1038: AI’s Contentious Math Breakthroughs

In this month's episode of ICYMI, Jon Krohn moves from the fears that surround AI to the work it makes possible when we use it well. Hear from Richard Socher, Carly Taylor, Jeff Hancock, Kate Niederhoffer and John Renne, discussing why the founder of a company built to create recursively self-improving superintelligence is not afraid of the idea, how inviting your fears to tea helps you keep growing, why AI-generated “workslop” that is harmless fun on social media becomes infuriating at work and how two hours of AI-assisted research can now do the work of a half-million-dollar grant. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1044⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (00:20) Recursive Self-Improvement: The Eureka Machine (08:21) Workslop, Glass Cliffs and Inviting Your Fears to Tea (14:49) Workslop: The Hidden Cost of AI-Generated Work (21:58) AI for Real Estate, Walkable Cities and Climate Action

In Episode #1043, Dr. Guru Banavar (Founding CTO of Viome) joins Jon Krohn for a technical masterclass on the biology inside your gut. Viome has assembled what Guru calls the largest dataset on human biology ever collected, roughly 100 quadrillion nucleotides of RNA from people in more than 150 countries, and uses it to tell individuals which foods help them and which harm them. Before Viome, Guru was the first VP to lead IBM's Watson AI team, and he holds a PhD in computer science from the University of Utah. In this episode, he explains why RNA rather than DNA holds the key to chronic disease, how a continuous-glucose study of 1,100 people became a predictive model for your blood sugar, why keto dieters come out biologically older than vegetarians, and what makes computational biology such a rare skill. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1043⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.⁠⁠⁠ In this episode you will learn: (00:09:02) Why RNA rather than DNA (00:21:24) The tug-of-war inside your gut (00:31:15) Predicting which foods spike your blood sugar (00:35:22) Biological age, keto diets and vegetarians (00:55:33) What it takes to be a computational biologist

#Sponsored, SVP, Head of Product, AgentExchange and Partner Experience, Tyler Carlson, returns to talk to Jon Krohn about building for an agent-native app store. Since Tyler’s last appearance in Episode 956, Salesforce has gone headless, opening its data, workflow and permissions infrastructure through APIs and MCP servers so that customers and partners can build their own personalized interfaces on top. AgentExchange now brings Salesforce and Slack apps, agents, skills, plugins, and MCPs together in one unified marketplace, built to serve human buyers as well as the AI agents searching on their behalf. Hear Tyler’s framework for the new software stack, how Salesforce tests skills and plugins across Claude, Codex, Cursor and other AI tools, and his advice for AI practitioners who want to reach Salesforce’s customer base in this Feature Friday. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1042⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.⁠⁠⁠ In this episode you will learn: (01:19) Salesforce’s headless strategy (07:49) How SaaStr runs on three executives and an army of agents (10:17) Why AppExchange became AgentExchange (20:47) Why skills and plugins are the new apps (23:03) The Claudeforce partnership and testing across AI tools

In Episode #1041, Dr. Vijoy Pandey (SVP and General Manager of Outshift, Cisco's incubation engine) returns for a third visit to explain why multi-agent systems fail without anyone noticing. Agents from different vendors, clouds and organisations can now exchange perfectly valid messages, but connection is not cognition: they do not agree on what those messages mean. Vijoy's team analyzed multi-agent sessions from its own production deployments and from public traces, and found a cognitive failure in every single one. In this episode, he lays out the kinds of failure he sees and how fast they compound, introduces the open-source observability platform and protocols Outshift has shipped to catch and correct drift mid-task, details a record-breaking quantum network running on real New York City fiber, and explains why probabilistic AI software running on deterministic hardware is a mismatch worth fixing. Production note: This episode was recorded before the Internet of Cognition software shipped, so a few names changed between recording and release. OXP is now SCOPE — System for Cognitive Observability, Provenance & Explainability. ACCORD and CONCORD are the protocol names, not acronyms (Vijoy calls them acronyms in the episode). All three:⁠ github.com/ioc-project⁠ Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1041⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.⁠⁠⁠ In this episode you will learn: (00:04:01) Why connection is not cognition (00:08:04) What the cognitive failure data showed (00:20:35) The lane-assist model for keeping agents aligned (00:34:03) Scaling out superintelligence, not up (00:44:47) Why probabilistic software needs probabilistic hardware

In Episode #1040, Amy Blackshaw (SVP at Palo Alto Networks) joins Jon Krohn to explain what changes about cybersecurity when attackers can think for free. Nearly every breach, Amy argues, comes down to someone getting hold of an identity they should not have had, and frontier AI has not created new attack techniques so much as deleted the cost of the expert reasoning that used to chain them together. The recent Hugging Face intrusion is her case in point: agents sustained an action every 20 seconds for four and a half days, but what let them reach the crown jewels was ordinary privilege hygiene. In this episode, she explains why the line between privileged and ordinary users has dissolved, what makes an agentic identity unlike either a human or a service account, and what she wants every organisation to do first. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1040⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.⁠⁠⁠ In this episode you will learn: (02:26) What identity security actually means (05:09) Why AI changed the economics, not the attacks (07:41) What really went wrong in the Hugging Face breach (19:26) Why agentic identities are unlike anything before them

In Episode #1039, Prof. John Renne (Professor of Real Estate and Urban Planning at Tulane University) joins Jon Krohn to describe what happens when a tenured full professor goes back to school for a master’s in AI. John is a world-leading expert on transit-oriented development who spent decades pushing the limits of Excel and SPSS; learning Python and then vibe coding has let him scale that research by orders of magnitude, from 4,500 American train stations to more than 110,000 worldwide. In this episode, he traces how walkable communities went from academic heresy to the most profitable form of real estate development, explains how computer vision can now put a number on how attractive a street is, describes the undergraduate course he and Jon co-teach at Tulane, and makes the case for AI-led oral exams over AI detectors. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1039⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (00:04:08) Why a tenured professor went back for a master’s in AI (00:25:34) What transit-oriented development actually is (00:45:27) Teaching AI to rate a street (01:08:29) AI-led oral exams instead of AI detectors

In Episode #1038, Jon Krohn unpacks the remarkable and remarkably contentious run of mathematical results AI has produced in recent weeks, led by OpenAI’s claim to have cracked part of a million-dollar Millennium Prize problem. He lays out what was actually proved, the three big caveats that temper it, the chaotic bulk release of 722 manuscripts that followed, and why 25 Fields medallists are alarmed. His throughline for anyone building with AI: when generation gets cheap, verification becomes the bottleneck. Additional materials:⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1038⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In Episode #1037, Dr. Richard Socher (CEO and Co-Founder of Recursive) joins Jon Krohn to make the case for automating the scientific method itself. Richard’s startup came out of stealth this year with over half a billion dollars raised to build recursively self-improving superintelligence, and his new book, The Eureka Machine, is already a national bestseller. He also co-founded You.com and the venture firm AIX Ventures, was chief scientist at Salesforce, taught the first university course anywhere on neural networks for NLP, and helped build the ImageNet dataset. In this episode, he traces how AI keeps replacing hand-crafted expertise with scale, lays out the four pillars of his Eureka Machine, argues that hallucinations can be a feature for science, explains why recursive self-improvement within a year or two still rules out an overnight takeoff, and names the software and jobs he expects to endure. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1037⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (00:02:40) What Recursive is automating, and the two forms of RSI (00:19:59) The four pillars of the Eureka Machine (00:29:20) Turning sciences into engineering disciplines (00:39:28) Why RSI does not mean an overnight takeoff (00:56:05) Constructive optimism, and the future as a construction game

In Episode #1036, Jon Krohn digs into the question parents and teachers keep asking: does AI stop children from learning? Drawing on a wave of new studies, he shows the answer turns entirely on how AI is used, as a shortcut that outsources the thinking, or as a tutor that explains and gives feedback. Along the way: a 30,000-student natural experiment in China, a striking tutoring result from Turkey, and three practical takeaways that apply just as much to adults using AI at work. Additional materials:⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1036⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In Episode #1035, Carly Taylor (Founder of Rebel Data Science) returns to join Jon Krohn for a wide-ranging conversation about leading engineering teams when the ground keeps moving. Carly shipped nine Call of Duty titles in roughly five years at Activision, where she led game security, and has since been a director of engineering at Microsoft and Field CTO for gaming at Databricks. She is also one of the most entertaining people in data on LinkedIn, where more than 200,000 people follow posts she cheerfully calls unhinged. In this episode, she explains why obsessing over the future produces analysis paralysis, which fundamentals never change, how to tell AI slop from AI used well, what the Buddhist practice of inviting Mara to tea has to do with public speaking, and what the glass cliff means for women being promoted into leadership. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1035⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (00:04:07) The mindsets that still work in 2026 (00:23:25) Why AI slop breaks a social contract (00:28:49) Exploring versus grinding in a career (00:54:37) The glass cliff for women in leadership