Today, we're joined by Shreya Shankar, a PhD student at UC Berkeley to discuss DocETL, a declarative system for building and optimizing LLM-powered data processing pipelines for large-scale and complex document analysis tasks. We explore how DocETL's optimizer architecture works, the intricacies of building agentic systems for data processing, the current la ... Show More
Yesterday
How to Engineer AI Inference Systems with Philip Kiely - #766
In this episode, Philip Kiely, head of AI education at Baseten, joins us to unpack the fast-evolving discipline of inference engineering. We explore why inference has become the stickiest and most critical workload in AI, how it blends GPU programming, applied research, and large ... Show More
54m 51s
Apr 16
How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765
In this episode, Rashmi Shetty, senior director of enterprise generative AI platform at Capital One, joins us to explore how the company is designing, deploying, and scaling multi-agent systems in a highly regulated environment. Rashmi walks us through Chat Concierge, a multi-age ... Show More
54m 18s
Mar 26
The Race to Production-Grade Diffusion LLMs with Stefano Ermon - #764
Today, we're joined by Stefano Ermon, associate professor at Stanford University and CEO of Inception Labs to discuss diffusion language models. We dig into how diffusion approaches—traditionally used for images—are being adapted for text and code generation, the technical challe ... Show More
1h 3m
Aug 2025
Amperity Reimagines Data and Developer Workflows with AI - Ep. 271
Derek Slager, co-founder and CTO of Amperity, explores how agentic AI and vibe coding are reshaping enterprise data management and the developer experience on the NVIDIA AI Podcast. Hear how Amperity’s platform unifies customer data, powers advanced analytics, and brings conversa ... Show More
36m 40s
Aug 2024
AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki
In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fa ... Show More
25m 37s
Oct 2025
Evals, error analysis, and better prompts: A systematic approach to improving your AI products | Hamel Husain (ML engineer)
Hamel Husain, an AI consultant and educator, shares his systematic approach to improving AI product quality through error analysis, evaluation frameworks, and prompt engineering. In this episode, he demonstrates how product teams can move beyond “vibe checking” their AI systems t ... Show More
54m 48s
Jul 2025
903: LLM Benchmarks Are Lying to You (And What to Do Instead), with Sinan Ozdemir
Has AI benchmarking reached its limit, and what do we have to fill this gap? Sinan Ozdemir speaks to Jon Krohn about the lack of transparency in training data and the necessity of human-led quality assurance to detect AI hallucinations, when and why to be skeptical of AI benchmar ... Show More
1h 28m
Nov 2024
SE Radio 641: Catherine Nelson on Machine Learning in Data Science
<p><strong>Catherine Nelson</strong>, author of the new O'Reilly book, <em data-renderer-mark="true">Software Engineering for Data Scientists</em>, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and ... Show More
48m 19s
Oct 2024
Gerald Sim, "Screening Big Data: Films That Shape Our Algorithmic Literacy" (Routledge, 2024)
Screening Big Data: Films that Shape Our Algorithmic Literacy (Routledge, 2024) examines the influence of key films on public understanding of big data and the algorithmic systems that structure our digitally mediated lives.
From star-powered blockbusters to civic-minded document ... Show More
1h 6m