Accelerating AI Training and Inference with A...

In this episode, Zoe Weil, co-founder and CEO of Sequen, joins us to discuss how ranking systems can use live behavioral signals to optimize for purchases rather than clicks or search relevance alone. Zoe explains why approaches developed at data-rich social platforms don’t neces ...  Show more

In this episode, Diogo Almeida, co-founder and CEO of TypeSafe, joins us to discuss Jev, TypeSafe’s recently released model for bringing fast, reliable intelligence directly into software. We explore the idea of “machine-native intelligence” and why Diogo believes models optimize ...  Show more

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 ...  Show more

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 ...  Show more

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 ...  Show more

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 ...  Show more