DeepMind’s New AI: History In The Making!

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DeepMind’s New AI: History In The Making!

Two Minute Papers 23.06.2023 217 810 просмотров 7 519 лайков

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Оглавление (6 сегментов)

Intro

Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér. Wow. This is a historic moment today. Let me tell you why. DeepMind just introduced their new system called AlphaDev and it is based on something they call AlphaZero. AlphaZero was an AI system that could learn to play Chess, Go, and Shogi by playing against itself. So how good is it? Well, it is incredible.

What is Alpha Zero

And I really mean that, this is an AI that can beat world champions in these games. Now I hope you allow me to quote myself from about 400 videos ago: “The point of AlphaZero is not to solve Chess, or any of these games. Its main point is to show that a general AI can be created that can perform on a superhuman level on not one, but several different tasks at the same time. “ It can learn as long as we formulate the problem as a video game. For instance, it is easy to think about Chess like we think about a game, because that’s exactly what it is. If you win, you get some points, if you lose, you lose some points. Simple. However, what their new AI, AlphaDev does is computer coding. Excuse me, what? How is coding a video game? Yes, it really imagines computer coding as a video game. You see, in the case of sorting numbers, the computer game level will be a series of numbers, and the actions that we perform with a controller in a game will be writing code. If this code is written well, it will sort these numbers correctly, in which case, oh yes, that’s right, we get a nice score. But let’s add a twist to the game: latency. Correctness is necessary, but the faster the code, the higher the score. I love it. Coding as a video game. That sounds nice. However, I doubt it will be

Sorting

able to say anything new as sorting is a very well studied area in computer science. This is one of the first things every computer scientist starts learning about and there are hundreds and hundreds of algorithms published in this area. I don’t expect that this will be able to say anything truly new here, but if it can at least match what humans can do, that would be nice.

Performance

And…what? Look at that! Am I dreaming or is this real? On shorter sequences, it is up to 70% faster, and even on big workloads, it is about 1. 7% faster than the currently used techniques. My goodness! And if that is at all possible, it gets even better. Get this, they have deployed it into the LLVM libc++ sorting library. What does that mean? Well,

Stack Transfer

hold on to your papers Fellow Scholars, because it likely means that it is now being used more than a trillions times a day. Wow. If someone finds out something new and useful in the area of physical manufacturing, it might very well take decades for a paper to see any use in the real world. However, here, we are going from paper to product not in decades, and not even in years. This is tech transfer in a matter of days. And this is an AI that can say, I got this, don’t worry about it. Just tell me what you wish to see, and I’ll write this software on my own. And don’t forget, this is a difficult game. It is like constructing a skyscraper…from scratch! One wrong move, and you are done. And it is not just as good as the collective intelligence of humanity, but it even exceeds it. My goodness. What a time to be alive! And interestingly, it also doesn’t write C++, but it writes Assembly code directly, this roughly means that it is really low to the ground. This is a bit closer to the metal, the hardware itself. Proper coding skills from an AI that even rivals humans.

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