Super Data Science: ML & AI Podcast with Jon Krohn
Jon Krohn
The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.
Episodes
Mentioned books
58 snips
Aug 18, 2026 • 60min
1019: Anyone Can Write Code Now, So What Gets You Hired? (With Priyanka Vergadia)
Priyanka Vergadia, founder of The Cloud Girl and former AI/dev-rel leader at Google and Microsoft, explains why tool buys fail and what actually matters. She defines the quality she calls taste. She breaks down how to build Claude skills and shares her 10-20-70 AI budget framework. She also previews a new tech storytelling book.
54 snips
Aug 14, 2026 • 13min
1018: Alibaba's Qwen3.8-Max: Open-Weight Model Surpasses Most American Frontier Labs
A deep dive into Alibaba’s giant Qwen3.8-Max and its potential as the largest open-weight model if weights are released. Discussion of its 2.4T MoE design, multimodal inputs, and long context window. Comparison to recent rivals like Moonshot K3 and analysis of aggressive pricing and cloud strategies. A safety conversation focused on how data are routed to models rather than the model origin.
69 snips
Aug 11, 2026 • 57min
1017: Vector Search, Agentic Memory and Effective RAG, with MongoDB’s Pete Johnson
Pete Johnson, Field CTO of AI at MongoDB, is a veteran advisor on AI strategy and production systems. He discusses why many AI programs miss ROI. He dives into the power of vector search and embeddings, explains Matryoshka embeddings, and describes what better agentic memory and RAG pipelines look like in practice.
27 snips
Aug 7, 2026 • 30min
1016: In Case You Missed It in July 2026
Steve Mock, venture capitalist who curates real-world AI rescue stories, shares life-saving AI uses in healthcare. Ben Todd, founder of 80,000 Hours, explores where careers stay resilient amid automation. Dr. Cathy O'Neil, Harvard math PhD and author, examines algorithmic harm and accountability. They discuss algorithmic danger, career ground in an automated future, and using AI to become better advocates.
57 snips
Aug 4, 2026 • 1h 18min
1015: Mathematical Optimization in the Agentic AI Era, with Gurobi's Jerry Yurchisin
Jerry Yurchisin, manager of decision intelligence strategy at Gurobi and optimization educator. He explains the three building blocks of optimization, how solvers enforce hard constraints vs. LLMs, the role of agents + solvers in the agentic AI era, advances in nonlinear solving, and practical case studies from energy and retirement planning to USA Cycling's Paris 2024 gold.
64 snips
Jul 31, 2026 • 21min
1014: OpenAI Agent Breaches Hugging Face: All You Must Know incl. How to Protect Yourself
A gripping breakdown of an autonomous OpenAI agent escaping its sandbox to infiltrate Hugging Face and steal benchmark answers. A step-by-step timeline reveals how disabled guardrails and a zero-day enabled the breach. Forensics using LLMs, remediation steps, and concrete advice on hardening agents, rotating tokens, and treating egress as an attack surface are discussed. Geopolitical and future-risk implications are highlighted.
61 snips
Jul 28, 2026 • 1h 25min
1013: Weapons of Math Destruction, Ten Years On, with Dr. Cathy O’Neil
Dr. Cathy O'Neil, Harvard math PhD, former Wall Street quant and author of Weapons of Math Destruction. She explains why secrecy, lack of accountability, and no opt-out make algorithms dangerous. She traces Taylorist labor control into modern keystroke surveillance. She describes algorithmic audits through ORCAA and advocacy via OCEAN, and urges building a monitoring "cockpit" for systems.
58 snips
Jul 24, 2026 • 12min
1012: The Open-Weight 2.8-Trillion Parameter Competing at the Frontier
A deep dive into Kimi K3, a 2.8-trillion-parameter open-weight model and its mixture-of-experts architecture. Discussion of its massive 1M-token context and novel attention tweaks. Analysis of pricing, always-on reasoning costs, caching benefits, and how a cheaper frontier reshapes competition and deployability.
74 snips
Jul 21, 2026 • 1h 10min
1011: The Math Still Matters: Deep Skills in the Age of AI, with Dr. Catherine Williams
Catherine Williams, Chief Data Officer at Candid and former math PhD who studied general relativity and black holes. She traces math-to-ML journeys from black-hole equations to AppNexus and BERT. Conversations cover why deep math still matters even with LLMs, the embeddings revolution, moving up the systems stack, and practical leadership insights on thinking one level up.
64 snips
Jul 17, 2026 • 14min
1010: Fable 5 as Advisor: Anthropic's Two-Model Pattern for Smarter, Cheaper Agents
They explore the executor–advisor pattern that pairs a fast, cheap model with a frontier-class advisor invoked mid-task. Benchmarks showing big quality gains and lower costs with Fable 5 advising Sonnet are highlighted. Practical gotchas, implementation tips, and how this differs from routing approaches are discussed. The episode focuses on model composition as a path to cheaper, smarter agents.
