Jaden Schaefer

I think one of the earliest turning points was the idea that thinking itself could just basically be reduced to kind of like math and logic.

So if human reasoning followed rules, then kind of the theory was that you could encode those rules into a machine.

And that was basically the foundational belief of early AI.

And so in 1956, this officially got a name.

There was a group of researchers that were gathered for a workshop and they coined this artificial intelligence.

And that's basically the moment

that most people consider to be kind of like the birth of the field of AI that we have today.

So this early AI obviously was, you know, what they thought it could do was extremely optimistic.

I think it was wildly optimistic.

So basically, these researchers believed that non-human level intelligence was maybe 20 years away.

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?