No Priors Ep. 141 | With Sunday Robotics Co-Founders Tony Zhao and Cheng Chi

The robotics industry is on the cusp of its own “GPT” moment, catalyzed by transformative research advances. Enter Memo, the first general-intelligence personal robot, focused on taking on your chores to give back your time. Sarah Guo sits down with Tony Zhao and Cheng Chi, co-founders of Sunday Robotics, to discuss the state of AI robotics. Tony and Cheng speak to the challenges they faced while developing their technology, the innovative glove system employed to scale real-world data collection, and the impact of diffusion policy and imitation learning. Plus, they talk about their 2026 in-home beta program and why personal robots are only a handful of years away from mass deployment. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tonyzzhao | @chichengcc | @sundayrobotics Chapters: 00:00 – Tony Zhao and Cheng Chi Introduction 00:56 – State of AI Robotics 02:11 – Deploying a Robot Pre-AI 03:13 – Impact of Diffusion Policy 04:29 – Role of ACT and ALOHA 07:02 – Imitation Learning - Enter UMI 10:38 – Introducing Sunday 11:57 – Sunday’s Robot Design Philosophy 15:05 – Sunday’s Shipping Timeline 19:02 – Scale of Sunday’s Training Data 23:58 – Importance of Data Quality at Scale 24:56 – Technical Challenges 27:59 – When Will People Have Home Robots? 30:48 – Failures of Past Demos 32:34 – Sunday’s Demos 36:53 – What Sunday’s Hiring For 39:10 – Conclusion

Tony ZhaoguestSarah GuohostCheng Chiguest

Nov 19, 202539mWatch on YouTube ↗

EPISODE INFO

Released: November 19, 2025
Duration: 39m
Channel: No Priors
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

The robotics industry is on the cusp of its own “GPT” moment, catalyzed by transformative research advances. Enter Memo, the first general-intelligence personal robot, focused on taking on your chores to give back your time. Sarah Guo sits down with Tony Zhao and Cheng Chi, co-founders of Sunday Robotics, to discuss the state of AI robotics. Tony and Cheng speak to the challenges they faced while developing their technology, the innovative glove system employed to scale real-world data collection, and the impact of diffusion policy and imitation learning. Plus, they talk about their 2026 in-home beta program and why personal robots are only a handful of years away from mass deployment. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tonyzzhao | @chichengcc | @sundayrobotics Chapters: 00:00 – Tony Zhao and Cheng Chi Introduction 00:56 – State of AI Robotics 02:11 – Deploying a Robot Pre-AI 03:13 – Impact of Diffusion Policy 04:29 – Role of ACT and ALOHA 07:02 – Imitation Learning - Enter UMI 10:38 – Introducing Sunday 11:57 – Sunday’s Robot Design Philosophy 15:05 – Sunday’s Shipping Timeline 19:02 – Scale of Sunday’s Training Data 23:58 – Importance of Data Quality at Scale 24:56 – Technical Challenges 27:59 – When Will People Have Home Robots? 30:48 – Failures of Past Demos 32:34 – Sunday’s Demos 36:53 – What Sunday’s Hiring For 39:10 – Conclusion

SPEAKERS

Tony Zhao
guest
Sarah Guo
host
Cheng Chi
guest

EPISODE SUMMARY

In this episode of No Priors, featuring Tony Zhao and Sarah Guo, No Priors Ep. 141 | With Sunday Robotics Co-Founders Tony Zhao and Cheng Chi explores sunday Robotics Builds Cheap, Safe Home Robots With Massive Real-World Data Sunday Robotics co-founders Tony Zhao and Cheng Chi describe how recent advances in imitation learning, diffusion policies, and low-cost hardware are finally enabling general-purpose home robots. They explain the shift from brittle, hand-engineered classical robotics to scalable, data-driven systems powered by millions of real-world trajectories collected via custom gloves and tools like Umi. The founders emphasize full-stack integration—hardware, data collection, training pipelines, and product design—to achieve dexterity, generalization, and safety at consumer price points. They outline a 2026 home beta program, discuss realistic timelines and costs, and explain how to critically interpret robotics demos in an industry full of hype.

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