A robot does not need another robot to learn how to work in a home.

That idea is at the center of Sunday Robotics. The company is building Memo, a general-purpose home robot trained with human data collected through its custom Skill Capture Glove.

In this episode of Automated, Brian Heater speaks with Sunday Robotics co-founder and CEO Tony Zhao about physical AI, robot learning, and why he left Stanford without keeping an academic fallback. Tony traces the company's foundation to ALOHA and the Universal Manipulation Interface, two research efforts that changed how he thought about scaling robotic intelligence.

Tony explains why data remains one of robotics' biggest bottlenecks. Sunday's glove closely matches Memo's hand, allowing people to capture high-quality manipulation data while performing ordinary tasks. This approach is cheaper and easier to distribute than collecting every training example through a robot.

Brian and Tony also discuss how smarter AI could compensate for simpler, lower-cost hardware, why Memo could eventually be priced more like a gaming PC or phone, and why a home robot does not need to work at human speed. If the robot can finish the dishes, laundry, and tidying while its owner is away, reliability and capability matter more than speed.

Finally, Tony explains why a polished robot video is not the same as repeatable real-world deployment. He argues that the variability of homes creates what Sunday calls research-market fit, pushing robots toward the broad, adaptable intelligence they would need to work around people and eventually move into services and industrial environments.

Connect with Tony Zhao
https://www.linkedin.com/in/tony-z-zhao

Learn more about Sunday Robotics
https://www.sunday.ai/

Apply for the Memo beta program
https://www.sunday.ai/beta-program

Explore ALOHA
https://tonyzhaozh.github.io/aloha/

Explore the Universal Manipulation Interface
https://umi-gripper.github.io/

Learn more about ACT-2
https://www.sunday.ai/blog/act-2-preview

We’d love to hear from you. Have thoughts or guest suggestions?
Reach us at podcast@automate.org

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