Super Data Science: ML & AI Podcast with Jon Krohn

• 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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• 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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• 880: Manus, DeepSeek and China’s AI Boom

  First developed in China, Manus AI and DeepSeek have made great waves on an international scale. Sought-after for their cost-effectiveness compared to US-made tech, Manus AI and DeepSeek are quickly becoming dominant technologies inside the country. In this five-minute Friday, Jon Krohn asks: Do these technologies warrant the huge amount of resources spent on them by multiple industries in China, and what makes hype become a mainstay? Additional materials: www.superdatascience.com/880 Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

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  10:17
• 879: Serverless, Parallel, and AI-Assisted: The Future of Data Science is Here, with Zerve’s Dr. Greg Michaelson

  Greg Michaelson speaks to Jon Krohn about the latest developments at Zerve, an operating system for developing and delivering data and AI products, including a revolutionary feature allowing users to run multiple parts of a program’s code at once and without extra costs. You’ll also hear why LLMs might spell trouble for SaaS companies, Greg’s ‘good-cop, bad-cop’ routine that improves LLM responses, and how RAG (retrieval-augmented generation) can be deployed to create even more powerful AI applications. Additional materials: www.superdatascience.com/879 This episode is brought to you by Trainium2, the latest AI chip from AWS 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: (04:00) Zerve’s latest features (35:26) How Zerve’s built-in API builder and GPU manager lowers barriers to entry (40:54) How to get started with Zerve (41:49) Will LLMs make SaaS companies redundant? (52:29) How to create fairer and more transparent AI systems (56:07) The future of software developer workflows

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• 878: In Case You Missed It in March 2025

  AI stacks, AGI, training neural networks, and AI authenticity: Jon Krohn rounds up his interviews from March with this episode of “In Case You Missed It”. In his favorite clips from the month, he speaks to Andriy Burkov (Episode 867), Natalie Monbiot (Episode 873), Richmond Alake (Episode 871) and Varun Godbole (Episode 869). Additional materials: www.superdatascience.com/878 Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

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  30:49

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