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I sit down with Karol Hausman and Kevin Black of Physical Intelligence (Pi) to unpack how they are building a general-purpose robot brain so any robot can perform any task, anywhere. We talk about the convergence of AI, robotics, and automation and what it will take to give machines true physical intelligence.
If you're interested in the future of general-purpose robots, physical AI, or the future of labor, then give this episode a listen/watch.
#robots #ai #decentralization
Chapters:
00:00 Introduction
02:11 Vision-Language-Action Model (VLA) vs Vision-Language Model (VLM)
05:47 "Taylor Swift" Pivotal Moment In Robotics
08:45 Training Robots With Natural Language Prompts
10:55 Pi's "Action Expert" Architecture
14:07 Pi’s Open Source Strategy
17:16 Perspectives On Building Hardware
23:17 Creating An Ecosystem For Physical Intelligence
25:56 Pi 0.5 Model And Open World Generalization
33:23 Hitting Diminishing Returns On Task-Specific Data
36:21 Tackling Real-Time Inference Speed in Robotics
39:38 Improving Context Length
45:58 Importance of In-House Data Collection
48:46 Opportunities For Service Providers In Robotics
49:33 The Role of Hardware in Robotics
51:05 Dealing with Edge Cases And Data Diversity
53:27 Founding Story Of Pi
56:33 Kevin’s Journey To Pi
59:54 Opportunities For Non-Technical Founders In Robotics
01:02:08 Exploring Areas For Early Deployment
01:02:49 Rapid Fire Questions on Robotics
01:03:01 One Assumption AI Researchers Get Wrong
01:07:54 Closing
Follow Jordan on X: https://x.com/jrwolfe
Links to Karol & Kevin’s Work:
Key Influences and Resources Mentioned:
Sergey Levine’s Substack - https://sergeylevine.substack.com/
Subscribe & Follow:
Subscribe to YouTube for more deep dives on decentralization, robots, and the real economy.
By Going DirectI sit down with Karol Hausman and Kevin Black of Physical Intelligence (Pi) to unpack how they are building a general-purpose robot brain so any robot can perform any task, anywhere. We talk about the convergence of AI, robotics, and automation and what it will take to give machines true physical intelligence.
If you're interested in the future of general-purpose robots, physical AI, or the future of labor, then give this episode a listen/watch.
#robots #ai #decentralization
Chapters:
00:00 Introduction
02:11 Vision-Language-Action Model (VLA) vs Vision-Language Model (VLM)
05:47 "Taylor Swift" Pivotal Moment In Robotics
08:45 Training Robots With Natural Language Prompts
10:55 Pi's "Action Expert" Architecture
14:07 Pi’s Open Source Strategy
17:16 Perspectives On Building Hardware
23:17 Creating An Ecosystem For Physical Intelligence
25:56 Pi 0.5 Model And Open World Generalization
33:23 Hitting Diminishing Returns On Task-Specific Data
36:21 Tackling Real-Time Inference Speed in Robotics
39:38 Improving Context Length
45:58 Importance of In-House Data Collection
48:46 Opportunities For Service Providers In Robotics
49:33 The Role of Hardware in Robotics
51:05 Dealing with Edge Cases And Data Diversity
53:27 Founding Story Of Pi
56:33 Kevin’s Journey To Pi
59:54 Opportunities For Non-Technical Founders In Robotics
01:02:08 Exploring Areas For Early Deployment
01:02:49 Rapid Fire Questions on Robotics
01:03:01 One Assumption AI Researchers Get Wrong
01:07:54 Closing
Follow Jordan on X: https://x.com/jrwolfe
Links to Karol & Kevin’s Work:
Key Influences and Resources Mentioned:
Sergey Levine’s Substack - https://sergeylevine.substack.com/
Subscribe & Follow:
Subscribe to YouTube for more deep dives on decentralization, robots, and the real economy.