Most next-gen AI models currently use deep learning as their underlying structure. A simple way to get introduced to this topic is through deep neural networks. 

[This website shows you how training a neural network works and lets you experiment with different settings.](https://playground.tensorflow.org/) 

Basically, a neural network is a graph of many different neurons. This network is given a set of inputs (numerical values), then the network outputs some result based on the weights for every neuron. This neural network can then be fed training data so it can learn how different inputs should connect to different outputs.

The weights for every neuron are updated according to how accurate they were in predicting the corrent output. In this way, the network gets better at learning to find different patterns in input data.

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