I’m not getting into angels and pinheads, but modern ML has the ability to perform “fuzzy analysis,” and interpret results in a far more flexible manner, than ever before.
They may not be able to match an MIT Ph.D, at analyzing experimental feedback, but they can probably match a lot of research assistants.
It’s like having a billion RAs, all running experiments, and triaging the results. I understand that is how they have made such good progress on medicines, with AI.
> “I have not failed. I've just found 10,000 ways that won't work.”
The CPU/GPU is to an LLM kinda like axons and dendrites are to the human brain: just a low-level implementation detail. The main crux of an LLM is what happens at a higher level.
The machine-level instructions being executed are just matrix multiplications. Billions of them. The complexity of LLM behavior is emergent from that.
They may not be able to match an MIT Ph.D, at analyzing experimental feedback, but they can probably match a lot of research assistants.
It’s like having a billion RAs, all running experiments, and triaging the results. I understand that is how they have made such good progress on medicines, with AI.
> “I have not failed. I've just found 10,000 ways that won't work.”
-Attributed to Thomas Edison