Posts with #FigureAI

#FigureAI

Public posts on X that use #FigureAI.

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  1. Moonlight✓@VVMotyka
    Figure 04 is the iPhone 1 moment for humanoid robots. Brett Adcock just confirmed design lock. Parts are already heading to assembly. He calls it the biggest generational leap in Figure’s history. #Figure04 #FigureAI #HumanoidRobots Clip from the All Hands ↓
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    Brett Adcock @adcock_brett
    Figure held an all-hands this week, and I've decided to share it here publicly Given our rate of progress, our roadmap has completely changed over the last year, and the team has doubled It's important to get everyone aligned on our mission going forward
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  2. Brett Adcock✓@adcock_brett
    Figure held an all-hands this week, and I've decided to share it here publicly Given our rate of progress, our roadmap has completely changed over the last year, and the team has doubled It's important to get everyone aligned on our mission going forward
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    1211311.9K219K
  3. Yi-Yi✓@yiyibuilds
    I open-sourced Teachable Figures, a skill for AI agents to create beautiful, interactive 2D and 3D lessons. Try it here: It started with something I wanted for my own learning. I was studying AI model architectures and AI infrastructure. While reading about systems like SGLang, I kept wanting to see what was happening. Where does the data go? How do the components work together? What changes when I adjust one part of the system? My first version was a skill to help me understand SGLang through visual, interactive explanations. Then I discovered Anatomy and iso-figure. Their work on mechanical structures, cutaways, exploded views, and functional isometric objects gave me ideas for how much further this could go. I combined their rendering approaches with my teaching workflow. That became Teachable Figures. One question kept coming up as I built it: What kind of representation would help someone understand this particular idea? - For a Transformer, I want to follow the data through the computation and see how a causal mask changes attention weights. - For anatomy, I want to rotate a structure, look inside it, and understand where things sit relative to one another. - For a mechanical assembly, I want to separate the components and inspect their connections. - For historical clothing, I want to understand the overlapping panels, construction, and folds. Each asks for a different way of showing things. I also ran into this during iteration. A rotating model still needs a recognizable shape. A garment needs folds that communicate its construction. Choosing the right renderer and source material became part of the teaching workflow. Learning science helped me think through those choices. - Dual coding encouraged me to connect verbal and visual explanations. - Spatial and temporal contiguity shaped where explanations appear and how they stay synchronized with changes. - Cognitive load shaped what to reveal first and what to leave for later. The interaction follows a simple learning sequence: Predict → try → observe → explain → apply it to a new situation. Does adding another gear always make the output slower? If a cone’s cross-sectional radius doubles, what happens to its area? Does a rocket lift off whenever its engine produces thrust? I want learners to make a prediction, change something, and have a result they can reason about. The current demos explore Transformer attention, chest anatomy, rocket structure and flight, cone cross-sections, a Ming-dynasty robe, and gear ratios. They support Chinese and English and can run offline. My hope is to make this a tool I can reach for whenever I encounter something I want to understand, and let an AI agent help me build a small, beautiful lesson around it. The video shows a few examples. Try the demos: Code and installation: Thanks to the creators of Anatomy and iso-figure for the work this builds on. If you try it, I’d love to hear what you’re learning and where the explanation falls short. Stars and contributions are welcome!
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  4. WIC en español@WIC_espanol
    【📦🤖¡Figure AI transmite #envivo 5 días ininterrumpidos de clasificación de paquetes!】Recientemente, la empresa estadounidense de robots humanoides #FigureAI transmitió en vivo sin edición el proceso completo de la tarea de turno estilo fábrica del #robot humanoide Figure 03. Durante la transmisión, el robot ejecutó tareas típicas de clasificación de paquetes en almacén: escanear códigos de barras, recoger paquetes de diferentes materiales como bolsas de plástico flexibles y cajas de cartón rígidas, voltear las etiquetas hacia abajo y colocarlas con precisión en la cinta transportadora. El robot también puede realizar de forma autónoma la detección y reemplazo de baterías, autodiagnóstico, y ajustar sus movimientos en tiempo real en entornos dinámicos. Hasta la tarde del 18 de mayo, Figure AI ya había transmitido durante 5 días, incluyendo una competencia en vivo entre un miembro del personal y el robot. #Robótica #IA #Automatización #Tech
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  5. Interesting Engineering✓@IntEngineering
    The household robot that can clean your room isn't a concept anymore. Figure just showed two humanoids resetting a bedroom in under two minutes, coordinating through movement alone. #HumanoidRobot #FigureAI
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  6. Manav✓@Manavpod
    Figure AI just launched a new side hustle. They are paying everyday people to film their household chores. This massive video dataset will train their humanoid robots. #FigureAI #SideHustle #TechNews
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  7. Vishal@vishalxrana
    🚨 Introducing Figure 02: the latest humanoid #robot by #FigureAI, backed by #OpenAI! This sleek new model brings major upgrades and is ready to redefine autonomous #robotics. 🤖
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  8. Automaxa | AI Automation@swapngoel
    Boston Dynamics Atlas vs Figure 03 🤖 🔵 Atlas: Industrial robotics and dynamic movement. ⚪ Figure 03: AI-driven perception and general-purpose tasks. Two approaches. One big question: Who will shape the future of humanoid robots? #Robotics #AI #FigureAI
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  9. Tendril@studiotendril
    No sci-fi gimmicks, just crisp design and motion working in total harmony. Every frame is true to the real product, and to the people behind it. Read the case study here: #tendril #figureai #motiondesign
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  10. सव्यसाची 🏹@rishabhp4982
    अमेरिका की मशहूर ह्यूमनॉइड रोबोट बनाने वाली कंपनी 'फिगर एआई' ने हॉलीवुड स्टार आर्नोल्ड की सलाह पर दर्जनों रोबोट्स को उबलते लावा में कूदने की ट्रेनिंग दी और करोड़ों की रोबोट फ्लीट को 20 मिनट में जलकर राख हो गए. #HumanoidRobots #FigureAI
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