Yoshua Bengio

If you look at the curve that I showed, it would take about five years to reach human level.

Of course, we don't really know what the future looks like, but we still have a bit of time.

The other thing is,

We have to do our best, right?

We have to try, because all of this is not deterministic.

If we can shift the probabilities towards a greater safety for our future, we have to try.

Yes, and invest massively on research to understand how we can get these AI agents to behave safely.

And the current ways that we're training them is not safe.

And all of the scientific evidence in the last few months point to that.

First of all, there's so much we don't know about biological neural networks.

And that's very mysterious and captivating because maybe it holds the key to improving artificial neural networks.

One of the things I studied...

recently, something that we don't know how biological neural networks do, but would be really useful for artificial ones, is the ability to do credit assignment through very long time spans.

There are things that

we can in principle do with artificial neural nets, but it's not very convenient and it's not biologically plausible.

And this mismatch, I think, this kind of mismatch may be an interesting thing to study to, A, understand better how brains might do these things, because we don't have good corresponding theories with artificial neural nets, and B,

maybe provide new ideas that we could explore about things that brain do differently and that we could incorporate in artificial neural nets.

I was thinking more about the first two meanings whereby we store all kinds of memories, episodic memories in our brain, which we can access later in order to help us both infer causes of things that we are observing now.

and assign credit to decisions or interpretations we came up with a while ago when you know, those memories were stored.

And then we can change the way we would have reacted or interpreted things in the past.