Daniel Filan

Challenge: know everything that the best go bot knows about go

On a few different views, understanding the computation done by neural networks is crucial to building neural networks that constitute human-level artificial intelligence that doesn’t destroy all value in the universe. Given that many people are trying to build neural networks that constitute artificial general intelligence, it seems important to understand the computation in cutting-edge neural networks, and we basically do not.

So, how should we go from here to there? One way is to try hard to think about understanding, until you understand understanding well enough to reliably build understandable AGI. But that seems hard and abstract. A better path would be something more concrete.

Therefore, I set this challenge: know everything that the best go bot knows about go. At the moment, the best publicly available bot is KataGo, if you’re at DeepMind or OpenAI and have access to a better go bot, I guess you should use that instead. If you think those bots are too hard to understand, you’re allowed to make your own easier-to-understand bot, as long as it’s the best.

What constitutes success?

Why do I think this is a good challenge?

Corollaries of success (non-exhaustive):

Drawbacks of success:

Related work:

A conversation with Nate Soares on a related topic probably helped inspire this post. Please don’t blame him if it’s dumb tho.