Join us for lunch and hear how the VAST Data Platform empowers generative AI and large-scale research workflows at NYU. We’ll uncover how VAST’s cutting-edge capabilities—spanning analytics, multiprotocol support, data reduction, performance, and reliability—make it the preferred choice for a wide range of AI research initiatives, from sentiment analysis to complex protein folding studies, as well as broader HPC applications. 

Key topics explored throughout the conversation will include: 

•• Running AlphaFold seamlessly on VAST, enabling researchers to accelerate discoveries in protein folding without modifications—an achievement that was challenging on legacy systems like GPFS. 
•• The development of the VAST Data Platform, incorporating Retrieval-Augmented Generation (RAG) to support diverse data sets, including biological, political, and nursing-related research, while maintaining strict data privacy.
•• VAST’s multi-protocol capabilities that simplify moving workloads between HPC clusters and Kubernetes, allowing researchers to optimize their workflows efficiently. 
•• Using the VAST Database and VAST Catalog to provide a scalable, high performance store for metadata and structured data used for such research initiatives as performing sentiment analysis on social media feeds.

This chat aims to provide a comprehensive view of how VAST drives innovation across various research fields, creating a seamless, reproducible, and accessible data ecosystem that fosters groundbreaking AI developments.