1. Solve reinforcement learning.
2. solve unsupervised learning.
3. gradually tackle more complicated things.
> what was the "real reason" they couldn't achieve their original goals?
I assume this is referring to why they gave up being a non-profit. The answer is that they needed more money.
Huh, I guess ML people weren't aware of "divide and conquer" that has been successfully employed in software engineering since basically forever?
> I assume this is referring to why they gave up being a non-profit. The answer is that they needed more money.
Ugh, that was more boring than even I expected, thanks a lot for saving me the time though, seems avoiding watching the full thing was worth it.
> The answer is that they needed more money.
isn't it still an odd choice for a nonprofit? it's hard to imagine a world without OpenAI and ChatGPT now, but at some point they decided being the best is most important. and presumably most profitable, since why just need a little more money?