@YifeiRobotics
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PhD @ UPenn GRASP , human robot collaboration , neurosymbolic planning
Philadelphia, PA
Joined July 2023
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Yifei Simon Shao retweeted
We have previously demonstrated commercial-grade mastery on individual *tasks*, but with Dyna-2.1, our robots are becoming agentic whole employees that complete workflows wherever they are deployed. Customers pay for complete roles, not isolated tasks.
Yifei Simon Shao retweeted
We are releasing Dyna-2.1, the first Physical Agent that achieves reliable super long-horizon whole-body autonomy. It combines our brand-new semi-humanoid hardware with an agentic system built around Dyna-2 to handle ultra-long real-world workflows.
Here is an uncut footage of Dyna-2.1 completing an entire hour-long laundry room workflow, just like a human does.
Yifei Simon Shao retweeted
Introducing 𝐒𝐩𝐞𝐜𝐮𝐥𝐚𝐭𝐢𝐯𝐞 𝐃𝐞𝐜𝐨𝐝𝐢𝐧𝐠: 𝐇𝐨𝐰 𝐈𝐭 𝐄𝐯𝐨𝐥𝐯𝐞𝐝, 𝐖𝐡𝐞𝐧 𝐈𝐭 𝐒𝐭𝐚𝐲𝐬 𝐋𝐨𝐬𝐬𝐥𝐞𝐬𝐬, 𝐚𝐧𝐝 𝐖𝐡𝐚𝐭'𝐬 𝐍𝐞𝐱𝐭. An interactive tutorial @Madisonkanna and I built for the NeurIPS Education Track.
Every LLM you use generates one token at a time. Autoregressive decoding is the bottleneck for inference. Speculative decoding accelerates this, and today it runs under nearly every hosted LLM. It is a cornerstone topic to learn in the LLM stack.
Blog: neurips2026-speculative-deco…
Yifei Simon Shao retweeted
🚨 Call for live demo / paper at CoRL 2026 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽! No paper required for demo track. Due Sep 27.
🔮 The real magical power of agent is live interactive demo with the audience, which is why we provide all-out support:
- Robot, compute, and API are ready for you in the conference room
- Custom robot / sim demo also welcomed
- Just submit a video proof - friendly to industrial participants
agentic-robotics-workshop.gi…
Paper submission also welcomed!
We also have an amazing speaker lineup from CMU, UC Berkeley, DeepMind, NVIDIA, and Tencent.
Excited to be part of the team!
Today we are introducing Dyna-2, a world-action model pre-trained on one million hours of human video. At this scale, for the first time, we discovered several new scaling laws:
• world-action models exhibit scaling law on human data across four orders of magnitude, from 1000 to 1,000,000 hours,
• this human data scaling law implied a scaling law on never seen robot data,
• both data and objective matter; world modeling and scaling on video data are essential for cross-embodiment scaling transfer to emerge
🧵
Call for community effort 🤖! Bring the Lobster 🦞 on robots! Our work Tidybot Universe 🌟, allows AI agents to autonomously iterate on real robotics hardware.
We built the infrastructure for displaying and sharing the learned skills across agents; and for hosting common services to be access across agents, starting with the Tidybot.
Join us today tidybot-services.github.io
What do "robot skills" look like when humans and AI build them together? We built 3 essential layers:
🧩 Skills: A community-built library. Browse, wish for a skill, or build it with an agent.
🤖 Agent Server: Ensures safety and hardware access. It manages time, executes safely, and rewinds movements if needed.
⚙️ Services: Hardware drivers and shared models that Service Agents add automatically upon request.
Yifei Simon Shao retweeted
Rising Star Speaker @YifeiRobotics spoke about
𝘎𝘦𝘯𝘦𝘳𝘢𝘭𝘪𝘴𝘵 𝘙𝘰𝘣𝘰𝘵𝘴, 𝘓𝘪𝘬𝘦 𝘓𝘓𝘔𝘴, 𝘕𝘦𝘦𝘥 𝘢 𝘓𝘪𝘵𝘵𝘭𝘦 𝘐𝘯𝘧𝘦𝘳𝘦𝘯𝘤𝘦-𝘛𝘪𝘮𝘦 𝘏𝘶𝘮𝘢𝘯 𝘐𝘯𝘱𝘶𝘵. Having human-in-the-loop is important!
Yifei Simon Shao retweeted
Join us on Oct 24th at #IROS2025 RoboGen Workshop! 🤩 We will discuss, Building toward embodied AGI: solving the data bottleneck. We got an exciting line of speakers from academia and industry! Link in thread.
@siyuanhuang95 @ShenlongWang Peter KT Yu
@yuewang314 Ruigang Yang @wu_chenfei @zhijianliu
Yifei Shao @KungPou40786 @IROS2025
