Marcus Hutter

And we have this annual competition, the Löbner.

And I mean, it started with ELIZA, that was the first conversational program.

And what is it called, the Japanese, Mitsuko or so, that's the winner of the last couple of years.

Yeah, it's quite impressive.

Yeah, it's quite impressive.

And then Google has developed Mina, right?

Just recently, that's an open domain conversational bot, just a couple of weeks ago, I think.

Maybe many humans will also fail this test.

I said the Turing test is not as bad as some people believe, but what is really...

not useful about the Turing test.

It gives us no guidance how to develop these systems in the first place.

Of course, we can develop them by trial and error and do whatever and then run the test and see whether it works or not.

But a mathematical definition of intelligence

gives us an objective which we can then analyze by theoretical tools or computational and maybe even prove how close we are.

And we will come back to that later with the ICSI model.

I mentioned the compression, right?

So in natural language processing,

They achieved amazing results.

And one way to test this, of course, you take the system, you train it, and then you see how well it performs on the task.

But a lot of performance measurement is done by so-called perplexity, which is essentially the same as complexity or compression length.