Large Models for All and How to Adapt Them Efficiently
Alex Smola
CEO
Foundation models have revolutionized ML, but using them remains a challenge. I’ll give an overview of such models and how to use them, both for mixed data in the context of AutoML and through fine-tuning and prompting, as is commonly done in Large Language Models.
In particular, AutoGluon allows users to integrate tabular data with representations for different data types, including text and images. I’ll discuss how this can be accomplished efficiently, taking advantage of the latest models available on public repositories, as well as how to adapt pure language models.
About the Speaker Alex Smola
Alex was VP, Distinguished Scientist with Amazoan, a lecturer at Stanford for Machine Learning, and now started his owna company.
He co-authored ‘Dive into Deep Learning,’ a widely used book adopted by 400 universities internationally, and he is one of the contributors to the opensource AutoML tool AutoGluon.
