Seems very oriented toward model architecture and inference engineering. Maybe add some more on model training flow, distillation, data generation, SFT and RL techniques?
Seems like he thinks RLVR == learning from binary reward for the whole chain, completely discounting techniques to provide denser rewards like process reward supervision?
Typing can also work, but handwriting is simply faster and easier to decode.
sEMG signals correlate with *muscle* activation. When your fingers move, the actuators are the muscles in your forearm, and the tendons relay the force on the joint. Placing the band higher up on the forearm would actually give you better signals, but a wrist placement is much more socially acceptable.