Science of AI and AI for Science
Date:
Neural language models with billions of parameters and trained on trillions of words are powering the fastest-growing computing applications in history and generating discussion and debate around the world. Yet most scientists cannot study or improve those state-of-the-art models because the organizations deploying them keep their data and machine learning processes secret. I believe that the path to models that are usable by all, at low cost, customizable for areas of critical need like the sciences, and whose capabilities and limitations are made transparent and understandable, is radically open development, with academic and not-for-profit researchers empowered to do reproducible science. In this talk, I’ll discuss some of the work our team is doing to radically open up the science of language modeling and make it possible to explore new scientific questions and democratize control of the future of this fascinating and important technology.