I'm impressed that such a short post can be so categorically incorrect. > For years, despite functional evidence and scientific hints accumulating, certain AI researchers continued to claim LLMs were stochastic parrots > In 2025 finally almost everybody stopped saying so. There is still no evidence that LLMs are anything beyond "stochastic parrots". There is no proof of any "understanding". This is seeing faces in cl…
The RL claims are also odd because, for starters, RLHF is not "reinforcement learning" based on any classical definition of RL (which almost always involve an online component). And further, you can chat with anyone who has kept up with the RL field, and quickly realize that this is also a technology that still hasn't quite delivered on the promises it's been making (despite being an incredibly interesting area of research). There's no reason to speculate that RL techniques will work with "agents" where they have failed to achieve wide spread success in similar domains.
I continue to be confused why smart, very technical people can't just talk about LLMs honestly. I personally think we'd have much more progress if we could have conversations like "Wow! The performance of a Markov Chain with proper state representation is incredible, let's understand this better..." rather than "AI is reasoning intelligently!"
I get why non-technical people get caught up in AI hype discussions, but for technical people that understand LLMs it seems counter productive. Even more surprising to me is that this hype has completely destroyed any serious discussions of the technology and how to use it. There's so much oppurtunity lost around practical uses of incorporating LLMs into software while people wait for agents to create mountains of slop.