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dylan604 3 days ago

Why not though? Current autopilot just attempts to keep plane on course/speed/altitude. Some can go further with auto-landing, but extreme emergency use only. I could see the airlines wanting to seek any fuel savings possible by possibly allowing AI to test slight changes to altitude/speed/course to conserve fuel based on some live inputs.

lemonwaterlime 3 days ago | parent | next [-]

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.

rcxdude 2 days ago | parent [-]

I would say the underlying mathematics is optimization theory, which also has applications in control but was not specifically designed for it (and indeed, the way you approach optimization in control and ML/AI is quite different)

3 days ago | parent | prev [-]
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