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Why Robots Still Struggle With Simple Tasks (And What Might Finally Change That) | Karol Hausman, Co-Founder & CEO of Physical Intelligence

2026-03-17 20:03:46

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Karol Hausman is the co-founder and CEO of Physical Intelligence, 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. The core thesis: the same scaling dynamics that transformed language models may also unlock robotic intelligence. But only if you resist every commercial pressure pushing you toward specialization. The central challenge isn’t mechanical design. It’s intelligence: how robots learn, generalize, and interact with a physical world that is far harder to simulate than it is to describe. Before launching Physical Intelligence, Karol worked at Google Brain and Stanford University, studying robot learning alongside researchers Sergey Levine and Chelsea Finn, who later became his co-founders.

In our conversation, we explore:

  • How growing up in a small town in Poland and watching Star Wars sparked Karol’s fascination with robots

  • The moment a lecture from Sergey Levine convinced him to abandon his PhD research direction and pivot fully to deep learning

  • Why robotics has historically lagged behind breakthroughs in language models

  • 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 return of reinforcement learning and the parallels between human learning and robot training

  • 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

Brex: The intelligent finance platform.

Granola: The app that might actually make you love meetings.

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Timestamps

(00:00) Intro

(04:05) Karol’s early fascination with robots

(07:38) How Karol relates to Fei-Fei Li’s biography

(08:52) What inspired Karol to build better robots

(11:19) Philosophical influences

(15:33) Parallels between The Inner Game of Tennis and robotics

(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

(32:33) Founding Physical Intelligence

(35:13) How Lachy Groom got involved

(39:40) How research shapes what Physical Intelligence builds

(45:22) The importance of real-world data

(49:07) The return of reinforcement learning in robotics

(53:31) The risk of commercializing too early

(55:47) Finding the right partners for the business

(57:13) Open research questions

(1:00:00) NVIDIA’s simulation engines

(1:01:57) The surprising speed of progress

(1:04:16) Reliability in robotics

(1:07:31) Compensating for missing senses

(1:12:28) Book recommendation

Follow Karol Hausman

LinkedIn: https://www.linkedin.com/in/karolhausman

X: https://x.com/hausman_k

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

America’s Electric Power Grid Is Broken. This Startup Is Trying to Fix It. (Zach Dell, co-founder & CEO of Base)

2026-03-10 20:03:39

“You must get comfortable with the notion that a lot of really smart people you respect are going to explain to you in excruciating detail why this is not going to work...You have to be able to see through that and have a clear vision in your mind for why it is going to work.” — Zach Dell, co-founder and CEO of Base

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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. Zach Dell, co-founder and CEO of Base, is building a different kind of power company. In under three years, Base has grown into a vertically integrated business valued in the billions. It combines home batteries and software to store electricity when it is cheap and deliver it when demand spikes. Dell’s interest in energy began long before Base. In college, he tried to lease a Hawaiian lava field for a solar project. He also experimented with anaerobic digestion systems in India and worked at Blackstone and Thrive Capital, where he met his co-founder. His bet is simple but ambitious: the next phase of the grid will come from increasing utilization rather than constantly building new infrastructure.

In our conversation, we explore:

  • How a failed college solar project and early energy experiments in India pulled Zach into the power industry

  • The lessons he absorbed from his parents, including truth-seeking, reinvention, and competitive endurance

  • How the U.S. grid’s regulatory structure discourages innovation and why Texas’s deregulated market creates space for new power companies

  • Why batteries are best understood as a time-shifting technology that increases grid utilization and reduces total system costs, not simply as energy generators

  • Base’s “make, move, store, sell” framework for thinking about the full power stack

  • How Base aims to become the first beloved energy company

  • How Zach identified Justin as a world-class operator and built the trust needed to go all-in together on a non-obvious idea

  • How aggressive AI adoption is compressing cycle times and why slow adopters risk falling behind

Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings

Brex: The intelligent finance platform.

Explore the episode

Timestamps

(00:00) Introduction to Zach Dell and Base

(03:06) The Hawaiian lava field solar project and early energy curiosity

(07:58) Investing vs. operating

(09:31) Lessons from Phil Jackson on aligning talented teams

(15:24) Lessons from his parents

(19:19) The loneliness of solo founding and the value of co-founders

(21:49) Justin’s strengths as a co-founder and how their partnership formed

(30:55) Why Base became the obvious focus

(32:21) The original vision and the three reversals

(35:49) The American power grid and what makes Texas different

(40:39) Why batteries matter and what Base is building

(41:44) How Base works in two market types

(45:59) Base’s core product

(47:43) The software behind Base’s battery network

(49:14) Base’s partnerships with battery cell makers

(50:43) The Gen 2 hardware mistake and the lesson in risk management

(52:00) Dino’s strengths as Head of Hardware

(53:20) Base’s positioning as grid infrastructure

(55:39) Building a beloved energy brand

(58:45) How hiring at Base has evolved

(1:01:54) AI workflows at Base

(1:03:44) Zach’s dedicated deep work time

(1:06:29) Final meditations

Follow Zach Dell

LinkedIn: https://www.linkedin.com/in/zach-dell-a631a554

X: https://x.com/ZachBDell

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People

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Subscribe to the show

I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

Infinite Games

2026-02-26 22:58:49

“To be prepared against surprise is to be trained. To be prepared for surprise is to be educated.”

- James Carse, Finite and Infinite Games

Friends,

Evolutionary biology has the concept of “allopatric speciation,” the process that occurs when a species develops separately from those on the mainland. Saved from some evolutionary pressures and exposed to oth…

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Everyone Is Betting on Bigger LLMs. She's Betting They're Fundamentally Wrong. (Eve Bodnia, Founder & CEO of Logical Intelligence)

2026-02-24 21:03:32

“AGI should be just like natural intelligence. Something which plans, something which is able to predict, produce new knowledge, be cheap and efficient, and be adaptive to the environment. It should reason, it should not mimic.” — Eve Bodnia, Founder & CEO, Logical Intelligence

Listen or watch now on
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Eve Bodnia is the co-founder and CEO of Logical Intelligence, 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. Eve's alternative: Kona—an EBM that reasons in abstract latent space, learns rules about the world rather than surface patterns, and can interface with language models as one output channel among many. Eve traces the core ideas behind her architecture to decades of work in symmetry groups, condensed matter physics, and brain science—fields that share, as she explains, the same underlying mathematics. In a public demo, Kona solved a complex reasoning task for roughly $4 in compute, compared to an estimated $15,000 using frontier LLMs. With Yann LeCun serving as founding chair of its technical board, Logical Intelligence sits at the center of a small but growing effort to rethink AI beyond language-based models.

In our conversation, we explore:

  • Why Eve believes LLMs can’t truly extrapolate knowledge, even at larger scale

  • What energy-based reasoning models are—and where the “energy” concept comes from

  • 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

  • What formally verified code generation means for the future of programming

  • Why the math behind particle physics also explains how the brain filters signal from noise

  • How meeting Grigori Perelman as a teenager shaped Eve’s views on ego and ownership in science

  • Why Eve believes humans must remain the constraint-setters in advanced AI

  • How meditation, piano, and Eastern philosophy support her creative process

Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings.

Persona: Trusted identity verification for any use case.

Explore the episode

Timestamps

(00:00) Introduction

(03:03) Eve’s encounter with Grigori Perelman

(05:38) Why bizarre people are Eve’s favorite people

(06:56) Her early obsession with math and physics

(09:02) The manifold hypothesis and language

(11:54) The Kekulé Problem

(14:05) Eve’s upbringing and her CERN research in high school

(17:40) Eve’s academic path

(20:36) Symmetry in nature

(22:58) Spirituality and creativity

(27:00) Theory vs. experiment

(29:03) Uncovering a critical gap in AI models

(33:45) What Logical Intelligence is building

(35:50) Logical Intelligence’s use cases

(42:08) Energy-based models explained

(45:06) LLMs vs. EBMs

(48:01) AGI defined

(51:22) Kona’s knowledge extrapolation

(53:20) The team behind Logical Intelligence

(58:09) Early investors in Logical Intelligence

(58:50) Feynman’s influence on Eve’s work

(1:01:15) How Eve sustains her creativity

(1:03:42) Final meditations

Follow Eve Bodnia

LinkedIn: https://www.linkedin.com/in/eve-bodnia-351b41355

X: https://x.com/evelovesolive

Website: https://logicalintelligence.com

Resources and episode mentions

Books

People

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Subscribe to the show

I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

How Bolt Survived An 85% Revenue Crash And Became Europe's Ride-Hailing Champion (Markus Villig, Founder & CEO)

2026-02-19 21:03:12

“We don’t care that we’re from a small country. We’ve always had the view that if we work harder and [make] smarter decisions, we can beat [any] company in the world, regardless of how big they are.”

Listen or watch now on
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In 2013, on an Estonian island of just 10,000 residents, a teenager borrowed €5,000 from his parents and decided to take on Uber. Twelve years later, Markus Villig leads Bolt, a company operating in 50+ countries, generating nearly €3 billion in revenue, and standing as one of the only European tech companies competing at true global scale. Rather than going head-to-head with incumbents in their strongest markets, Bolt expanded through underserved cities, emerging economies, and overlooked segments of urban transport. When COVID erased 85% of its revenue in weeks, the company didn’t retreat; it staged a kind of corporate “eucatastrophe,” pivoting into food delivery across nearly 20 countries in what became a company-wide sprint. That same bias toward action now shapes Markus’s broader agenda: investing in defense tech for Estonia and Ukraine, pushing for capital markets reform, and advancing a contrarian thesis on autonomous vehicles.

In this conversation, we discuss:

  • How growing up in Soviet-occupied Estonia shaped Markus’s ambition and moral clarity

  • How Bolt’s European ethos and long-term focus on driver retention became a structural advantage

  • The marketplace models and capital discipline that allowed Bolt to outmaneuver better-funded rivals

  • Why Bolt found breakout success in African markets after failing in 12 Western countries

  • The 85% revenue collapse during COVID and the rapid food delivery pivot that reshaped the company

  • Bolt’s partnerships with Stellantis and Pony.ai and its long-term bet on autonomous vehicles

  • Why Ukrainian and Eastern European startups are often outperforming their Western peers

  • Markus’s blueprint for closing Europe’s tech deficit and building globally competitive companies

Thank you to the partners who make this possible

Granola: The app that might actually make you love meetings

Brex: The intelligent finance platform.

Persona: Trusted identity verification for any use case.

Explore the episode

Timestamps

(00:00) Intro

(03:32) How The Lord of the Rings shaped Markus’s worldview

(05:52) Bolt’s underdog story and its existential turning point

(10:22) Estonia’s startup DNA and its imprint on Bolt

(13:38) Europe’s ambition problem

(17:23) Europe’s defense tech gap

(23:09) The need for capital market reform in Europe

(25:13) Bolt’s origin story

(36:35) Frugality as strategy

(38:24) What running Bolt actually demands

(41:27) The hidden costs of being too lean

(42:50) Bolt’s shift to experimentation

(44:10) Bolt’s micromobility strategy

(45:50) How Bolt found the right markets

(50:44) The Serbian mob story

(54:00) Markus on venture capital and lessons from Klarna’s board

(55:40) Why Bolt never sold

(57:08) Bolt’s autonomous vehicle (AV) strategy and key partnerships

(1:05:50) The concept of culture-market fit

(1:07:48) How Bolt operates: writing, hiring, reading, and more

(1:13:15) Markus’s personal strengths

(1:14:15) What people get wrong about business

(1:16:27) Final meditations

Follow Markus Villig

X: https://x.com/villigm

LinkedIn: https://www.linkedin.com/in/markusvillig

Resources and episode mentions

Books

People

Other resources

Subscribe to the show

I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.

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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

Lessons of a First-Time Fund Manager

2026-02-05 23:47:00

Friends,

Four years ago, I set out to raise my first venture fund. The result was Generalist Capital, a $15 million vehicle to invest in a small collection of (hopefully) legendary companies.

The beginning of this year marks something of a turning point. After closing on a few investments, Generalist Capital officially moved from the deployment phase to management and harvesting. That makes it a fitting moment to share the lessons learned along the way. Though venture capital is awash in content, in my view, there’s too little introspective writing on the mental game of fund management. Below, you’ll find my attempt to distill the most important lessons I’ve learned so far. To that end, these are best seen as the lessons of a first-time fund manager, relating primarily to the challenges of starting a fund and establishing an initial viable strategy.

Naturally, the gravity of these lessons will depend on information I cannot give you: my long-term performance as an investor. It will likely take another six to ten years to discover how promising a portfolio I have built with Generalist Capital, and even longer to know definitively if I am any good. As of our last update to LPs, Generalist Capital was performing in the top 10-15% in its vintage, but the data suggests that it takes about six years for a fund to settle into its terminal quartile. There’s still a long way left to run and too much uncertainty to read much into this. I am afraid that this is the best I can offer you.

Let this serve as a reminder, then, if any were needed, that you should take my lessons with a grain of salt. I have achieved little, and every investor must learn to play their own game. Though I hope they spark new ideas for you, these are just the observations of one manager at the beginning of what I hope proves to be a long career.

  1. If this is your first time managing a fund, be extremely skeptical of your early investment urges. You’re probably overly keen to validate your existence to your LPs.

  2. The best companies can go under the radar for a long time. When other VCs asked which of my investments I was most bullish about, I told them freely. It still took several years for a Tier 1 firm to lead a round into the company.

  3. You do not have to wait for a round. If you have enough to offer a company, they’ll find a way to bring you aboard ahead of a formal raise. When you see a startup you love, try to make something happen.

  4. Don’t assume you know your level. New managers often think they can’t get access to rounds led by Tier 1 VCs. With the right pitch, you may be closer than you think.

  5. It’s very rare you see everything you want in a startup: founder, market, traction, and so on. When you do, write a much bigger check than you ordinarily would.

  6. The first investor has a unique relationship with a founder. You can build good relationships no matter when you invest, but the first check in earns a special level of trust.

  7. Contrary to what you might expect, the best companies are not easier to access as round sizes grow. Competition escalates as they succeed, often through late growth.

  8. The best investors often need little more than a sentence to explain why they’ve invested in a company. The longer and more convoluted your investment rationale is, the more skeptical you should be of it.

  9. Find your pace. A generation of managers has been conditioned to deploy vintages in 18-24 months. There is nothing wrong with taking twice as long, or more.

  10. Just because a deal is hot does not mean it is good. Don’t let other people’s urgency influence your desire.

  11. Remind yourself: the best venture firms in the world make a majority of bad investments. Don’t index on a buzzy name.

  12. Conversely, if some of the best investors in the world are backing a startup you don’t consider promising, look again, extremely closely. There’s a good chance you’re missing something important.

  13. Remember, the best investors in the world ≠ the best known investors. Calibrate accordingly.

  14. Don’t assume the best opportunities will land in your lap. Outbound sourcing is a necessity.

  15. Progress is never linear. A company that you had more or less written off can suddenly catch light, and one that was on a breakout trajectory can easily stall or stumble.

  16. Don’t push your anxiety onto your founders. It’s not your job to let them know of every new company that pops up in their space.

  17. If you’re asked for advice, give it honestly, but recognize that you have 0.01% of the context a founder has.

  18. Fight for every dollar. Getting an extra $10K into a breakout company can make a huge difference for a small fund.

  19. Founders respond to conviction. Earnestly explaining to an entrepreneur why you’re excited about their business and showing a desire to move quickly can overcome any number of natural disadvantages.

  20. Be skeptical of a pitch that looks too rational. Great companies often have something paradoxical about them. If something doesn’t quite make sense, that’s a good indication you should lean in, not out.

  21. Be careful you don’t get stuck correcting your last mistake. If you invested too little in a startup that has just started to break out, don’t triple the size of your next check to compensate. Consider each opportunity anew.

  22. If you’re not positioned to catch a wave, don’t chase it. You could burn an entire vintage on second-and third-rate AI companies.

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