Comment by root_axis
4 days ago
If we had AGI we wouldn't need to keep spending more and more money to train these models, they could just solve arbitrary problems through logic and deduction like any human. Instead, the only way to make them good at something is to encode millions of examples into text or find some other technique to tune them automatically (e.g. verifiable reward modeling of with computer systems).
Why is it that LLMs could ace nearly every written test known to man, but need specialized training in order to do things like reliably type commands into a terminal or competently navigate a computer? A truly intelligent system should be able to 0-shot those types of tasks, or in the absolute worst case 1-shot them.
To add to this, previously one could argue that LLMs were on par with somewhat less intelligent humans and it was (at least I found) difficult to dispute. But now the frontier models can custom tailor explanations of technical subjects in the advanced undergraduate to graduate range. Simultaneously, I regularly catch them making what for a human of that level would be considered very odd errors in reasoning. When questioned about these inconsistencies they either display a hopeless lack of awareness or appear to attempt to deflect. They're also entirely incapable of learning from such an interaction. It feels like interacting with an empty vessel that presents an illusion of intelligence and produces genuinely useful output yet there's nothing behind the curtain so to speak.