 Dear Fellow Scholars, this is two-minute papers with Kato Ejona Ifehir. This is a contest by OpenAI where a bunch of AI's compete to decide who has the best transfer learning capabilities. Transfer learning means that the training and the testing environment differs significantly, therefore only the AI's that learn general concepts prevail and the ones that try to get by with memorizing things will quickly fall. In this experiment, these programs start playing Sonic, the Hedgehog, and are given a bunch of levels to train on. However, like in a good test at school, the levels for the final evaluation are kept secret. So, the goal is that only high quality general algorithms prevail and we can cheat through the program as we don't know what the final exam will entail. We only know that we have to make the most of the training materials to pass. Sonic is a legendary platform game where we have to blaze through levels by avoiding obstacles and traps, often while traveling with the speed of sound. Here you can see the winning submission taking the exam on a previously unseen level. After one minute of training, as expected, the AI started to explore the controls, but is still quite inept and does not make any meaningful progress on the level. After 30 minutes, things look significantly better as the AI now understands the basics of the game. And look here, almost got up there and got it. It is clearly making progress as it collects some coins, defeats enemies, goes through the loop and gets stuck seemingly because it doesn't yet know how being underwater changes how high it can jump. This is quite a bit of a special case, so we are getting there. After only 60 to 120 minutes, it became a competent player and was able to finish this challenging map with only a few mistakes, really impressive transfer learning in just about an hour. Note that the algorithm has never seen this level before. Here you see a really cool visualization of three different AI's progress on the map, where the red dots indicate the movement of the character for earlier episodes and the bluer colors show the progress at later stages of the training. I could spend all day staring at these. Videos are available for many many submissions, some of which even opened up their source code and there are a few high quality write-ups as well, so make sure to have a look. There's gonna be lots of fun to be had there. This competition gives us something that is scientifically interesting, practical and super fun at the same time. What more could you possibly want? Huge thumbs up for the open AI team for organizing this and of course, congratulations to the participants. And now you see that we have a job where we train computers to play video games and we are even paid for it. What a time to be alive. By the way, if you wish to unleash the inner scholarly new, two minute paper shirts are available in many sizes and colors. We have max 2. The links are available in the video description. Thanks for watching and for your generous support, and I'll see you next time.