My first "oh shit" moment was when ChatGPT 3 was brand new. Maybe December 2022 or so.

I have a personal project: who's winning the race at 3 AM?

You see, I don't sleep well. I live in a busy city, with a busy freeway about a half mile away. Sometimes at 3 AM there are some very loud cars racing on the freeway. That's illegal for many reasons, not least of which is the fact that the noise pollution wakes people up from their precious sleep and causes knock-on affects to the population.

Anyway, now that I'm woken up, my only question is: who's winning the race?

I used this question as a way to explore a hyptothetical tech stack, with each part of the tech stack useful in some way to my work as a software engineer who's interested in robotics.

- run raspberry pis with microphones, collect audio data

- run a k8s cluster for audio collection and processing

- calculate and triangulate individual points, and give estimations of velocity based on position changes over time, and adjust for doppler shift

- estimate (poorly, but doable) engine power based on amplitude

- run a webserver in the k8s cluster showing an animation of the racers with color fields representing estimation error radiating from the position estimate, with arrow representing velocity

Great project, actually. It was really thought-provoking. I had this working in late 2018.

Since there was a lot of hype around this new "AI", I thought how smart could it be?

I threw the scenario to chat GPT. I did have to break the problem set into smaller parts for context window purposes. But the solution it came up with solved about 80% of the project correctly (and very close to solutions I already came up with), about 15% of the project remained "open until we have more data", with maybe about 5% of the project would have been incorrectly solved.

That was very much an "oh shit, AI is closer than the 20 years away that I've been telling people. It's more like 5 years away"

Here we are three, almost four, years later...