Why Robotics Data is 250,000 Years Behind LLMs

Lukas Ziegler, Robotics Evangelist, Investor, and Advisor, has spent the past 10 years working across robotics software, commercial roles, content, and investing. Now, he believes the industry is entering a new era. Learn more at: https://bit.ly/NebiusPodcasts In this episode, Evan Helda, Head of Physical AI at Nebius, sits down with Lukas to explore the shift from Robotics 1.0 to Robotics 2.0: a world where you don't program a robot, you just tell it what to do. They discuss why the humanoid debate has been asking the wrong question, why the data gap between LLMs and robotics is vastly misunderstood, and why the companies that will win are already co-building with end users rather than shipping to them. They also get into storytelling: why public exposure builds trust in robots faster than any marketing campaign ever could. 0:00 - Intro teaser 0:40 - Lukas Ziegler’s journey from engineer to robotics evangelist 2:40 - Robotics 2.0: the shift from programmed to general-purpose robots 4:45 - The biggest investment trends in physical AI 7:45 - Why robotics has a massive data problem 11:00 - Synthetic data, AI moats, and the future of RobotOps 17:00 - Why storytelling will determine robotics adoption 19:15 - Preparing for a future where robots free up our time 20:00 - Outro What You'll Learn: -What Robotics 2.0 means and why it's a fundamentally different paradigm from Robotics 1.0. -Why specialized humanoids may have a clearer path to deployment than general-purpose systems. -The massive data gap between LLMs and robotics, and why physical AI will scale gradually. -The three investment theses: verticalized humanoids, RobotOps infrastructure, and data collection. -Why robotics companies should involve end users from the earliest stages of development. -Why exposure beats education when it comes to public trust in robots.