Turing lecture: The mathematics of large machine learning models
APA
(2025). Turing lecture: The mathematics of large machine learning models. SciVideos. https://scivideos.org/icts-tifr/32487
MLA
Turing lecture: The mathematics of large machine learning models. SciVideos, Aug. 10, 2025, https://scivideos.org/icts-tifr/32487
BibTex
@misc{ scivideos_ICTS:32487, doi = {}, url = {https://scivideos.org/icts-tifr/32487}, author = {}, keywords = {}, language = {en}, title = {Turing lecture: The mathematics of large machine learning models}, publisher = {}, year = {2025}, month = {aug}, note = {ICTS:32487 see, \url{https://scivideos.org/icts-tifr/32487}} }
Abstract
The success of modern AI models defies classical theoretical wisdom. Classical theory recommended the use of convex optimization, and yet AI models learn by optimizing highly non-convex function. Classical theory prescribed to control model complexity and yet AI models are very complex, so complex that they often memorize the training data. Classical wisdom recommends a careful and interpretable choice of model architecture, and yet modern architectures rarely offer a parsimonious representation of a target distribution class.
The discovery that learning can take place in completely unexpected scenario poses beautiful conceptual challenges. I will try to survey recent work towards addressing them.