Comment by tonii141
18 hours ago
a) Still true: vanilla LLMs can’t do math, they pattern-match unless you bolt on tools.
b) Still true: next-token prediction isn’t planning.
c) Still true: error accumulation is mitigated, not eliminated. Long-context quality still relies on retrieval, checks, and verifiers.
Yann’s claims were about LLMs as LLMs. With tooling, you can work around limits, but the core point stands.
My man, math is pattern matching, not magic. So is logic. And computation.
Please learn the basics before you discuss what LLMs can and can't do.
I'm no expert on math but "math is pattern matching" really sounds wrong.
Maybe programming is mostly pattern matching but modern math is built on theory and proofs right?
When an LLM does it, it's pattern matching.
RL training amounts to pattern matching.
How does an LLM decode Base64? Decode algorithm? No - predictive pattern matching.
An LLM isn't predicting what a person thinks - it's predicting what a person does.
Nah, its all pattern matching. This is how automated theorem provers like Isabelle are built, applying operations to lemmas/expressions to reach proofs.
2 replies →
a) no, gemini 2.5 was shown to "win" gold w/o tools. - https://arxiv.org/html/2507.15855v1
b) reductionism isn't worth our time. Planning works in the real world, today. (try any agentic tool like cc/codex/whatever). And if you're set on the purist view, there's mounting evidence from anthropic that there is planning in the core of an LLM.
c) so ... not true? Long context works today.
This is simply moving goalposts and nothing more. X can't do Y -> well, here they are doing Y -> well, not like that.
a) That "no-tools" win depends on prompt orchestration which can still be categorized as tooling.
b) Next-token training doesn’t magically grant inner long-horizon planners..
c) Long context ≠ robust at any length. Degradation with scale remains.
Not moving goalposts, just keeping terms precise.
My man, you're literally moving all the goalposts as we speak.
It's not just "long context" - you demand "infinite context" and "any length" now. Even humans don't have that. "No tools" is no longer enough - what, do you demand "no prompts" now too? Having LLMs decompose tasks and prompt each other the way humans do is suddenly a no-no?
2 replies →