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Comment by ingenieroariel | Hacker News Reader

thanks! I am still curious about the sensor inputs part.

I am trying to replace the 2.4ghz controller on my electric skateboard to make 0 to 5kmh and braking more pleasant and maybe use gyroscopes to do away with the controller altogether. What would tokens be in that case? Do you create a CAN style representation and feed that to the llm? What kind of throughput do you foresee being possible on which hardware?

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I am still thinking how I'll pull this off. But basically it is collect tons of Telemetry converted to in ascii/text.

Telemetry in sense sensor streams, both command and responses.

Then we'll just train a small model for long enough. Then we will see how it would respond.

That's the plan sort of.

In this case, I would ask the LLM to suggest an algorithm to minimize acceleration, jerk and snap based on the expected sensor input data, and then just implement that. Probably in memory on whatever runs the board.

Straightforward control problem of bringing the board from 5-0kmh smoothly?

Let's see.

Basic control theory will work better than AI here. The mathematical models used in control theory have been used in computing since at least the 50's (Kalman Filters). I suspect you won't have issues with computational power.

Figuring out exactly which model to use and how, may take some work. Also understanding control theory will allow you to do things like traction control, etc.

In addition. I Agree.

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