit a script, run in sandbox, interpret result) and in the math prover space (where its writing terms to HOL or Lean to verify) but it's not common
@icedquinn @subnetter @whiteline people have multiple times used it to solve complex zk problems. obviously it's using "tricks" to do that. But, it did in fact solve problems that people did not yet. If there was just an LLM, the number of times it could do that would be "zero".
@sun @subnetter @whiteline i think you're going to run in to issues because the theorem provers still rely on lean to compile and verify the lemmas. so it works in that regard. but you still have to teach them to actually reformulate arguments *as logical lemmas* for the computer to then validate, and translate between the math and prose somewhere.
i'm sure its possible. it's still not an AGI--transformers never will do that--but at least that rig would be capable of reason.
i'm sure its possible. it's still not an AGI--transformers never will do that--but at least that rig would be capable of reason.
@icedquinn @subnetter @whiteline yeah pure llms can't really problem solve and hacks on top of them may have success but there's clearly upper bounds to that
@sun @subnetter @whiteline i never had the hardware or cash to get lost in the weird LLM bodge game. 
i did design a neuromorphic model that still needs testing, and i saw KANs have some really promising optimizations recently. but the transformer meta is just fighting losing math battles with money.
i did design a neuromorphic model that still needs testing, and i saw KANs have some really promising optimizations recently. but the transformer meta is just fighting losing math battles with money.
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