Andrej Karpathy

I love to re-explain and things like that.

And I think people should be doing that more as well.

I think that forces you to manipulate knowledge and make sure that you know what you're talking about when you're explaining it.

What is a neural network?

It's a mathematical abstraction of...

The brain, I would say.

That's how it was originally developed.

At the end of the day, it's a mathematical expression.

And it's a fairly simple mathematical expression when you get down to it.

It's basically a sequence of matrix multiplies, which are really dot products mathematically.

And some non-linearity is thrown in.

And so it's a very simple mathematical expression.

And it's got knobs in it.

Many knobs.

Many knobs.

And these knobs are loosely related to basically the synapses in your brain.

They're trainable.

They're modifiable.

And so the idea is we need to find the setting of the knobs that makes the neural net do whatever you want it to do, like classify images and so on.

And so there's not too much mystery, I would say, in it.