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Strange Loop Podcast

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Strange Loop Podcast
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  • Leading the teams behind the world’s fastest AI | Jensen Huang
    This episode is part of our “Summer Selects” series—curated archival episodes that shifted our perspective and are worth revisiting.NVIDIA founder and CEO Jensen Huang reveals the leadership philosophies and management practices that have made NVIDIA a powerhouse of AI and accelerated computing.Jensen discusses why first-principles thinking is at the core of his decision-making, how he shapes company strategy through action—not words—and why he believes in empowering teams to pursue “barely possible” challenges. He shares his approach to building an organization that attracts exceptional talent, values deep domain expertise, and maintains a flat hierarchy where information travels quickly and everyone contributes.Jensen also reflects on how leadership means creating an environment for others to thrive, why flat organizations win, and how empowering employees at every level leads to breakthrough innovation.Whether you’re a founder, manager, or aspiring leader, this interview is packed with actionable wisdom and inspiration from one of technology’s most respected CEOs.What's in this episodeHow Jensen challenged classic management playbooks to create a nimble, empowered organizationThe value of direct communication, transparency, and learning from everyone in the companyWhy NVIDIA avoids siloed structures, status reports, and commodity workThe “top five things” system for keeping a pulse on the company and aligning action with strategyWhy continuous, adaptive planning beats rigid five-year plans in fast-moving industriesThe importance of humility, adaptability, and changing your mind as a leaderInsights on creating a culture where people can do their life’s best work—and walk away from the wrong work—Transcript: Coming—About Strange LoopStrange Loop is a podcast about how artificial intelligence is reshaping the systems we live and work in. Each episode features deep, unscripted conversations with thinkers and builders reimagining intelligence, leadership, and the architectures of progress. The goal is not just to follow AI’s trajectory, but to question the assumptions guiding it.Subscribe for more conversations at the edge of AI and human knowledge.—Timestamps(00:04) Staying current in tech as a leader  (01:14) Building intuition for industry change  (03:22) Running a company on first principles  (04:25) Attracting, empowering, and organizing top talent  (07:31) Leadership style: direct, inclusive, evolving  (10:21) "Top Five Things" and transparent communication  (13:16) Continuous planning and true empowerment  —Where to find JensenLinkedIn: https://www.linkedin.com/in/jenhsunhuang/Blog: https://blogs.nvidia.com/blog/author/jen-hsun-huang/—Where to find JoelLinkedIn: https://www.linkedin.com/in/joel-hellermark/X: https://x.com/joelhellermark
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  • How machine learning could save millions of lives | Daphne Koller
    This episode is part of our “Summer Selects” series—curated archival episodes that shifted our perspective and are worth revisiting.Daphne Koller—AI pioneer, founder of Coursera, and CEO of Insitro—sits down with Sana founder and CEO Joel Hellermark to explore the groundbreaking intersection of digital technology, scientific discovery, and human health.In this episode of Strange Loop, Daphne shares her inspiring journey from a prodigious student to leading some of the most important advances in AI, education, and biotech. She reveals how machine learning is unlocking the secrets of biology, enabling new treatments, and offering hope for solving some of humanity’s toughest medical challenges.Daphne also discusses the ethical challenges, the importance of collaboration across fields, and her vision for a future where AI and biology together unlock new possibilities for patients worldwide.What's in this episodeFrom early academic prodigy to founding Coursera and InsitroHow AI and massive datasets are transforming drug discovery and biologyWhy data quality and removing human bias are key to scientific breakthroughsThe exponential growth curves in AI and genomics—and why we’re at an inflection pointChallenges and opportunities in building high-impact, interdisciplinary teamsThe future of healthcare: personalized medicine, early detection, and longer, healthier livesReflections on culture, leadership, and inspiring the next generation of scientists and engineers—Transcript: Coming—About Strange LoopStrange Loop is a podcast about how artificial intelligence is reshaping the systems we live and work in. Each episode features deep, unscripted conversations with thinkers and builders reimagining intelligence, leadership, and the architectures of progress. The goal is not just to follow AI’s trajectory, but to question the assumptions guiding it.Subscribe for more conversations at the edge of AI and human knowledge.—Timestamps(00:00:00) Early days of AI(00:04:12) Intersecting biology & AI(00:06:22) Predicting biology(00:10:12) insitro’s vision(00:12:30) Harmonizing datasets(00:13:53) Finding patterns(00:15:39) Addressing biases(00:17:02) Importance of finetuning(00:19:35) Layers of multimodality(00:21:34) Actionable insights(00:23:57) Bilingual colleagues(00:26:14) Biologists’ future(00:29:25) Eroom’s Law(00:34:57) Lack of data(00:39:51) Incentivizing scientists(00:43:56) Daphne’s motivation(00:46:40) Future of medicine—Where to find DaphneLinkedIn: https://www.linkedin.com/in/daphne-koller-4053a820/X: https://x.com/daphnekoller—Where to find JoelLinkedIn: https://www.linkedin.com/in/joel-hellermark/X: https://x.com/joelhellermark
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  • Rethinking AI’s power and limits | Geoffrey Hinton
    This episode is part of our “Summer Selects” series—curated archival episodes that shifted our perspective and are worth revisiting.Hear the Godfather of AI Geoffrey Hinton reflect on the journey from the early days of neural networks to today’s breakthroughs in artificial intelligence, sharing unique insights from decades of pioneering research.Discover why Hinton believes that scaling up AI models leads to creativity and reasoning that rivals (and may eventually surpass) human intelligence. Hear his candid thoughts on how language models learn, why intuition and training data matter, and what current models still have to learn from the human brain.This conversation between Geoffrey Hinton and Joel Hellermark was originally recorded in April 2024 at the Royal Institute of Great Britain in London. An edited version was premiered at Sana AI Summit 2024 in Stockholm, Sweden.What's in this episodeThe surprising similarities (and differences) between AI and the human mindWhy multi-modality and fast weights could be the next frontiers in AIHow AI models might develop subjective experience and even “feelings”Hinton’s advice to young researchers about trusting intuition and challenging consensusReflections on leadership, collaboration, and building teams for breakthrough science—Transcript: Coming—About Strange LoopStrange Loop is a podcast about how artificial intelligence is reshaping the systems we live and work in. Each episode features deep, unscripted conversations with thinkers and builders reimagining intelligence, leadership, and the architectures of progress. The goal is not just to follow AI’s trajectory, but to question the assumptions guiding it.Subscribe for more conversations at the edge of AI and human knowledge.—Timestamps(00:00:00) Early inspirations(00:05:05) Meeting Ilya Sutskever(00:06:12) Ilya’s intuition(00:09:00) Understanding of LLMs(00:15:15) Scaling neural networks(00:18:30) What is language?(00:21:35) The GPU revolution(00:25:05) Human Brain Insights(00:29:05) Feelings & analogies(00:32:58) Problem selection(00:35:21) Gradient processing(00:36:52) Ethical implications(00:40:15) Selecting talent(00:41:49) Developing intuition(00:43:50) The road to AGI(00:45:00) Proudest moment—Where to find GeoffreyX: https://x.com/geoffreyhinton—Where to find JoelLinkedIn: https://www.linkedin.com/in/joel-hellermark/X: https://x.com/joelhellermark
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  • How to build an AI-first organization | Ethan Mollick
    Most companies are using AI to cut costs. Ethan Mollick argues that the biggest mistake companies make is thinking too small.In the first episode of Strange Loop, Wharton professor and leading AI researcher Ethan Mollick joins Sana founder and CEO Joel Hellermark for a candid and wide-ranging conversation about the rapidly changing world of AI at work.They explore how AI is not just an efficiency tool but a turning point—one that forces a choice between incremental optimization and transformational scale. The discussion covers the roots of machine intelligence, the relevance of AGI, and what it takes to build organizations designed from the ground up for an AI-native future.What’s in this episodeWhy most companies are underestimating what AI makes possibleThe tension between using AI for efficiency vs. scaling ambitionHow traditional org charts, built for a human-only workforce, are breakingThe collapse of apprenticeship and its long-term implications- How prompting is becoming a foundational business skillWhy “cheating” with AI may be the new form of learningThe risks of using AI to optimize the past instead of inventing the futureWhat it means to build truly AI-native teams and organizations—Transcript: https://sanalabs.com/strange-loop/ethan-mollick—About Strange LoopStrange Loop is a podcast about how artificial intelligence is reshaping the systems we live and work in. Each episode features deep, unscripted conversations with thinkers and builders reimagining intelligence, leadership, and the architectures of progress. The goal is not just to follow AI’s trajectory, but to question the assumptions guiding it.Subscribe for more conversations at the edge of AI and human knowledge.—Timestamps(00:20) Origins: AI in the early days at MIT(01:53) Defining and testing intelligence: Beyond the Turing test(06:35) Redesigning organizations for the AI era(08:56) Human augmentation or replacement(14:58) Navigating AI's jagged frontier(17:18) The 3 ingredients for successful AI adoption(23:31) Roles to hire for an AI-first world(33:41) Do orgs need a Chief AI officer?(39:45) The interface for AI and human collaboration(43:50) Rethinking the goals of enterprise AI(49:15) The case for abundance(52:30) Best and worse case scenarios(58:51) Avoiding the trap of enterprise AI KPIs—Where to find EthanNewsletter: https://www.oneusefulthing.org/LinkedIn: https://www.linkedin.com/in/emollick/X: https://x.com/emollick—Where to find JoelLinkedIn: https://www.linkedin.com/in/joel-hellermark/X: https://x.com/joelhellermark
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Conversations at the edge of artificial intelligence and human knowledge. Hosted by Joel Hellermark.
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