The author misses the science of emergence. Reductionist views can’t fully explain macro-level capabilities that arise in these systems. Something emerges at hi

The author misses the science of emergence. Reductionist views can’t fully explain macro-level capabilities that arise in these systems. Something emerges at higher scales from the possibility space as model sizes grow; they stop being mere “stochastic parrots” or black boxes running simple regressions. The weights develop their own inherent logic based on how they relate to each other, analogous to how brain waves encode memory at a level higher than individual neuron networks. Ultimately, the value of AI lies in the imagination of its wielder. The Unknown Unknowns framework is a useful tool for navigating AI effectively (it powerful to help elaborate on Known Unknowns and identify Unknown Unknowns), along with a healthy dose of critical thinking and understanding how reinforcement learning and RLHF work post-pretraining.