This is huge. Along with the paper "Humanoid Locomotion as Next Token Prediction" it seems like the "how to use transformers to get scaling in robotics" proble

This is huge. Along with the paper "Humanoid Locomotion as Next Token Prediction" it seems like the "how to use transformers to get scaling in robotics" problem has been cracked. By using transformers to predict both actions and the next multi-modal inputs (like touch sensation and/or vision) the transformer model learns a useful, general model of the world. RFM-1 and HLaNTP use totally different models, and data sources but come to the same conclusion, they see scaling behavior similar to those in LLMs. Both are small models compared to LLMs. This means we're about to see a rapid take off in robot capabilities. 1x, Tesla, and Figure probably have been using this many-to-many transformer backbone for several months now and know just how important it is. I wouldn't be surprised to see Covariant be acquired quickly to buy their expertise, data, and customer relationships.