VASC Seminar

Abstract: Machine learning has transformed many fields by learning from large collections of data. Yet, it is rarely applied to its own outputs: the models themselves. Today, with millions of publicly available models, a natural question arises: what can we do with so many models? In this talk, I will motivate two core applications that [...]

Abstract: Transformers are ubiquitous. They influence nearly every aspect of modern AI. However, the mechanics of their training remain poorly understood. This poses a problem for the field due to the immense amounts of data, computational power, and energy being invested in the training of these networks. I highlight a recent intriguing empirical result from [...]