LLMs alone aren't the way to AGI. Perhaps something involving a merge of diffusion or other models that are based on more sensory elements, like images, time, and motion, but LLMs alone aren't going to get us there.
The end of the exponential means the start of other models.
> LLMs alone aren't the way to AGI
Pretraining + RL works, there is no clear evidence that it doesn't scale further.
Pretraining + RL itself is the scaling limit. If you feed it the entire dataset before 1905, LLMs aren't going to come up with general relativity. It has no concept of physics, or time even.
AGI happens when you DON'T need to scale pertaining + RL.
> If you feed it the entire dataset before 1905, LLMs aren't going to come up with general relativity.
Link?
You don't need a source for that, an LLM with such little data is barely able to form proper sentences.
> an LLM with such little data
There is a mountain of data pre-1905. Certainly enough to train a decent 30B parameter model.
Now, digitizing & OCRing all of that data... THAT is a challenge.
AGI maybe not, but it is reaching disruption level intelligence in the SWE domain.