How LLMs and Generative AI are Revolutionizing AI for Science with Anima Anandkumar
EPISODE 614
|
JANUARY
30,
2023
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About this Episode
Today we’re joined by Anima Anandkumar, Bren Professor of Computing And Mathematical Sciences at Caltech and Sr Director of AI Research at NVIDIA. In our conversation, we take a broad look at the emerging field of AI for Science, focusing on both practical applications and longer-term research areas. We discuss the latest developments in the area of protein folding, and how much it has evolved since we first discussed it on the podcast in 2018, the impact of generative models and stable diffusion on the space, and the application of neural operators. We also explore the ways in which prediction models like weather models could be improved, how foundation models are helping to drive innovation, and finally, we dig into MineDojo, a new framework built on the popular Minecraft game for embodied agent research, which won a 2022 Outstanding Paper Award at NeurIPS.
About the Guest
Anima Anandkumar
NVIDIA
Resources
- ProGen: Language Modeling for Protein Generation
- MineDojo
- Dissecting the Controversy around OpenAI’s New Language Model with Robert Munro, Miles Brundage, Amanda Askell, Stephen Merity, Anima Anandkumar
- AI Rewind 2018: Trends in Machine Learning with Anima Anandkumar
- Tensor Operations for Machine Learning with Anima Anandkumar
- Language Modeling and Protein Generation at Salesforce with Richard Socher
- Stable Diffusion & Generative AI with Emad Mostaque
- Accelerating Intelligence with AI-Generating Algorithms with Jeff Clune
- Foundation Models for Decision Making
- Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry
- GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics | bioRxiv
- ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research Awarded to Team for Modelling How Pandemic-Causing Viruses, Especially SARS-CoV-2, are Identified and Classified
- Retrieval-based Controllable Molecule Generation
- Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models
- Multi-modal Molecule Structure-text Model for Text-based Editing and Retrieval
- Fast Sampling of Diffusion Models via Operator Learning
