Machine Learning Street Talk (MLST)/
Designing How AI Grows — Tom McGrath
Tom McGrath argues interpretability should become a “natural science on computers” that can actively shape training, not just explain models after the fact. The episode ranges from intentional design and controlled generalization to manifold geometry, reward hacking, and why sparse autoencoders may be useful but not the final representation format.
