[dave1010uk]

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.

[embedding-shape]

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.

[adastra22]

Not that they wanted more money personally, but that they needed more money for compute.

[peterdsharpe]

"Financially, what will take me to $1B?" -Greg Brockman, August 2017

[arvid-lind]

> 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?

[mycall]

Don't all nonprofits need more money to improve their sustainment?

[nativeit]

Maybe, but somehow I doubt the American Heart Association is planning to open a chain of pork barbecue restaurants to support its mission against heart disease.

[gizajob]

Trivial to imagine everyone switching to Anthropic or Google or on-device LLMs.