『The Thinking Machine』のカバーアート

The Thinking Machine

The Thinking Machine

著者： Jonathan Stephens
無料で聴く

概要

We’re entering a new era in robotics. One where the bottleneck isn’t just algorithms, it’s the entire stack. The foundation models, the data pipelines, the simulation environments, the training infrastructure. All of it has to come together for robots to move from demos to deployment.

The Thinking Machine Podcast goes deep with the researchers, founders, and engineers working across this stack. That means conversations with teams building robotics foundation models like Groot and Gemini Robotics, architects of world models and neural simulators, and the people designing the data collection systems that make training possible at scale.

If you’re building in robotics, investing in the space, or trying to understand where this field is really headed, this podcast is for you.

2026 Jonathan Stephens 科学
エピソード
  • Why Robotics Is Harder Than It Looks with Chris Paxton

    Why Robotics Is Harder Than It Looks with Chris Paxton
    2026/02/24

    Robots can walk. They can dance. They can even do backflips.

    But can they reliably fold your laundry, make coffee, or recover from mistakes in your kitchen?

    In this episode, I sit down with robotics researcher Chris Paxton to talk about what’s actually hard about building intelligent robots.

    We explore:

    • Why robotics today is fundamentally different than it was 10 years ago
    • The rise of world models and robot imagination
    • Why contact and manipulation tasks are harder than navigation for robots
    • The compounding error problem in long-horizon tasks
    • Why robotics evaluation is still an unsolved challenge
    • How new data pipelines and egocentric data are accelerating progress

    If you’ve seen humanoids walking around conferences and wondered, “Are we really close?”, this episode brings clarity.

    Follow Chris on X: @chris_j_paxton
    Check out RoboPapers for deeper dives into robotics research: https://www.youtube.com/@RoboPapers
    続きを読む 一部表示
    50 分
  • Modeling the Real World with Tolga Kart

    Modeling the Real World with Tolga Kart
    2026/02/10

    Tolga Kart spent seven years building massive 3D worlds for Call of Duty at Sledgehammer Games. Then he left gaming for Tesla Autopilot, led simulation at Parallel Domain, and now he's the CEO of Third Dimension AI, a company building neural simulators that reconstruct reality from sensor data.

    In this episode, we dig into SuperSim, Third Dimension's first product, which takes driving logs and reconstructs them into photorealistic 4D environments where robots can train and validate their behavior. The results look so real that Tolga has to convince people they're not just watching video.

    In this episode we discuss:
    - How SuperSim reconstructs real-world scenes in hours, not months
    - The difference between a "digital twin" and a "digital cousin"
    - Why procedural generation hit its limits for robotics simulation
    - The domain gap problem and why it's finally being solved
    - Generating synthetic edge cases: erratic drivers, collapsing bridges, kids running into the street
    - Why Gaussian Splatting is a good medium for robotics simulation
    - What's next for simulation for humanoids, drones, and beyond

    About Tolga Kart:
    Tolga Kart is the Co-Founder and CEO of Third Dimension AI. He brings over 2 decades of experience building cutting-edge technology in gaming, autonomy, and AI. Tolga began his career in gaming, shipping two Call of Duty titles at Activision Games before transitioning to autonomous vehicles. At Tesla, he built the Autopilot TPM team and rebuilt the simulation team, fully integrating it into Autopilot's development framework. Most recently, he led and scaled Parallel Domain's engineering organization in two years.

    Follow Tolga on LinkedIn: https://www.linkedin.com/in/tolgakart/
    Follow Tolga on X: https://x.com/tolgakart

    About Third Dimensions AI:
    Third Dimension AI is a spatial generation company building the 3D worlds that will power tomorrow's embodied AI—from robots to autonomous vehicles—and enable new frontiers of creativity in gaming and entertainment. Third Dimension was founded in 2024 and backed by venture capital firms Felicis, Abstract, Soma Capital, MVP Ventures, and Solari Capital.

    To learn more, visit https://www.thirddimension.ai

    Thanks to Lightwheel for making this episode possible. Learn about how Lightwheel is making physical AI successful at: https://www.lightwheel.ai
    続きを読む 一部表示
    51 分
まだレビューはありません