Allie K. Miller

It started learning.

And so the combination of just being able to go back and forth and hold that information, the fact that it was not some ugly, you know, terminal sort of looking thing, like it really wasn't for engineers.

It was just a normal website.

And the fact that it was like very performant and fast, all of that combined, you just tested and you're like, this is the moment that I've been counting down for.

The way that I define it and how it was initially launched in, you know, 1956, it's been around for a while, is that it's AI attempting to mimic what a human can do.

And that might mean typing tweets.

That might mean like your Roomba going around and cleaning your home.

That might mean a self-driving car because, again, it's mimicking the fact that a human can drive a car.

So it's just some sort of computer system mimicking a thing that a human can do.

And that thing might be really simple or really complex.

Yeah, it's kind of weird, right, that we like lost this middle ground of people.

A hundred percent.

Like first two years, everyone was kind of floating along.

Now it's you're either at 10 or you're at one.

I think what a lot of people are still tripping up on is that they believe it is only for the most technical among us.

There's something like a million data scientists and machine learning engineers in the world.

There's something like 30 million developers.

And even the most advanced tools that I am using, that I am helping other non-technical business professionals use,

Only a couple million people are using those tools.

So I think that there's still a lot of education to be done or at least self-experimentation to say, wait a second, even though these things sound really technical, it's actually a myth.