Erase Sign Presentation Mobile

Erase Sign Presentation Mobile

[indistinct shouting] - No steal. There's no steal there. I predict not a steal, watch this: ...and he stayed. [excited] He's gonna steal! This is a steal! If this app works, this kid's about to steal! [excited squealing] There he goes! There he goes! Freakin' works! It works. Two years ago I came up with an idea for an app where you could decode baseball signs So you would know when the other team was going to steal, even after just the first inning. Then in a covert effort to get people more interested in coding the machine learning, I would make the app free and available to everyone. I'm happy to report... It's no longer just an idea. Today I'm going to show you exactly how the app works, and we'll use it in the wild, and then we're going to talk about machine learning in very simple terms with my buddy Jabril. But first, to set the stage we need to understand the fascinating world of secret baseball signs. It's the game within the game. Most people know the catcher will give signs to the pitcher when your team is on defense. But when you're on offense, the third-base coach gives signs to both the batter and the base runner. For example, he could secretly tell the batter to bunt, or to not swing at the next pitch, or he can tell the base runner to steal. And just to be clear, stealing a base is when you start running as soon as the pitches thrown, instead of waiting for the batter to try and hit it. It's risky because if the batter doesn't hit the ball and the catcher is good, he can throw you out at second base. Because it's a big advantage, coaches will actually tell their players to watch and see if they could figure out the other team's signs. That's considered a fair play and it's part of the game. The problem is, our brains aren't great at figuring out the complex pattern. So we set out to create an app that would use machine learning to do exactly that. And by we, I mean Jabril actually sat down and wrote the code and I just made sure he had unlimited Cheez-Its and Lacroix. Here's how it works: If I saw coach touched his nose, ears, arm, chin, and so on, I would assign those to letters in the app. Then I'll just watch him sign and record the order. After that I would just let the app know the outcome; so was it a steal or not. After you do this for enough sequences, the app will start to make predictions. In this case, it's predicting the combination of "A, D", or "nose then chin" is their steal sign. This worked well enough on my workbench, so now it's time for the first real-world test in a kids-versus-adults Wiffle Ball game. And my friend Sara takes the game of Wiffle Ball pretty...