The Generalist

Much of the fear around AI centers on misalignment – the idea that powerful systems might act against human interests. Vincent Weisser worries about something different: what happens if advanced AI systems are perfectly aligned with the interests of a small group of institutions? That concern led him to co-found Prime Intellect, a startup building open infrastructure for training and deploying advanced AI models. Before Prime Intellect, Weisser helped organize Vitalik Buterin’s Zuzalu experiment and worked in decentralized science, where he helped unlock roughly $40 million in funding for unconventional research. Today, he’s applying that same open ethos to AI, working to ensure the tools that shape superintelligence remain broadly accessible rather than concentrated in the hands of a few.
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In our conversation, we explore:
Why Vincent believes multiple superintelligences are safer than one
The intellectual influences that shaped Vincent’s thinking about intelligence and progress, including David Deutsch and Nick Bostrom
Prime Intellect’s evolution from distributed compute infrastructure to frontier model training and reinforcement learning tools
Why Vincent believes open and decentralized science could accelerate discovery
The Zuzalu experiment and what it suggests about the future of scientific communities
The role of aesthetics and craft in building technology
Why Europe might have a cultural advantage in a post-superintelligence world
Vincent’s predictions for the next five years of AI
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Thank you to the partners who make this possible
Granola: The app that might actually make you love meetings.
Brex: The intelligent finance platform.
Rippling: Stop wasting time on admin tasks, build your startup faster.
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Transcript: https://www.generalist.com/p/why-one-superintelligence-is-more
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Timestamps
(00:00) Introduction to Vincent Weisser
(03:28) The book behind Prime Intellect’s name
(07:35) The case for suffering
(09:35) An overview of Prime Intellect
(13:03) Why open source models matter
(21:18) Vincent’s intellectual influences
(25:17) Early years in the startup scene
(31:48) Funding science outside traditional institutions
(41:22) The past 6 months of AI progress
(43:45) Deciding to build Prime Intellect
(46:55) Why GPUs were the right starting point
(51:39) Training models on Prime Intellect
(59:48) Why beauty matters
(1:03:48) The Zuzalu experiment
(1:06:27) Prime Intellect’s AGI Easter egg
(1:11:13) Predictions for the next five years
(1:15:09) Final meditations
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Follow Vincent Weisser
LinkedIn: https://linkedin.com/in/vincentweisser
X: https://x.com/vincentweisser
Goodreads: https://www.goodreads.com/user/show/69248416-vincent-weisser
Website: https://primeintellect.ai
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Resources and episode mentions: https://www.generalist.com/p/why-one-superintelligence-is-more⁠
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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
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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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Transcript: https://www.generalist.com/p/karol-hausman-physical-intelligence
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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
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Follow Karol Hausman
LinkedIn: https://www.linkedin.com/in/karolhausman
X: https://x.com/hausman_k
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Resources and episode mentions: https://www.generalist.com/p/karol-hausman-physical-intelligence
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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
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Thank you to the partners who make this possible
Granola: The app that might actually make you love meetings
Brex: The intelligent finance platform.
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Transcript: https://www.generalist.com/p/americas-electric-power-grid-is-broken⁠
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Timestamps
(00:00) Introduction to Zach Dell and Base
(02:08) The Hawaiian lava field solar project and early energy curiosity
(07:03) Investing vs. operating
(09:31) Lessons from Phil Jackson on aligning talented teams
(14:27) Lessons from his parents
(18:20) The loneliness of solo founding and the value of co-founders
(23:45) Justin’s strengths as a co-founder and how their partnership formed
(29:55) Why Base became the obvious focus
(32:08) The original vision and the three reversals
(34:58) The US power grid and what makes Texas different
(39:19) Why batteries matter and what Base is building
(41:12) How Base works in two market types
(45:10) Base’s core product
(46:50) The software behind Base’s battery network
(48:20) Base’s partnerships with battery cell makers
(49:51) The Gen 2 hardware mistake and the lesson in risk management
(51:08) Dino’s strengths as Head of Hardware
(52:36) Base’s positioning as grid infrastructure
(53:29) Building a beloved energy brand
(58:01) How hiring at Base has evolved
(1:01:10) AI workflows at Base
(1:03:00) Zach’s dedicated deep work time
(1:05:54) Final meditations
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Follow Zach Dell
LinkedIn: https://www.linkedin.com/in/zach-dell-a631a554
X: https://x.com/ZachBDell
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Resources and episode mentions: https://www.generalist.com/p/americas-electric-power-grid-is-broken
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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
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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.
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Transcript: https://www.generalist.com/p/everyone-is-betting-on-bigger-llms
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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
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Follow Eve Bodnia
LinkedIn: https://www.linkedin.com/in/eve-bodnia-351b41355
X: https://x.com/evelovesolive
Website: https://logicalintelligence.com
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Resources and episode mentions: https://www.generalist.com/p/everyone-is-betting-on-bigger-llms⁠
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].

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
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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.
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Transcript: https://www.generalist.com/p/how-bolt-survived-an-85-revenue-crash
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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
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Follow Markus Villig
X: https://x.com/villigm
LinkedIn: https://www.linkedin.com/in/markusvillig
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Resources and episode mentions: https://www.generalist.com/p/how-bolt-survived-an-85-revenue-crash
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Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].