I just assumed it was developed by Boeing.

As a rule of thumb, airplanes subsystems are expected to have 99.99999% reliability, so the whole gets 99.9999%.

Airline airplanes are currently more than one order of magnitude better than this. But if you have that, you can claim your plane works.

It's very much enough for drones tho... all you need is a tiny Jensen's chip, moped engine, some boom boom play-doh and you're ready to rock. No remote control needed.

we can do it once we know how they work. which will be never.

The mathematics that LLMs and machine learning are based on started off being developed for aircraft decades ago. It’s called “control theory”. So we had “AI” on airplanes first. Specifically we had adaptive control algorithms explicitly because of the problems introduced by fuel levels changing during the course of a flight.

In physics, we typically start with mass-spring-damper system representation. Elementary physics and engineering typically has assumptions such as mass being constant. You develop all sorts of dynamical models and intuition with that assumption. But an aircraft burns fuel as it flies, meaning its mass changes during the course of the flight. Thus your models drift and you have to adapt to that.

Pilots would have tomes they'd have to switch between at various points of the journey and adaptive control algorithms alleviated this. They still needed the actual reference guide in the cockpit as a risk mitigation.

The difference between that decades old application is that you don’t need a billion parameter model to do flight control. Most people do not understand the historic development of these techniques. The foundation of them has been around for a while. What we have done with the newest batch of "AI" is massively scale them up.