Large Foundation Models and Generative AIRethink the theoretical foundation of generative AI and explore new methods to build, deploy, and risk manage large foundation models
Deep learning, modern hopfield networks, nonparametric large language models
Probabilistic Graphical Models and Combinatorial Inference Explore probabilistic graphical models as a unified framework which combines uncertainty and logical structure to model complex, real-world phenomena.
Combinatorial inference, structure learning, nonparametric graphical models
Computer Systems for Massive Computational ExperimentsBuild production-grade robotic systems for conducting massive computational experiments and deploy real-time machine learning
Experiment management systems, deployment operating systems
Artificial Intelligence
Project: Large Foundation Models and Generative AI
Explore theory, methods and applications of large foundation models towards generative AI
High Dimensional Statistics
Project: Graphical Models and Combinatorial Inference
Infering the topological and geometrical properties of high dimensional probabilistic graphical models
Computer Systems
Project: Real-time and Low Latency Robotic Systems
A robotic approach to develop and deploy real-time and low-latency machine learning systems
CFMG: Center for Foudation Models and Generative AI
Keywords: foundation models, generative AI, research, talents, repository, empower
An operational platform providing dedicated resources to empower the research of large foundation models and generative AI at Northwestern University
Highlights
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DNABERT: A Language Model for Genome
Febury 6th, 2024 | Project
Large language models, genomics, AI for Science