🎉 We just released code, data and model for... our #SIGGRAPH2023 work "CT2Hair"!! CT2Hair achieves fully automatic reconstruction of production-ready hair strands from computed tomography (CT) scans!! Code&Data: Project:show more

📢GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans📢... We present a novel method to reconstruct hair strands from colorless 3D scans by extracting orientation cues directly from the mesh surface geometry by finding local characteristic lines and from shaded renderings using a neural 2D line detector. We enhance the reconstruction with a diffusion prior trained on synthetic hair data and adapted to each scan using a tailored text prompt, allowing us to recover both simple and complex hairstyles without relying on color input. To support further research, we also introduce Strands400, the largest publicly available dataset of 3D hair strand reconstructions from real-world scans of 400 different people, featuring complicated hairstyles, such as ponytails and buns. 🌍 📷 Great work by Rachmadio Noval L. Artem Sevastopolsky Egor Zakharov @ness_prisshow more

Coarse2Real (C2R) transfers simple 3D renderings into realistic style... video. Check our paper and project page to learn how to hedge small amount of synthetic paired data with real non-pair data for training the C2R model. We will release the model soon!show more

We just released Amp Tab, our new completion engine.... It's based on a custom model and can complete not just single lines, but entire code blocks. Right next to your cursor or a Tab away.show more

We wanted better charts from our agents So we... built a skill for generating NYT-style data viz Includes guiding principles + real code snippets. Based on Hyperagent's study of actual examples + public teachings of Mike Bostock. Example + skill below 👇show more

Many of you asked for code & weights for... π₀, we are happy to announce that we are releasing π₀ and pre-trained checkpoints in our new openpi repository! We tested the model on a few public robots, and we include code for you to fine-tune it yourself.show more

Introducing DeepSeek Coder! - SOTA large coding models with... params ranging from 1.3B to 33B. - Building games, testing code, fixing bugs, and analyzing data... You dream it, we make it. - Free for commercial use and fully open-source. Try it out now atshow more

So many R&D artifacts (motion, code, and origami) came... out of this project, we had to build our own internal software for organizing, reviewing, and presenting them But that's a post for another time...show more

when we started Supabase we timed how long it... took to start a database on various platforms and insert a row of data. For AWS it took me 6:49 Kamil Ogórek just did a speed run of supabase - from project creation to "database ready": we're at 10 seconds ⚡show more

Our new Google AI Professional Certificate from #GrowWithGoogle features... 20+ hands-on labs designed to help you use AI as a partner in your daily work. You’ll learn how to: ✔️ Build project plans and daily workflows ✔️ Vibe code custom AI applications for your job ✔️ Generate custom marketing and creative assets ✔️ Develop data-backed market researchshow more

📅 We're thrilled to unveil today the top Priority... 1 from our Q2 Roadmap: the Launch of the Data Lake Chain! This priority comes along with a new ground-breaking use case for $LAKE and the Data Lake App ready for deployment! Get ready for our most ambitious quarter yet as we embark on the largest implementation of blockchain in healthcare ever witnessed! 🔜🪐show more

Static 3D generation isn't enough. We need assets ready... for animation. Our new #SIGGRAPH work, AniGen, takes a single image and generates the 3D shape, skeleton, and skinning weights all at once. Code is fully open-sourced! Kudos to Yihua and VAST AI Research 🧵(1/4)show more

OpenAI's Deep Research is getting a run for its... money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!show more

Announcing "look at your damn data" for Reinforcement Learning!... You now get the full power of W&B Weave traces in the wan deeee bee workspace. For any wandb run that calls an LLM, just "pip install weave" and "import weave" in your code. We also have out-of-the-box integrations for verifiers from will brown, ART from OpenPipe, and verl from Bytedance Seed Team. Use those libraries with wandb/weave installed and everything just works.show more

🔥🔥🔥We’ve been listening to your feedback! Our latest world... model HY-World 1.5 just got a major upgrade to make world generation more accessible than ever: 🛠️ Open Training Code: Fully customizable code for building and training your own models. ⚡ Accelerated Inference: Turbocharged speed and optimized VRAM for real-time interaction. 📉 Lite 5B Model: A new lightweight model that fits into small-VRAM GPUs. 🙌 Zero Waitlist: Our online app is now fully open to everyone—no application required. This is just the beginning. HY-World is building the future of spatial intelligence—open, accessible, and community-driven. 🕹️ Play now: ⭐ GitHub:show more

💡Data Scraping vs. Data Mining: Understanding the Difference Ever... wondered why OptimAI Network emphasizes Data Mining over simple web scraping? Here’s why: 🔹Web Scraping is surface-level, capturing raw data from websites without context, validation, or depth. 🔹Data Mining, however, is a deeper, intelligent process—extracting, analyzing, validating, and refining data into structured insights essential for advanced AI models. 💫 Why OptimAI Focuses on Data Mining? OptimAI's decentralized nodes don’t just collect data—they actively validate, annotate, and refine it. By leveraging collective human intelligence, edge computing, and autonomous AI agents, we deliver the high-quality, real-world data necessary for powering sophisticated AI. 💫 Why It Matters—and Why You Should Join Now Participate now via our OptimAI Lite Node, and become a foundational part of building the most comprehensive decentralized Reinforcement Data Network for Agentic AI. Mine data, fuel innovation, and earn OPI rewards. 👉 Chrome Extension Node: 👉 Telegram Node: Together, let's redefine data for #DePIN #AI.show more

I'll always root for a team that open-sources its... best work, and Robbyant just did it properly. Robbyant, Ant Group's embodied-AI company, released LingBot-Vision, a vision foundation model for robots, and the part I love is the data. They trained it on 161M images, filtered down from 2B raw ones and mostly pulled straight from the open web, with no human labels, no edge detectors, no depth sensors anywhere in the loop. It learns the exact edges of objects from raw pixels. That's roughly a tenth of the data DINOv3 saw, and under a third of the training. And it shows in the results. On depth, working out how far away things are, the 1B model edges out a 7B on NYU-Depth. It also powers LingBot-Depth 2.0, which reads the surfaces cameras usually choke on, glass and mirrors, and halves indoor depth error. LingBot-Vision is fully open. Weights from the 1.1B flagship down to a tiny 21M version, code, and the paper. This is the timeline I want more of. Robbyantshow more

Spent the past few weeks building a fully automated... pipeline for egocentric manipulation data with Kyle Jiang. Any new manipulation task captured using our own wearable sensing platform can now be dropped into the same pipeline with minimal manual fix. Instead of raw videos and annotations, we transform human demonstrations into robot-ready training data. Next, we're bringing touch into the loop with tactile gloves.show more

Ready for 2026 ? Qubic #Science #Neuraxon Research version... 2.1 is out, since life moves so does the data we capture for understanding True #AI Bioinspired evolution. This one includes a deeper exploration of the #TimeSeries of #AritificialLife moments of the Neuraxoners. (Log Level 2, btw it increases 10X the log files) New Hugging Face Dataset 9,170,708 TimeSeries Rows from 40K Nxers about 2,000 Games Code GitHub : And Paper ResearchGateshow more

I am posting after a Long Time on Twitter,... but its to announce a big change. I have started and we are Collecting Egocentric Data at Scale from India, Covering 300 + Commercial Locations 1500 + Households This is the network and base we have built in just past 2 months, as the Robotics companies, VLMs and World Models increase their requirements on Real World Data collection, Human Loops will be keep scaling out capacity. We are on track to collect 1M Hours of Egocentric in the coming 6 months for our clients exclusively. We are maintaining 95% Quality standards across industrial data and running a End - End Operational Management complying all Indian Laws and compensating our partners/operators. (From Environment sourcing, to hardware, Legal contracts, deployment, training, collection, processing) Check our Samples: - Commercial Videos -- Household Videos --- Multimodel ---- Egocentric + Live Audio Narration Links : On the Journey to become #1 India Physical AI Data Partner. We are also building our capacity as annotation and labelling partner for data companies to become end-end partner for companies. A big change from the world of crypto and web3 but physical AI and data space is where i want to build my next venture #Egocentric #EgocentricIndia #PhysicalAI #Robotics #India #AIdata #data #Multimodeldata #worldmodels #VLMs #Humanloops #Egocentridata #Multimodeldatashow more

A Letter to Our Community: The Road Ahead for... Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷show more