In this episode, Jacob sits down with Karol Hausman (Co-Founder) and Danny Driess (Research Scientist) from Physical Intelligence, two of the minds behind some of the most exciting advances in robotics. They unpack the last decade of progress in AI robotics, from early skepticism to the breakthroughs powering today’s generalist robot models.

The conversation covers everything from folding laundry with robots to building scalable data pipelines, the limits of simulation, and what it’ll take to bring robot assistants into everyday homes. It's a wide-ranging and thoughtful look at where robotics is headed, as well as how fast we might get there.

(0:00) Intro
(1:31) Early Days in Robotics
(2:08) Shift to Learning-Based Robotics
(4:50) Challenges and Breakthroughs
(8:45) Google's Role and Spin-Out Decision
(15:08) Comparing Robotics to Self-Driving Cars
(19:18) Hardware and Intelligence
(21:05) Future Milestones and Scaling Challenges
(33:23) Data Collection and Infrastructure Needs
(35:49) Choosing and Tackling Complex Tasks
(38:49) Evaluating Model Performance
(41:28) The Role of Simulation in Robotics
(44:27) Research Strategies and Hiring
(48:16) Open Source and Community Impact
(52:27) Advancements in Training and Model Efficiency
(58:45) Future of Robotics and AI
(1:01:16) Quickfire

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

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