

Thanks that sounds interesting, will have a listen. Mapping human cognition to what’s likely represented with the stuff stored in neurons is very tricky but also quite intriguing.


Thanks that sounds interesting, will have a listen. Mapping human cognition to what’s likely represented with the stuff stored in neurons is very tricky but also quite intriguing.


Model output can look like human reasoning however they often ignore these intermediate steps and the output tokens are often filler designed to allow more context to load. There something there that’s half way to reasoning because it’s loading that related training data but it not a connected chain of thought as we do. I read this article about it a few weeks ago and it summarizes the current research.
https://www.quantamagazine.org/is-ai-reasoning-right-for-the-wrong-reasons-20260731/


You can replace all the ‘reasoning’ steps from an LLMs output with “please wait” and it will still supply the same final answer. We think but LLMs just throw up connected bits of their training. Which was stolen from human reasoning in the first place. They are an illusion of thought at best and a malfunctioning search engine most of the time.
Which would be fine if it was additional renewable power that was added to the grid and generated by those same corporations or a subsidiary. But how unlikely is that. Keeping the profits but making average people pay for your environmental damage, that’s just business as normal. Same issue as with government AI promises here.