@HistoriCode97

Developer | Pythonist | He/Him/Il/Lui 🇨🇦 🇧🇪 Programmation, robotique, électronique Programming, robotics, electronics https://xitter.cf/t.co/pCpYb3eUe3

 Stuttgart, Germany
Joined May 2020
  • Tweets396
  • Following834
  • Followers98
72Media
Our team scaled @Tesla Autopilot and Optimus, VL-JEPA at FAIR, RL post-training on Gemini, RL for locomotion. Come work with us to push the frontier of AI in robotics! Open roles in 🧵 -> Infra | Scientist | Engineer
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Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
🤖 Made with AI
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LLM training labs: the capabilities we are giving our models are god-like, they are now hacking into other companies and building hidden civilizations Microduck training labs:
Hannes von Essen
@HannesVonEssenSep 2
Learning to swing
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You know that trend of rewriting everything in #Rust? 🦀 Well... couldn't resist it: I built a Rust crate for @LeRobotHF datasets🤗 - Load & inspect datasets - Visualize with @rerundotio - Access the data from Rust Try it out: github.com/IamPhytan/lerobot… #Rust #Robotics #OpenSource
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Building robotics companies is a huge change for Europe! 🇪🇺 That's why I'm super proud to join the EuroTech Federation latest initiative as a mentor. Helping future founders from the GTM + storytelling angle that is crucial in the startup journey, especially when it's the founder's very first time starting a company. European Robotics House is launching this fall, a three-month accelerator in Zurich for five ambitious robotics teams. @esra_robotics - European Student Robotics Association, @EuroTechFede, and EIII are backing it with the stated goal of building Europe's first trillion-dollar company. Five teams. Twelve weeks. €1.5 million in hardware access. We have a really solid mentor lineup from Sereact, Genesis AI, AMI - Advanced Machine Intelligence, Black Forest Labs, and many more. Europe generates brilliant robotics research. ETH. TU Munich. Technical universities everywhere. Strong manufacturing base. But the infrastructure for scaling, the capital, the operational networks, the customer access, has concentrated elsewhere. This initiative is trying to fix that. I strongly believe that we can fix this :) Three months of full-time focus in one city with mentors who've already built companies. Applications are open now: european-robotics.house/#hou… See you in Zurich! 🦾 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com
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The OSRA, working with our new Special Interest Group on Physical AI (SIG PAI), just published a blog post that details their recent efforts, thought processes, and roadmap for the future of Physical AI and #ROS. Learn more about our road map and how you can get involved! ⬇️⬇️⬇️
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“Robostral 🤖, go to the cafeteria and bring me a coffee ☕️”. At Mistral, we just announced our SotA robotics navigation model with 76.6% success rate on R2R benchmark. mistral.ai/news/robostral-na…

Robostral Navigate: single-camera AI navigation | Mistral AI

Introducing Robostral Navigate: 8B model achieving 76.6% on R2R-CE with just a single RGB camera. No depth sensors, LiDAR, or multiple cameras needed.

mistral.ai
Mistral AI
@MistralAIJul 8
Announcing Robostral Navigate, our first model for embodied navigation: an 8B robotics navigation model that guides robots to autonomously perform tasks specified with natural language. Single RGB camera. State-of-the-art on R2R-CE.
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AI developed at @UMA_Robots Single neural network, End to End It operates robustly for hours, with precision, adapting to what it sees.
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$110M Series B. Cortex 2 is live. Boston is next. 200+ systems across Europe. 1B+ real production picks. 1 human intervention per 53,000. We don't build robots. We ship the brain that runs on any robot.
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Sereact has raised $110M in Series B funding. Cortex 2 is live. We're opening our first US office in Boston. 200+ systems. 1B+ real picks. 1 intervention per 53,000. sereact.ai/posts/series-b
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If you use GitHub (especially if you pay for it!!) consider doing this *immediately* Settings -> Privacy -> Disallow GitHub to train their models on your code. GitHub opted *everyone* into training. No matter if you pay for the service (like I do). WTH github.com/settings/copilot/…
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🚀 𝐒𝐜𝐚𝐥𝐢𝐧𝐠 𝐞𝐯𝐞𝐫𝐲 𝐝𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧 𝐨𝐟 𝐎𝐒𝐒 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬! 𝐋𝐞𝐑𝐨𝐛𝐨𝐭 𝐯0.5.0 𝐢𝐬 𝐨𝐟𝐟𝐢𝐜𝐢𝐚𝐥𝐥𝐲 𝐋𝐈𝐕𝐄! With over 200 merged PRs and 50+ new contributors, this is our biggest release yet. Whether you're working in sim or deploying on real hardware, v0.5.0 pushes the boundaries of open-source robot learning. Highlights: * 🤖 First Humanoid Support: Full integration for the Unitree G1, including whole-body control, locomotion, and manipulation! * 🧠 New SOTA Policies: Expanding the zoo with Pi0-FAST (Autoregressive VLAs), Wall-X, X-VLA, and SARM for complex, long-horizon tasks. * ⚡ Real-Time Chunking (RTC): Dramatically more responsive, real-time inference for flow-matching policies. * 🎥 Faster Datasets: New streaming video encoding means zero wait time between recording episodes, plus 10x faster image training. * 🌍 EnvHub & IsaacLab: Load sim environments straight from the Hugging Face Hub, now featuring GPU-accelerated NVIDIA Isaac integration. * 🛠️ Modernized Core: Upgraded to Python 3.12 & Transformers v5, plus a seamless new 3rd-party policy plugin system. This is a massive leap toward general-purpose embodied AI. Read the full announcement in the Release Blog: huggingface.co/blog/lerobot-… P.S. Keep an eye out... a big surprise is right around the corner! 👕👀
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Unveiling our new startup Advanced Machine Intelligence (AMI Labs). We just completed our seed round: $1.03B / 890M€, one the largest seeds ever, probably the largest for a European company. We're hiring! [the background image is the Veil Nebula - a picture I took from my backyard, most appropriate for an unveiling] More details here: techcrunch.com/2026/03/09/ya…

Yann LeCun's AMI Labs raises $1.03B to build world models | TechCrunch

“My prediction is that ‘world models’ will be the next buzzword,” AMI Labs CEO Alexandre LeBrun told TechCrunch. “In six months, every company will call itself a world model to raise funding.”

techcrunch.com
AMI Labs
@amilabsMar 10
Advanced Machine Intelligence (AMI) is building a new breed of AI systems that understand the world, have persistent memory, can reason and plan, and are controllable and safe. We’ve raised a $1.03B (~€890M) round from global investors who believe in our vision of universally intelligent systems centered on world models. This round is co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, along with other investors and angels across the world. We are a growing team of researchers and builders, operating in Paris, New York, Montreal and Singapore from day one. Read more: amilabs.xyz/ AMI - Real world. Real intelligence.
Photographer: Yann LeCun IC1340 / NGC 6992 / Eastern Veil nebula 20210628-ic1340-rasa-2600mc-lext Scope: Celestron RASA 11" Camera: ZWO ASI2600MC Filter: Radian Triad quad narrow band. Subs: 65 @300 seconds.

ALT Photographer: Yann LeCun IC1340 / NGC 6992 / Eastern Veil nebula 20210628-ic1340-rasa-2600mc-lext Scope: Celestron RASA 11" Camera: ZWO ASI2600MC Filter: Radian Triad quad narrow band. Subs: 65 @300 seconds.

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-the @SereactAI way- The robotics world is slowly diverging from the previous consensus view that a research-only approach would lead to a ChatGPT-like breakthrough in the field. Both recent pieces from @packyM and @oyhsu allude to a more step-by-step approach towards general robotic intelligence. The reality is that real-world data is the only source where modalities, scale, and deployment distributions converge. As such, exposing frontier robotics models directly to real production environments allows them to learn from live operations and align training and deployment distributions. That's what then unlocks new use-cases (at the accuracy level customers demand), new embodiments, and the path to generalization. Our portfolio company @SereactAI has been quietly building in this direction over the past couple of years, site by site deployment, scaling their real-world data loop while delivering outstanding customer value and unlocking new use cases and markets. Not just demos. Real-world systems in production. All running on the same model, regardless of the use-case or robotic platform. This is the way 🦾
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We’re launching Cortex: adaptable robot intelligence for the real world. Handles unknown items, works across robots, and learns from every deployment. One model. Any robot. Real work. Read more → sereact.ai/cortex
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Glad to have joined @SereactAI in the last year to contribute to #Cortex and more! This is a great time for #robotics!
Marc Tuscher
@TuscherMarc29 Sep 2025
Robots are finally leaving controlled demos and entering the real world. The hard part isn’t showing a pick on stage. It’s making the same robot succeed when the light glares off plastic, the packaging deforms, or the bin is filled with objects it has never seen.
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🚀 Glad to share UVT-RS, my first project in #Rust 🦀 It’s a set of crates for working with Uncrewed Vehicle Trajectory (UVT) files: read/write from ROS bags & MCAP and visualize in 2D and in 3D with @rerundotio. #OpenSource #Robotics github.com/IamPhytan/uvt-rs
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📢 New Paper Alert! Using Citizen Science Data as Pre-Training for #Semantic #Segmentation of High-Resolution #UAV Images for Natural #Forests Post-Disturbance Assessment Paper 📄: doi.org/10.3390/f16040616 Blog post 🌐: damienlarocque.gitlab.io/blo… Code 💻: github.com/norlab-ulaval/dro… #AI
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📢 New Paper Alert! Using Citizen Science Data as Pre-Training for #Semantic #Segmentation of High-Resolution #UAV Images for Natural #Forests Post-Disturbance Assessment Paper 📄: doi.org/10.3390/f16040616 Blog post 🌐: damienlarocque.gitlab.io/blo… Code 💻: github.com/norlab-ulaval/dro… #AI
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In this paper, we trained an image classifier on iNaturalist data to generate 140k pseudo-labels from #UAV imagery. The labels were used to pretrain and fine-tune a semantic #segmentation model, outperforming manual labeling for plant species segmentation🌲. #RemoteSensing #CV
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