Huang says models may run 10,000 internal inferences before answering, including tree search and reinforcement learning.
“The idea that a model before it answers your answer had already done internal inference 10,000 times, it's probably not unreasonable. And it's probably done tree search, it's probably done reinforcement learning on that,”
Huang says AI creates abundance of intelligence by orders of magnitude, compressing year-long work into hours or real-time.
“AI reduces the cost of intelligence or create the abundance of intelligence by orders of magnitude.”
Huang describes PhysicsNEMO as a physics-aware AI framework combining principled simulation with AI prediction.
“PhysicsNEMO is essentially a physics aware AI model simulation system and AI framework that allows us to create these AI models that are either trained by principled simulators or work alongside principled simulators”
Huang claims PhysicsNEMO can predict physics simulations ten thousand times faster than traditional methods.
“so it's grounded in the laws of physics, but able to predict 10,000 times faster.”