Super Data Science: ML & AI Podcast with Jon Krohn

• 885: Python Polars: The Definitive Guide, with Jeroen Janssens and Thijs Nieuwdorp

  Jeroen Janssens and Thijs Nieuwdorp are data frame library Polars’ greatest advocates in this episode with Jon Krohn, where they discuss their book, Python Polars: The Definitive Guide, best practice for using Polars, why Pandas users are switching to Polars for data frame operations in Python, and how the library reduces memory usage and compute time up to 10x more than Pandas. Listen to the episode to be a part of an O’Reilly giveaway! Additional materials: ⁠www.superdatascience.com/885 This episode is brought to you by Trainium2, the latest AI chip from AWS, by Adverity, the conversational analytics platform and by the Dell AI Factory with NVIDIA. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (07:44) Why Jeroen and Thijs wrote Python Polars: The Definitive Guide   (21:54) Best practices in Polars  (25:55) Why Polars has so many users (34:32) The benefits of the Great Tables package (51:06) Jeroen and Thijs’ partnership with NVIDIA and Dell for Python Polars: The Definitive Guide

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• 884: Model Context Protocol (MCP) and Why Everyone’s Talking About It

  Model Context Protocol (MCP) is Anthropic’s hottest tool, with over 1,000 community-built MCP servers in operation by February alone. In this Five-Minute Friday, Jon Krohn explains what took so long for users to catch on: Anthropic released MCP in November 2024. Hear more about the buzz behind MCP, its applications, and how easy it is to get started. Additional materials: ⁠www.superdatascience.com/884⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

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  6:44
• 883: Blackwell GPUs Are Now Available at Your Desk, with Sama Bali and Logan Lawler

  Returning after the “Super Bowl of AI”, NVIDIA GTC, Sama Bali and Logan Lawler talk to Jon Krohn about their respective work at tech giants NVIDIA and Dell. Sama and Logan discuss the next-gen Blackwell GPUs to their collaboration with Dell in launching Pro-Max PCs specially designed to take on heavy computational workloads as well as the incredible performance of GB 10 and GB 300 workstations, and the widening accessibility of AI developer tools and models.  Additional materials: www.superdatascience.com/883 This episode is brought to you by ODSC, the Open Data Science Conference, by Adverity, the conversational analytics platform and by the Dell AI Factory with NVIDIA. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (07:29) About Dell’s Pro Max PCs (14:01) Why having a Blackwell GPU from Nvidia is a great option for those new to training and deploying AI models   (36:47) When it makes sense for a data scientist to switch from a Unix to a Windows based system  (46:33) Logan’s and Sama’s predictions for AI

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• 882: 40x Hotter Than the Sun: The ASML Machines That Make AI Chips

  This week’s five-minute Friday heads to the Netherlands to find out more about Dutch company ASML, the brains behind the lithography machines that build AI chips.  Jon Krohn walks through how ASML came to dominate the market, where they’re headed next, and how ASML’s complex machines shape AI chips as well as the very future of AI.   Additional materials: www.superdatascience.com/882 Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

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  9:45
• 881: Beyond GPUs: The Power of Custom AI Accelerators, with Emily Webber

  Emily Webber speaks to Jon Krohn about her work at Amazon Web Services, from its Annapurna Labs-developed Nitro System, a foundational technology that can enhance securities and performance in the cloud and how Trainium2 became AWS’ most powerful AI chip with four times the compute of Trainium. Hear the specs of AWS’s chips and when to use them. Additional materials: www.superdatascience.com/881 This episode is brought to you by ODSC, the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (08:36) Emily’s work on AWS’ SageMaker and Trainium  (23:54) How AWS Neuron lets builders tailor their approach to using frameworks  (29:07) Why using an accelerator is better than using a GPU  (35:29) The key differences between AWS Trainium and AWS Trainium2  (52:45) How to select between AWS Trainium and AWS Trainium2

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