Earlier quoted context omitted.
I don't get why some people seem to think the only way to use a LLM is for next token prediction or AGI has to be bult using LLM alone. You want planning, you can do monte carlo tree search and use LLM to evaluate which node to explore next. You want verifiable reasoning, you can ask it to generate code(an approach used by recent AI olympiad winner and many previous papers). What is even "planning", finding desirable…
The problem is that every time you ask the LLM to evaluate what to do next it will return a wrong answer X% of the time. Multiple that X across the number of steps and you have a system that is effectively useless. X today is ~5%. I do think LLMs could be used to assist in building a world model that could be a foundation for an AGI/agent system. But it won't be the major part.
Re: Overcoming the limits of current LLMs
#111absolutely