Stealing Baseball Signs with a Phone (Machine Learning)

After doing this with a few examples for which you know the solution, you reach a point where the answer becomes less precise the more you turn the knobs, so you stop. Then paste these hidden node buttons in place, because you've trained your model, and with any new input whose solution you don't know, you'll get a correct output, steal in this example. This is a simplified model, of course, but it can be expanded to include thousands of input values ​​and thousands of output values, and you will discover very complex connections. The cool thing about this is that this is how the neural networks in our brain learn the same thing.

Once I receive enough data to understand how my hands and arms interact and keep an object balanced this way, it trains my model and attaches that of my brain. small buttons. Then I'll be able to add a new entry that I haven't tried before and I know what to do, so I don't need to practice all the different things because my mind has drawn the boundaries. Think about it. Long before the advent of

machine

learning

and neural networks, computers followed coded instructions that humans fed to them. Now they can learn like humans, but they can do it more quickly and completely than we can.

I'll try it now. So when I gave Gabriel a challenge that would take thousands of years to solve with a normal computer using an exhaustive search...hey, man. you are fast. Please tell me that your indicator is the touch of a mustache. Then you will make a random movement, tapping your teeth. Alright? This is correct. Gabriel's

machine

learning

algorithm established the correct terms and solved the code in less than three minutes. The machine learning model requires more data than our version and can decode three sequences, but the good news is that we will decode any combination of signals as long as we look at the inputs correctly.

Now it's time to do a real life test and I asked my friend Dustin for a secret trick. This is the stadium where he used to play as a kid and today my son plays for the Rascals. I'll film the third base coaches when they signal and we'll feed the data into the machine learning algorithm... These kids are yelling at me, they want to know the name of my channel. That they didn't recognize him shows me that everything he did here was a good disguise. Thanks to Dustin's incredible interviews and videos, we've collected more data that proves our method works.

While Dustin boldly set up a camera and filmed all the third base coaches. - Talk to them first and tell them what you are doing. - Well. - Because the

signs

are secret, right? - Well. Well. Well understood. I got in trouble for

stealing

signs

. I was more nervous and reserved. If you put a GoPro camera in a mug, you can instantly watch videos and take photos, and it will look like you're browsing on your

phone

and drinking coffee. I have used this trick several times. Especially in the Carnival Scam video, the app worked excellently with Destin's footage and at the game I attended, and you get a great feeling when you crack its code.

Well, they will steal. You will be able to anticipate what will happen next. - Run. - It will. I knew he was going to steal, I knew it. I hope you enjoyed this argument for learning more about machine learning as much as I did. I'll put links to both versions of the app in the video description for you to see. If there are specific rules against using sign-

stealing

technology in your league, I don't encourage you to violate them. Otherwise, from my personal experience, you risk angering important people. You cheated, Mark Ruffa! "Subscribe to the channel please" "Subscribe to the channel please"