| Many of humans' capabilities are pretrained with massive computing through evolution. Inference results of o3 and its successors might be used to train the next generation of small models to be highly capable. Recent advances in the capabilities of small models such as Gemini-2.0 Flash suggest the same. Recent research from NVIDIA suggests such an efficiency gain is quite possible in the physical realm as well. They trained a tiny model to control the full body of a robot via simulations. --- "We trained a 1.5M-parameter neural network to control the body of a humanoid robot. It takes a lot of subconscious processing for us humans to walk, maintain balance, and maneuver our arms and legs into desired positions. We capture this “subconsciousness” in HOVER, a single model that learns how to coordinate the motors of a humanoid robot to support locomotion and manipulation." ... "HOVER supports any humanoid that can be simulated in Isaac. Bring your own robot, and watch it come to life!" More here: https://x.com/DrJimFan/status/1851643431803830551 --- This demonstrates that with proper training, small models can perform at a high level in both cognitive and physical domains. |
Hmm .. my intuition is that humans' capabilities are gained during early childhood (walking, running, speaking .. etc) ... what are examples of capabilities pretrained by evolution, and how does this work?