An AI Primer with Wojciech Zaremba

Hey, today we have voice check Zaremba, and we're going to talk about AI. So, Voiture, could you give us a quick background?

I'm a founder at OpenAI, and I'm working on robotics. I think that deep learning and AI is a great application for robotics. Prior to that, I spent a year at Google Brain and I spent a year at Facebook Research. And I graduated from, I had finished my PhD at NYU.

Can you explain how you pulled that off? The team is pretty rare.

So, the great thing about both of these organizations is that they are focused on research. So throughout my PhD, I was actually publishing papers over there. I highly recommend both organizations, as well as, of course, OpenAI.

Yeah, okay. So most people probably don't know what OpenAI is, so could you just give that explanation?

Oh, OpenAI focuses on building AI for the good of humanity. We are a group of researchers and engineers collaborating together who essentially try to figure out what are the missing pieces of articles of general artificial intelligence and how to build it in a way that would be maximally beneficial to humanity as a whole. OpenAI is greatly supported by Elon Musk and Sam Altman, and in total, we gathered an investment of 1 billion dollars, a group, which is quite a lot.

I know some, but what are the OpenAI projects?

So there are several large projects going on simultaneously. We are also doing basic research. So let me first enumerate the large projects, and these are robotics.

So in terms of robotics, we are working on manipulation. We think that manipulation is complex; it's one of the parts of robotics which is the most unreal.

Sorry, just to clarify, what does that mean exactly?

It means that in robotics, there are essentially three major families of tasks. One is locomotion, which means how to move from, let's say, how to walk, how to move from point A to point B.

The second is navigation. So you're moving in a complicated environment, such as, for instance, a flat or a building, and you have to figure out actually to which rooms you have visited before and where to go.

The last one is manipulation. This means you want to grasp an object, let's say, open an object, place objects in various locations. The third one is the one which is currently the most difficult.

So it turns out that when it comes to arbitrary objects, current robots are unable to just grab an arbitrary object. For any object, it's possible to hand code a single solution. So say, as long as, same factory had the same object again, I don't know, we are producing classes and there exist hand-coded solutions to it.

There is a way to write a program saying, "Let's play their hand in the middle of the class," and then "let's close it." But there is no way, so far, to write a program such that it would be able to grasp an arbitrary object.

Okay, gotcha. And then, just very quickly, the other OpenAI projects go on?

So another one has to do with playing a complicated computer game, and the third one has to do with linking a large number of computer games.

You might ask why it's interesting, and in some sense, we would like to see.

A human has an incredible skill of being able to learn extremely quickly, and it has to do with prior experience. So let's say, even if you haven't played ever a volleyball, if you try it out for the first time, within 10 or 15 minutes, you would be able to grasp how to actually play.

And it has to do with all the prior experience that you have from different games. If you would put a child, like if you would put an infant on their volleyball court and ask him or her to play, they would fail miserably.

But, I mean, due to the fact that they have experience coming from a large number of other games or, let's say, other life situations, they are able to actually transfer all the knowledge.

So, at OpenAI, we are able to pull together a large number of computer games, and computer games can be, it's quite easy to quantify how good you are in the computer game.

Currently, the best AI system...