Donald Wunsch on the Limits of AI and Why It Matters

And now we have these rich people like Amazon and, uh, uh, OpenAI that are doing this, uh, the same sort of research.

So it's gonna be interesting to see what happens to these tools as they get more sophisticated.

So let's talk about your paper, Artificial General-

Oh, look, I, actually, I want to run on that risk for a moment because-

Okay

...

it, it embraces something that's very fundamental to human intelligence and is more difficult for artificial intelligence, and that is the concept of paradox.

Okay? So paradox is something that is really important and, uh, it's a theme in literature, it's a theme in religion, it's a theme in, uh, scientific, you know, like Copernican revolution, you could say, is built on paradox too.

And so, um, so the idea of paradox really is a, a deep concept that artificial intelligence, you know, can talk about it, like an LLM could give you a whole essay about paradox.

But to really process paradox, that's something that I think is important, and it, it relates to the theme that you just, uh, wrote.

So it is both true and false, uh, that you have to be rich to do this.

The true part is that, uh...

So for example, I had a student, he took all my classes, uh, and he went to a small company in Alexandria called Heron Systems.And Heron Systems got a, a contract from DARPA and, uh, they entered the Alpha Dogfight Competition, and it was a David and Goliath result.

They, uh, they beat Boeing, they beat Lockheed, they beat all these big contractors, uh, at, uh, the, this full-blown flight simulator that was a fighter flight simulator where they would engage in dogfights against the other, uh, AI contenders, and then the winner could take on a real human, and they took on the real human, and they clobbered them.

Wow.

And, uh, and, and so they were taken over by another company, uh, called, uh, Shield AI, and he's still doing that.

And, uh, and, and he, he was a wonderful student.

Uh, and anyway, this, this idea, this is the David side of it.

But the Goliath side is this.

I asked him, "Well, what worked for you?" And he said, "Well, w- we...

Our first grant had 900K from DARPA.

They had phase one, and then they had to go phase two, and then they got to, uh, fight against the human pilot." He said, "Our phase one, we spent the majority of our money on the hardware.

Uh, so we bought, we bought the GPUs, and we ran them, uh, all the time, you know, pretty close to 24/7, and, uh, that's what worked for us.

Uh, the, the algorithms were the things that I learned.

It wasn't some algorithmic breakthrough.