
Sphoenix
87 posts

Sphoenix
@SphoenixAI
Robotics. AI Health & Safety. Editor-in-chief @BotNewsAI





World Cup fever continues! Viking Row at Boston Dynamics HQ!





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



Asimov 1 is an open-source humanoid robot you can build and customize yourself. Two ways to get one: 1) Source the parts yourself: docs.menlo.ai/asimov/1/bom 2) Get the DIY kit: asimov.inc/diy-kit The kit bundles every part as a group buy, cheaper than sourcing one by one, and you build alongside others.


"A parcel with snacks has been delivered for Flexion. Retrieve it using the stairs and come up using the elevator. Then unpack it and place the items into the empty drawer on the shelf in the snack area." One instruction. No human operator. Everything that follows is autonomous. Today we're introducing Reflect v1.0, our robotics intelligence platform for long-horizon work. From a single natural-language command, the robot understands the task, navigates a multi-floor building, calls elevators, handles doors, uses tools to unpack a box, and puts the items away. The biggest shift in v1.0 is that we use reinforcement learning across every layer, from low-level control to high-level reasoning. Long-horizon autonomy is unforgiving. The robot must recover on its own when things don't go to plan because in the real world, they never do. Combining reasoning, perception, physical execution and runtime robustness into a single mission-capable system is the foundation required to solve humanoid autonomy. Our team is just getting started. #HumanoidRobots #Flexion










We are releasing Falcon Perception, an open-vocabulary referring expression segmentation model. Along with it, a 0.3B OCR model that is on par with 3-10x larger competitors. Current systems solve this with complex pipelines (separate encoders, late fusion, matching algorithms). We developed a novel simpler "bitter" approach: one early-fusion Transformer (image + text from first layer) with a shared parameter space, and let scale + training signal do the work. Please check our work ! 📄 Paper: arxiv.org/pdf/2603.27365 💻 Code: github.com/tiiuae/falcon-… 🎮 Playground: vision.falcon.aidrc.tii.ae 🤗 Blogpost: huggingface.co/blog/tiiuae/fa…








