Comment by D-Machine
18 days ago
Obviously you can build an AI model that rides a bike, just not an LLM that does so. Even the transformer architecture would need significant modification to handle the multiple input sensor streams, and this would be continuous data you don't tokenize, and which might not need self-attention, since sensor data doesn't have long-range dependencies like language does. The biking AI model would almost certainly not resemble an LLM very much.
Calling everything "language" is not some gotcha, the middle "L" in LLM means natural language. Binary code is not "language" in this sense, and these terms matter. Robotics AIs are not LLMs, they are just AI.
>Binary code is not "language" in this sense
Any series of self consistent encoded signals can be language. You could feed an LLM wireless signals if until it learned how to connect to your wifi if you wanted to. Just assign tokens. You're acting like words are something different than encoded information. It's the interconnectivity between those bits of data that matters.
This literally ignores everything I said and you clearly are out of your depth. See my other comment, sensor data can't be handled by LLMs, it is nothing like natural language.
https://news.ycombinator.com/item?id=46948266