Accelerating AI Training and Inference with A...

In this episode, Justin Johnson, co-founder of World Labs, joins us to discuss world models and the emerging field of spatial AI. We explore why many researchers see capabilities beyond language as an important frontier for AI, and what it means to build models that can understan ...  Afficher plus

The conventional wisdom in AI is that the next breakthrough will come from more compute, more data, and larger models. But what if the next leap comes from somewhere else? In this episode, Max Welling—co-founder and CTO of CuspAI and professor at the University of Amsterdam—argue ...  Afficher plus

How to get the best price performance in Amazon EC2 for the most demanding machine learning training workloads? Tune in to learn how AWS Trainium-based Amazon EC2 Trn1n instances can help you train your network-intensive generative AI models at scale. Amazon EC2 Trn1n instances d ...  Afficher plus

State space models (SSMs), granite models, and Mamba: Dell’s Tyler Cox and Shirish Gupta discuss with Jon Krohn why state space models can process information so efficiently, and how Dell’s AI factory helps enterprises manage custom AI workloads. Hear the latest on the Dell Pro A ...  Afficher plus

Reproducibility, Python notebooks, and data science communities: Software developer Akshay Agrawal speaks to Jon Krohn about Marimo, the next-generation computational notebook for Python, how he built and fostered a thriving community around the product, and what makes this noteb ...  Afficher plus

Learn how NVIDIA's Nemotron family of open source models is redefining accelerated computing. NVIDIA’s Bryan Catanzaro and Jonathan Cohen discuss the breakthroughs in efficiency, openness, and collaboration — sharing how Nemotron empowers developers and enterprises to innovate, c ...  Afficher plus