No. 94Physical AI
Fangzheng Wang on the Constraints Shaping Hybrid Robotics
Fangzheng Wang · CEO, HopTo
Physical AI interviews
Humanoids, dexterous hands, autonomous driving, and the data layer underneath them.
13 interviews in this sector
13 people Physical AI interviews funding →
13 people Physical AI interviews funding →
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No. 91Physical AI
Christian Duriez on the Constraints Shaping Soft Robotics
Controlling a deformable robot starts with acknowledging that complete control is impossible.
Christian Duriez · CEO, Compliance Robotics
No. 90Physical AI
Julius Kümmerle on Why Autonomous Driving Still Needs Boundaries
Models interpolate very well within the boundaries of their training distribution. Extrapolating beyond those boundaries remains an unsolved challenge whether in autonomous driving, vision-language models, or large language models.
Julius Kümmerle · CEO and Co-founder, SafeAD
No. 89Physical AI
Fabio Bonomo on Why Robotic Hands Break at Durability
The real difficulty lies in integrating these two worlds: ensuring natural compliance capable of interacting safely and intuitively with objects and people, without compromising mechanical stability, precision, and system lifespan.
Fabio Bonomo · CEO, qbrobotics
No. 88Physical AI
Marco Prata on Why Robotic Hands Break at Reliability
A robust system is not one that never fails, but one that continues operating, or can be restored quickly, when something eventually does.
Marco Prata · Co-founder, Seed Robotics
No. 87Physical AI
Rich Walker on the Trade-Offs Shaping Robot Dexterity
Our perspective is that if you need to do something that requires the full human ergonomics, then you’ll need an anthropomorphic hand, but if you need dexterity then you can use other morphologies.
Rich Walker · Director, Shadow Robot
No. 86Physical AI
Sicheng Yang on Why Embodied AI Breaks at the Hand
We believe compliance is essential for the long-term stable operation of dexterous hands in industrial environments, as collisions and impacts with the physical world are almost inevitable.
Sicheng Yang · Founder, Dexcelbot
No. 85Physical AI
Tobias Antonsson on the Constraints Shaping Micro-Robotics
The primary constraint is energy density and the associated expense.
Tobias Antonsson · CEO, Bitcraze AB
No. 82Physical AI
Andrew Fleury on Why Automotive ADAS Breaks on Two Wheels
Automotive ADAS did not fail to translate to micromobility because the need wasn’t there, but because the assumptions baked into car safety systems simply do not work on two wheels.
Andrew Fleury · CEO, Luna Systems
No. 78Physical AI
Daniele Pucci on Physical AI and the Limits of Vision-First Humanoids
You cannot deploy top-down intelligence into a passive body and expect safe, adaptive behavior in unstructured, contact-rich environments. The body has to be intelligent from the start.
Daniele Pucci · CEO, Generative Bionics
No. 72Physical AI
Sha Feng on Designing Wearable Robotics for Human Limits
My ethical boundary is clear: any interface must be consensual, reversible, and must enhance—not diminish—human agency.
Sha Feng · Chief Explorer, Ascentiz
No. 67Physical AI
Stephen James on Why Robotics Breaks at the Data Layer
The companies that win robotics won't be the ones with the best model architecture. They'll be the ones that solved data infrastructure first.
Stephen James · Founder, Neuracore
No. 44Physical AI
Max Amunategui on Transforming Automotive Services with Lumivar’s AI OS
Businesses are literally drowning in phone calls and messages asking technical stuff like parts compatibility, vehicle data and servicing needs.
Max Amunategui · Co-founder, Lumivar
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