Max Tegmark

Why deeper networks are good, but we were able to show an additional cool fact there, which is that even incredibly simple problems, like suppose I give you a thousand numbers and ask you to multiply them together, you can write a few lines of code, boom, done, trivial.

If you just try to do that with a neural network that has only one single hidden layer in it, you can do it.

But you're going to need two to the power of a thousand neurons to multiply a thousand numbers, which is, again, more neurons than there are atoms in our universe.

That's fascinating.

But if you allow yourself to make it a deep network of many layers, you only need 4,000 neurons.

It's perfectly feasible.

So...

In some Hollywood movies...

That I will not mention my name because I don't want to spoil them.

The way they get AGI is building a quantum computer.

Because the word quantum sounds cool and so on.

That's right.

First of all, I think we don't need quantum computers to build AGI.

I suspect your brain is not a quantum computer in any profound sense.

I even wrote a paper about that many years ago.

I calculated the so-called decoherence time, how long it takes until the quantum computerness of what your neurons are doing gets erased by just random noise from the environment.

And it's about 10 to the minus 21 seconds.

So as cool as it would be to have a quantum computer in my head, I don't think that fast.

On the other hand, there are...

very cool things you could do with quantum computers, or I think we'll be able to do soon when we get bigger ones, that might actually help machine learning do even better than the brain.