> To make AI more general, you just make the input tokenization more granular, change the training method, and perhaps add some kind of iterative framework on t

> To make AI more general, you just make the input tokenization more granular, change the training method, and perhaps add some kind of iterative framework on top to make it do more stuff. It's probably a bigger step than that. For example humans learn from experience, current AIs are trained offline and then frozen and can only "learn" by stuffing their short term memory with notes, like someone with anterograde amnesia. AI technology is changing each year, and AGI will probably be more different from today's transformer-based systems than they were from convolutional nets. But it will probably incorporate ideas and components from today's LLMs, and just as importantly, it's development will probably be paid for from the pockets of investors who have been tantalized by today's AI and think AGI must soon follow. I personally hope it's a long way off but it might only be a few key insights away at this point.