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
10 snips
Mar 27, 2026 • 11min
A Post-Transformer Architecture Crushes Sudoku (Transformers Solve ~0%)
A hard Sudoku benchmark exposes a major weakness in top transformer models while a new post-transformer BDH architecture nails 97.4% accuracy. Discussion covers why Sudoku is a powerful test of constraint-solving and reasoning. Hear what BDH changes about model state, sparsity, and continual learning to achieve far better efficiency and scaling for reasoning tasks.
29 snips
Mar 24, 2026 • 1h 18min
977: Attention, World Models and the Future of AI, with Prof. Kyunghyun Cho
Kyunghyun Cho, NYU professor and co-author of the original attention paper, explains the origins of attention and its rapid validation. He discusses sample efficiency and why actively choosing data matters. He debates world models versus latent planning and describes teaching undergrads with coding agents.
54 snips
Mar 20, 2026 • 10min
976: NVIDIA’s Nemotron 3 Super: The Perfect LLM for Multi-Agent Systems
They unpack NVIDIA’s Nemotron 3 Super architecture and how a 120B model only activates 12B parameters for efficiency. Listeners hear about the hybrid Mamba-Transformer design and latent mixture-of-experts routing. The conversation covers million-token context windows, NVFP4 precision with Blackwell GPUs, throughput benchmarks, and where to access and deploy the model for multi-agent systems.
23 snips
Mar 17, 2026 • 1h 13min
975: Unmetered Intelligence is Heralding the Next Renaissance, with Zack Kass
Zack Kass, AI advisor and author of The Next Renaissance, outlines why cheap, abundant intelligence will reshape society. He discusses parallels with the original Renaissance, risks from information overload and media negativity, how AI can transform education and personalized learning, and four practical principles for thriving in an AI-driven future.
54 snips
Mar 13, 2026 • 14min
974: When Will The AI Bubble Burst? How Bad Will It Be?
A rapid look at signs of AI hype, from questionable startups to massive spending on compute and researchers. A tour of historical bubbles like railways and dot-coms that left lasting infrastructure. Discussion of how big bets signal demand and lock in adoption. Practical warnings about timing and how technical fundamentals can protect practitioners if a correction comes.
59 snips
Mar 10, 2026 • 1h 12min
973: AI Systems Performance Engineering, with Chris Fregly
Chris Fregly, AI systems performance engineer and author with experience at AWS, Databricks, and Netflix, discusses GPU-centric performance engineering. He focuses on memory bandwidth over FLOPS. Topics include full-stack hardware–software co-design, low-level profiling and CUDA, inference optimizations like KV cache, and practical use of AI coding assistants and continuous evals.
45 snips
Mar 6, 2026 • 27min
972: In Case You Missed It in February 2026
Praveen Murugesan, VP of Engineering at Samsara, on quantum computing for routing and more autonomous ops. Antje Barth, Amazon technical staff on developer-facing AI tooling and UI automation workflows. Tom Griffiths, cognitive scientist and author exploring human cognition shaping AI design. Will Falcon, CEO of Lightning AI and PyTorch Lightning creator on turning open source into a revenue-generating company.
50 snips
Mar 3, 2026 • 60min
971: 90% of The World’s Data is Private; Lin Qiao’s Fireworks AI is Unlocking It
Lin Qiao, CEO and co-founder of Fireworks AI and former Meta engineering leader, builds platforms that unlock private enterprise data for custom open-source models. She discusses autonomous intelligence, coding agents that act like junior engineers, why enterprises should bet on open models, and how Fireworks optimizes model, hardware, and evaluation choices for real-world use.
47 snips
Feb 27, 2026 • 15min
970: The “100x Engineer”: How to Be One, But Should You?
A fast look at how code-generation tools are creating super-productive engineers who program through AI agents. Stories about Karpathy moving to agentic, English-first coding and Steinberger’s viral multi-agent workflow that outpaced teams. Discussion of why more planning and specs matter when agents do the typing and the risks of skill atrophy and overreliance on AI.
81 snips
Feb 24, 2026 • 1h 11min
969: The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths
Tom Griffiths, Princeton professor bridging psychology and computer science, explores mathematical models of thought and AI. He discusses probabilistic versus symbolic approaches, how autoregressive training shapes LLM behavior, engineering inductive biases and meta-learning, and modeling curiosity as information-seeking. Short, clear dives into building and evaluating minds and machines.
