red75prime

Ancient bacteria will be surprised to encounter penicillin. Viruses are less resistant to degradation. But, yeah, it's nothing to look forward to, horizontal gene transfer and all.

The first paper (free-tier chatbots) due to fake references, the second paper (a specialized AI-research tool) due to overreliance on preprints.

This reminds me of "Autonomous driving? Ahhhh! There will be a bloodbath!"

Then I'd just marvel at your all-encompassing knowledge.

> The subagent is just as intelligent

Isn't it a common practice to use cheaper models to do the grunt work?

My initial comment was tongue in cheek (but transparent enough I think, given the context). So, let's be clear. I questioned whether it's still true that it's people who are doing all the HR work at Microsoft without LLM assistance.

You, probably, talk about something else.

"We" as in "industry in general" or "we" as in "HR at my company"? Although, I'd be more interested in what Microsoft does.

Maybe something has changed between now and then? Say, some kind of a technology that allows to select eligible employees better.

> LLMs do not replicate brain functionality.

Oh! Do you know how does the brain function? Heck, we don't know in detail how LLMs do their thing. The trivial observation that the brain in not a Turing machine is irrelevant if we are talking about functionality and not computational substrate.

But a Turing machine that implements functionality of a target system is the information-theoretical optimal compression of the data produced by the target system. So it stands to reason that LLMs that need to compress vast amounts of data approximate such a machine.

> C++ is Turing complete. Hell, HTML+CSS is Turing complete.

This is absolutely irrelevant to the question of the limits of LLM training. It's a common surface-level patter matching response, though.

> There's a very obvious and immediate one: availability and size of training data. And compute. And time.

Yeah, practical limitations. And practical results like seven hundred solved math problems show that you need, at least, to stop and think.

> What does quantum computation have to do with brains or LLMs?

If you have to ask that, it means that you haven't dug into all this mess deep enough. Basically, BQP computational complexity class is more powerful than P-class. If the brain employs such computations (although we don't know the appropriate quantum algorithms, so it's just wishful thinking mostly), the corresponding Turing machine is impractically large and slow.

> Says the person who just listed a lot of beliefs in marketing bullshit.

Nah. Learn more.

Obviously, error rate of ChatGPT should be measured by comparing to human diagnoses and when it plateaus, we should investigate a possibility that the number is driven mostly by human errors.

Replicating the brain functionality is magic? Or the brain itself is magic, so we need magic to replicate its functionality? Nah, learn more.

An LLM with CoT is Turing-complete, so there's no wall to its capabilities. There's no theorems that establish limits of reinforcement learning either. There's no evidence of quantum computations in the brain.

All you have is a strong belief.

The server doesn't respond right now (2026-10-25T05:30:00Z). What happened?

The wallet is at $2,016.73

> it already works very well.

Peephole optimization that can't be made global due to combinatorial explosion?

Do you know why are you downvoted? "Stochastic parrot" is so out of touch with reality that you are a perfect example of the human gullibility.