Mario Gabriele 🦊

@hausman_k is the co-founder and CEO of @physical_int, a robotics company building a general-purpose “AI brain for the physical world.” The company has raised more than $1 billion in funding to develop foundation models that allow robots to operate across many machines, environments, and tasks rather than being programmed for a single purpose. In our conversation, we explore: • The moment a lecture from Sergey Levine convinced him to abandon his PhD research direction and pivot fully to deep learning • The case for building a general “AI brain” for the physical world rather than a single specialized robot • The role of real-world data in training robots, the limits of simulation, and how deployment could create a powerful data flywheel • The unique challenges of physical intelligence and why robots must operate with far higher reliability than language models Thank you to the partners who make this possible - @brexHQ: The intelligent finance platform: brex.com/mario - @meetgranola: The app that might actually make you love meetings: granola.ai/mario Timestamps (00:00) Intro (04:05) Karol’s early fascination with robots (18:21) Karol’s entry point to robotics and PhD program (25:49) Combining robotics with LLMs: The Taylor Swift demo (30:48) The 1970s SHRDLU AI experiment (39:40) How research shapes what Physical Intelligence builds (49:07) The return of reinforcement learning in robotics (1:00:00) NVIDIA’s simulation engines (1:07:31) Compensating for missing senses

For decades, America’s electrical system has rewarded utilities for building more infrastructure, not for lowering costs. The result is a grid that expanded but rarely improved. @ZachBDell, co-founder and CEO of @basepowerco, is building a different kind of power company. In our conversation, we explore: • How a failed college solar project and early energy experiments in India pulled Zach into the power industry • How the U.S. grid’s regulatory structure discourages innovation and why Texas’s deregulated market creates space for new power companies • Base’s “make, move, store, sell” framework for thinking about the full power stack • How aggressive AI adoption is compressing cycle times and why slow adopters risk falling behind Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @brexHQ: The intelligent finance platform: brex.com/mario (00:00) Introduction to Zach Dell and Base (09:31) Lessons from Phil Jackson on aligning talented teams (21:49) Justin’s strengths as a co-founder and how their partnership formed (30:55) Why Base became the obvious focus (41:44) How Base works in two market types (50:43) The Gen 2 hardware mistake and the lesson in risk management (58:45) How hiring at Base has evolved (1:06:29) Final meditations

For decades, America’s electrical system has rewarded utilities for building more infrastructure, not for lowering costs. The result is a grid that expanded but rarely improved. @ZachBDell, co-founder and CEO of @basepowerco, is building a different kind of power company. In our conversation, we explore: • How a failed college solar project and early energy experiments in India pulled Zach into the power industry • How the U.S. grid’s regulatory structure discourages innovation and why Texas’s deregulated market creates space for new power companies • Base’s “make, move, store, sell” framework for thinking about the full power stack • How aggressive AI adoption is compressing cycle times and why slow adopters risk falling behind Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @brexHQ: The intelligent finance platform: brex.com/mario (00:00) Introduction to Zach Dell and Base (09:31) Lessons from Phil Jackson on aligning talented teams (21:49) Justin’s strengths as a co-founder and how their partnership formed (30:55) Why Base became the obvious focus (41:44) How Base works in two market types (50:43) The Gen 2 hardware mistake and the lesson in risk management (58:45) How hiring at Base has evolved (1:06:29) Final meditations

For decades, America’s electrical system has rewarded utilities for building more infrastructure, not for lowering costs. The result is a grid that expanded but rarely improved. @ZachBDell, co-founder and CEO of @basepowerco, is building a different kind of power company. In our conversation, we explore: • How a failed college solar project and early energy experiments in India pulled Zach into the power industry • How the U.S. grid’s regulatory structure discourages innovation and why Texas’s deregulated market creates space for new power companies • Base’s “make, move, store, sell” framework for thinking about the full power stack • How aggressive AI adoption is compressing cycle times and why slow adopters risk falling behind Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @brexHQ: The intelligent finance platform: brex.com/mario (00:00) Introduction to Zach Dell and Base (09:31) Lessons from Phil Jackson on aligning talented teams (21:49) Justin’s strengths as a co-founder and how their partnership formed (30:55) Why Base became the obvious focus (41:44) How Base works in two market types (50:43) The Gen 2 hardware mistake and the lesson in risk management (58:45) How hiring at Base has evolved (1:06:29) Final meditations

For decades, America’s electrical system has rewarded utilities for building more infrastructure, not for lowering costs. The result is a grid that expanded but rarely improved. @ZachBDell, co-founder and CEO of @basepowerco, is building a different kind of power company. In our conversation, we explore: • How a failed college solar project and early energy experiments in India pulled Zach into the power industry • How the U.S. grid’s regulatory structure discourages innovation and why Texas’s deregulated market creates space for new power companies • Base’s “make, move, store, sell” framework for thinking about the full power stack • How aggressive AI adoption is compressing cycle times and why slow adopters risk falling behind Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @brexHQ: The intelligent finance platform: brex.com/mario (00:00) Introduction to Zach Dell and Base (09:31) Lessons from Phil Jackson on aligning talented teams (21:49) Justin’s strengths as a co-founder and how their partnership formed (30:55) Why Base became the obvious focus (41:44) How Base works in two market types (50:43) The Gen 2 hardware mistake and the lesson in risk management (58:45) How hiring at Base has evolved (1:06:29) Final meditations

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@evelovesolive is the co-founder and CEO of @logic_int, which is developing energy-based reasoning models (EBMs) as an alternative to large language models. She argues that LLMs, which operate by recognizing and recombining patterns within language space, are structurally incapable of genuine reasoning. In our conversation, we explore: • The $4 vs. $15,000 benchmark, and what it tells us about the cost of guessing vs. knowing • How Logical Intelligence showed spontaneous knowledge transfer at just 16M parameters • Why systems like chip design, surgical robotics, and power grids need more than probabilistic AI • How meeting Grigori Perelman as a teenager shaped Eve’s views on ego and ownership in science Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @withpersona: Trusted identity verification for any use case: withpersona.com/generalist Timestamps (00:00) Introduction (03:03) Eve’s encounter with Grigori Perelman (09:02) The manifold hypothesis and language (22:58) Spirituality and creativity (27:00) Theory vs. experiment (42:08) Energy-based models explained (48:01) AGI defined (58:09) Early investors in Logical Intelligence (1:03:42) Final meditations

@evelovesolive is the co-founder and CEO of @logic_int, which is developing energy-based reasoning models (EBMs) as an alternative to large language models. She argues that LLMs, which operate by recognizing and recombining patterns within language space, are structurally incapable of genuine reasoning. In our conversation, we explore: • The $4 vs. $15,000 benchmark, and what it tells us about the cost of guessing vs. knowing • How Logical Intelligence showed spontaneous knowledge transfer at just 16M parameters • Why systems like chip design, surgical robotics, and power grids need more than probabilistic AI • How meeting Grigori Perelman as a teenager shaped Eve’s views on ego and ownership in science Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @withpersona: Trusted identity verification for any use case: withpersona.com/generalist Timestamps (00:00) Introduction (03:03) Eve’s encounter with Grigori Perelman (09:02) The manifold hypothesis and language (22:58) Spirituality and creativity (27:00) Theory vs. experiment (42:08) Energy-based models explained (48:01) AGI defined (58:09) Early investors in Logical Intelligence (1:03:42) Final meditations

@evelovesolive is the co-founder and CEO of @logic_int, which is developing energy-based reasoning models (EBMs) as an alternative to large language models. She argues that LLMs, which operate by recognizing and recombining patterns within language space, are structurally incapable of genuine reasoning. In our conversation, we explore: • The $4 vs. $15,000 benchmark, and what it tells us about the cost of guessing vs. knowing • How Logical Intelligence showed spontaneous knowledge transfer at just 16M parameters • Why systems like chip design, surgical robotics, and power grids need more than probabilistic AI • How meeting Grigori Perelman as a teenager shaped Eve’s views on ego and ownership in science Thank you to the partners who make this possible - @meetgranola: The app that might actually make you love meetings: granola.ai/mario - @withpersona: Trusted identity verification for any use case: withpersona.com/generalist Timestamps (00:00) Introduction (03:03) Eve’s encounter with Grigori Perelman (09:02) The manifold hypothesis and language (22:58) Spirituality and creativity (27:00) Theory vs. experiment (42:08) Energy-based models explained (48:01) AGI defined (58:09) Early investors in Logical Intelligence (1:03:42) Final meditations