Jaden Schaefer

They thought things like vision, language, reasoning were basically solved problems.

And of course, I think the spoiler alert is that they were not because we're here, you know, like over 50 years later and bringing a lot of this stuff out.

I mean, 75 years later for some of this stuff.

So a lot of these early AI systems were what we now call symbolic AI.

Basically, the systems worked by hand.

These hand coded rules.

So if this happens, then that right, it's kind of the if then you see this pattern.

And you know, if the computer sees a pattern, it's going to respond in a specific way.

And in that like really narrow domain, this actually worked, you could build programs, you know, that played chess, or that solved logic puzzles, or, you know, things that did basic math proofs.

But the second that you took them outside of these kind of, you know, really small controlled environments, everything broke, right?

This is not actual intelligence.

It's, I mean, we know what these are.

It's just kind of computer systems.

But at the time, they believed they truly had achieved, you know, artificial intelligence.

So...

Of course, we know that the real world is very messy.

Language is ambiguous.

Vision is very noisy.

As humans, we're relying on like intuition in our experience and also like on context.

So there's a lot of things that aren't just rules.