Sai Vemprala @saihv
Co-founder/CTO @GenRobotics_AI building general robot intelligence. Ex-@MSFTResearch | @tamu | @asu saihv.com Bellevue, WA Joined December 2016-
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❓How can humanoids learn to squat and open a drawer? Reward-tuning for every such whole-body task is infeasible. 🚀Meet DreamControl: robots "dream" how people move and manipulate objects in varied scenarios, practice using them in simulation, and then act naturally in the…
Last week, we shared DreamControl — a scalable framework for whole-body humanoid control that fuses diffusion priors with reinforcement learning to enable real-world scene interaction. Diffusion + RL → natural whole-body skills Policies run in real time → bridges sim-to-real…
@genrobotics_ai is bringing natural whole-body skills on real robots!!!
@genrobotics_ai is bringing natural whole-body skills on real robots!!!
The power of generative models — now embodied in humanoids. Announcing DreamControl –– After a year-long research effort at General Robotics — we present a scalable framework for whole-body humanoid control that fuses diffusion priors with reinforcement learning to unlock…
95% of GenAI pilots fail — MIT Media Lab Robot AI is even more challenging. The 5% that succeed? They deploy. Experience AI deployed on your robots today! In video: Pick and place for @Universal_Robot forbes.com/sites/andreahi…
95% of GenAI pilots fail — MIT Media Lab Robot AI is even more challenging. The 5% that succeed? They deploy. Experience AI deployed on your robots today! In video: Pick and place for @Universal_Robot forbes.com/sites/andreahi…
Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and @nvidia Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation
One skill. Any arm. Pick and Place. In video: UR5e, WidowX #robotics #AISkills #manipulation
Generalization is the hallmark of intelligence - robots should adapt, not memorize. One skill, multiple robots, multiple objects.
Generalization is the hallmark of intelligence - robots should adapt, not memorize. One skill, multiple robots, multiple objects.
🤖 GRID Feature Release: Heterogeneous multi-agent control is now live on GRID Enterprise. As requested, all AirGen users can now coordinate mixed robot fleets — and adapt AI skills across form factors with ease. #robotics #AI #multiagent
Hello Roboticists, Trossen Robots are now live on Open GRID. With just a few lines of code, any Trossen arm — old or new — can tap into AI skills from the cloud. One example: Teleoperation via API → data collection on Isaac Sim → playback on real hardware 👇🏻 Making Trossen…
AI skills for every Trossen robot, anywhere—through GRID. Excited for what this collaboration unlocks: making robots useful, fast—for all Trossen and GRID users. More this week 👀
AI skills for every Trossen robot, anywhere—through GRID. Excited for what this collaboration unlocks: making robots useful, fast—for all Trossen and GRID users. More this week 👀
Humans fundamentally combine skills to solve complex tasks. Robots should too. 💻 grid.generalrobotics.dev 🔗 generalrobotics.company/post/general-p…
Big news today - we’re now General Robotics! This reinforces our mission towards truly general robot intelligence, and more importantly, our belief that general intelligence emerges from modular compositions of many skills. GRID is the home for AI skills and sims across robots.
Big news today - we’re now General Robotics! This reinforces our mission towards truly general robot intelligence, and more importantly, our belief that general intelligence emerges from modular compositions of many skills. GRID is the home for AI skills and sims across robots.
Hello Robots, Roboticists, Engineers, We believe general-purpose robot intelligence will emerge from AI skills—composable capabilities that sense, reason, and act. These are not tasks. They are not demos. They are capabilities—learned, reusable, and ever-adapting across form…
Scaled Foundations is now General Robotics. We’re building general-purpose intelligence for every robot. Across any scenario in the physical world. Blog: generalrobotics.company/post/general-p…
Thrilled to share our work on accelerating neurosymbolic methods for robotics! STLCG++ encodes logical constraints in a computational graph, achieving 100-1000× faster quantitative evaluation—enabling real-time symbolic reasoning for traj opt, policy learning, & more. 🧵 [1/n]
Scaling Signal Temporal Logic (STL) for real-time robotics and AI! Blog: sca.fo/stlcg-plus-plus STLCG based methods are largely restricted to small-scale, offline applications due to it’s computational costs. Introducing STLCG++, a new approach inspired by causal masking used…
Looking at the robotics talent landscape: Our analysis shows approximately one engineer capable of working on robotic systems for every 20 ML specialists. This poses interesting challenges for scaling physical AI applications.
Data is the fuel for building any AI system. Let’s break down how you can generate data for Robot AI training seamlessly. Here is my GRID notebook that you can use to follow along: grid.scaledfoundations.ai/shared/14a128b…
Drone giant DJI didn't appear overnight. Their decade-long dominance stems from CEO Frank Wang. Wang's research and his eventual 2011 thesis defined the blueprint that revolutionized quadcopters forever. Let's revisit this thesis here: ⬇️
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