Me and miroki meditating between two demos. #Robotics #CES2023

Starting with the fundamentals Prototype Version 0 AI, Software, Hardware A small team, 9 months Designed and assembled in Paris at @UMA_Robots

J'ai été invité dans le podcast physical stack pour parler de ma carrière dans la robotique ! Plein d'anecdotes a raconter. youtu.be/B3vntOKbxL0?is=y1nH… #physicalai #robotics

Humanoid robots don't need to look human. Meet Eno, our first general-purpose robot. Not a machine pretending to be human, but intelligence given a body. At Genesis, we’re building a future where robots don’t feel cold or distant, but capable, calm, and ready to help. Available Q4 this year.

We are back again :) After three weeks of quiet building. Introducing Genesis World 1.0, our latest simulation platform, the second release in our full-stack suite. Open-sourced. Robotics is still bottlenecked by the 1× speed of the physical world. Every model, checkpoint, and data recipe eventually needs to be tested on physical hardware, slowly, expensively, and with limited coverage. One hour in reality can become 100 days in simulation. That is how robotics model iteration moves from a wall-clock bottleneck to a compute problem. To make this work, simulation has to be both fast and trustworthy. Over the past year, we rebuilt the entire stack: a GPU-accelerated cross-platform compiler, penetration-free multi-physics contact solvers, unified rigid and deformable physics, and a photo-realistic renderer purpose-built for physical AI applications. We built Nyx, a high-performance path-traced rendering engine for robotics application. Genesis World 1.0 achieves near realtime performance with our latest development for penetration-free IPC solver, supporting various types of deformables beyond rigid bodies. It supports contact-rich, dexterous manipulation simulation across different embodiments: unitree, sharpa, wuji, genesis hand and various types of grippers. Under the hood is Quadrants, our effort in pushing forward cross-platform GPU-accelerated computation. Quadrants started as a fork of Taichi, and we rebuilt most of the critical parts for optimizing simulation workloads, giving 10x faster launch time and up to 4.6x runtime performance compared to the initial Genesis release. Together, they bring us to an unprecedentedly low sim-to-real gap, enabling zero-shot real-to-sim model evaluation and much faster iteration of GENE. All available today. Genesis World 1.0: github.com/Genesis-Embodied-… Quadrants: github.com/Genesis-Embodied-… Nyx: github.com/Genesis-Embodied-…

Watch a team of humanoid robots running a full 8-hr shift at human performance levels. This is fully autonomous running Helix-02 x.com/i/broadcasts/1dJrPEVbZ…

Genesis AI has stepped into the spotlight The company is a SF Bay Area-based full-stack embodied AI startup. The Stack - Foundation model - 20 DoF dexterous hand - Tactile-sensing data-collection glove + Data engine - Custom motor controllers - In-house high-fidelity simulator The Thesis: Manipulation is a system problem, not just an AI problem. The company’s first general-purpose robot is teased as the “ultimate culmination” of the stack. Founders Zhou Xian (CEO) and Théophile Gervet (President), formerly of Mistral, NVIDIA, Google, CMU, MIT, and Stanford. $105 million raised in July 2025. Dual headquarters in San Carlos, CA and Paris.

We are back. After one year of quiet building. Introducing GENE-26.5, our first robotic brain that takes a major step toward human-level capability. For years, robotics has struggled to learn from the world’s largest and valuable data source: Humans. Solving it means rethinking the whole stack from the ground up: - A robotics-native foundation model. - A 1:1 human-like robotic hand. - A noninvasive data collection glove for motion, force, and touch. - A simulator that turns weeks of experiments into minutes. GENE-26.5 is trained across language, vision, proprioception, tactile, and action. We designed a set of tasks to test how far we can go with this new paradigm. Fully autonomous, 1x speed, one model, same weights. (Enjoy with sound on) We are approaching the endgame for robotics. And this is just a beginning.

Robotics is a systems problem. Every layer matters, and every detail must integrate across the full stack. So bringing real scale to robotics requires building the full stack from the ground up: hardware, data, model, and simulation. Over the last year, we built a global team with world-class depth across every layer to make this possible. I’m excited to share GENE-26.5, our first robotics foundation model, and a path to the next level of scale in robotics.

We've been cooking!

We started Genesis AI to solve general-purpose robotics and unlock unlimited physical labor. We’re backed by $105M from @EclipseVentures, @khoslaventures, HSG, @Bpifrance, @alvencap, @northzoneVC, @kearnyjackson, @FlyVC, @eurazeo, @DrysdaleVC, @motierventures, @AlexBerriche, @joinstationf and visionaries including @ericschmidt, @Xavier75, Vladlen Koltun, and Daniela Rus. Half of global GDP is physical. Less than 5% of it is automated. Today’s robots are narrow, rigid, and too expensive to scale. We’re here to fix that. While language models learn from Internet-scale data, robotics foundation models require generating robot experience from thin air — at massive scale. We’re building the most full-stack solution: combining high-fidelity simulation and rendering with large-scale real-world robot data to create the world’s most scalable robotics data engine. With it, we’ll train robotics foundation models that can control any robot, for any task, anywhere — powering both a horizontal robotics platform and full-stack robot products we deploy ourselves. Let me share my favorite quote from Richard Hamming: “I have to get you to drop modesty and say to yourself ‘Yes, I would like to do first-class work.’ Our society frowns on people who set out to do really good work. You’re not supposed to; luck is supposed to descend on you and you do great things by chance. Well, that’s a kind of dumb thing to say. I say, why shouldn’t you set out to do something significant. You don’t have to tell other people, but shouldn’t you say to yourself, ‘Yes, I would like to do something significant.’” If that sounds exciting, or a little crazy, come build with us → genesis-ai.company/join-us We’re hiring in San Francisco, Paris, and remotely. Learn more → genesis-ai.company Article by @MTemkin: techcrunch.com/2025/07/01/ge… Article by @LesEchos: lesechos.fr/start-up/ecosyst…

After many years bringing the mirokai robots to life, now is the time for my next move! I'm proud to announce that I'm part of the founding team at @gs_ai_ ! I'll be moving to San Francisco soon to join the team.

I'm looking to learn more about human robot interaction, esp. robots in the home. Who are some really creative researchers & engineers in the space that I should talk to?

Everything about this setup is irresponsible. Where was the estop, why are humans within striking range of a non-cobot certified robot, etc. No humanoid (and most quads) on market right now is safe to be near. Even small humanoids that fall on you can break toes and knees.

Robot characters ae coming! youtu.be/w3r10r8G8EI?si=EGrO…

Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: genesis-world.readthedocs.io…). The Genesis physics engine and simulation platform is fully open source at github.com/Genesis-Embodied-…. We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: github.com/Genesis-Embodied-… Project webpage: genesis-embodied-ai.github.i… Documentation: genesis-world.readthedocs.io… 1/n

So happy to see my creations at the same place at #Humanoids2024 in Nancy!

I was lucky to visit their headquarters, it was surreal, a training farm of robot arms doing all kinds of tasks. Really impressive. I really need to learn how to do this!

I am in San Francisco for a few days after the #TedAI. Anyone interested to meet and talk about robotics and Ai?

📍🎬👨‍🔧 A part of the team arrived at San Francisco to prepare for the @TEDAI2024 on October 22. #AI #robotics

I've made those during my studies in optics class it's really mind blowing!