We just did the largest live deployment of interactive... robots in history. Users online could ask the robot to do things it was never taught to do. A true foundation model, with 0 task-specific data and 0 task fine tuning. 1/10show more

We’re excited to introduce Text-to-LoRA: a Hypernetwork that generates... task-specific LLM adapters (LoRAs) based on a text description of the task. Catch our presentation at #ICML2025! Paper: Code: Biological systems are capable of rapid adaptation, given limited sensory cues. For example, our human visual system can quickly adapt and tune its light sensitivity to our surroundings. While modern LLMs exhibit a wide variety of capabilities and knowledge, they remain rigid when adding task-specific capabilities. Traditionally, customizing these models requires gathering large datasets and performing often expensive, time-consuming fine-tuning for specific applications. To bypass these limitations, Text-to-LoRA (T2L) meta-learns a “hypernetwork” that takes in a text description of a desired task, as a prompt, and generates a task-specific LoRA that performs well on the task. In our experiments, we show that T2L can encode hundreds of existing LoRA adapters. While the compression is lossy, T2L maintains the performance of task-specifically tuned LoRA adapters. We also show that T2L can even generalize to unseen tasks given a natural language description of the tasks. Importantly, Text-to-LoRA is parameter-efficient. It generates LoRAs in a single, inexpensive step, based solely on a simple text description of the task. This approach is a step towards dramatically lowering the technical and computational barriers, allowing non-technical users to specialize foundation models using plain language, rather than needing deep technical expertise or large compute resources.show more

How can a visuomotor policy learn from internet videos?... We introduce Dreamitate, where a robot uses a fine-tuned video diffusion model to dream the future (top) and imitate the dream to accomplish a task (bottom). website: paper:show more

Atomic Bot put Hermes and OpenClaw head-to-head on the... exact same task, running the same model (Qwen 3.6 35B) with the same goal: analyzing GitHub history, mapping growth spikes, and shipping a live dashboard in the browser. Key metrics to watch for 👀 > Time to complete the task > Tokens spent > Quality of the final result (dashboard in browser)show more

Alright, now that we know *what* an agent is,... how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.show more

🇨🇳 ROBOT RELAY ON THE GREAT WALL? CHINA JUST... DID THAT Robots just ran an energy baton relay on the Great Wall of China to open the World Humanoid Robot Games. Yes, actual robots. In uniforms. Running. Is it the future of sports, or just the nerdiest flex in history? Source: CGTNshow more

What if your model handled its own tuning? ⚙️... With NVIDIA TAO 7, just prompt your coding agent what you want in plain language and let it do the rest. • Agent skills plug into your coding agent and improve accuracy. • AutoML removes the guesswork from hyperparameters. LLM-guided tuning finds strong configs up to 2x faster. • Fine-tune any Hugging Face CV or VLM model on local NVIDIA GPUs. • Data enhanced fine-tuning helps your agent identify why the model fails, then fix it. Try TAO skills ➡️show more

GPT-5.1 is now live in Warp. It’s much faster... (40% faster task completion on a subset of SWE-bench Verified) without compromising quality. GPT-5.1 is available to all Warp users, and is now the default model for all new users.show more

Peeling a potato is trivial -- until you try... to make a robot do it with a knife. This is actually one of the hardest problems in manipulation: contact-rich, force-sensitive, and success is subjective. We taught a robot arm to peel with >90% success :Dshow more

We were able to embed all of Wikipedia in... < 15 minutes on Modal Labs for ~ 17$. Here's what this actually means for an organization: 1. Unrestricted Rates: Eliminates the bottleneck of rate limits for large-scale operations. 2. Rapid Experimentation: Allows quick iterations of data chunking experiments, reducing wait times from hours to minutes. 3. Fine-tuning: Use of the same hf infrastructure for model fine-tuning, speeding up experiment cycles, and deployment. Reducing experiment timelines from hours to approximately to minutes is something that has compounding effects! take a look!show more

The team just sent me this funny video of... how AWFUL the days after the 2020 election were. People were kinda laughing at me, but it was miserable. And little did we know how bad it would truly get under the Biden and progressive retaliation machine. This was when we first locked in with the Charlie Kirk show and kept up real time updates and analysis where Arizona and a number of other states became central. I never want to go back to this feeling. Never. Charlie was adamant that we do everything we could possibly do to fix this in 2024. We DID IT and we must continue for 2026 and 2028 to have a shot at saving this country.show more

The interactive product page is now fully live on... Shopify . Tested the integration of interactive animation directly within the online store. You can configure the product, and all data stays in sync through to checkout. 🎄 Test it:show more

MolmoAct2 is landing in LeRobot! Ai2's open Action Reasoning... Model combines a Molmo2-ER vision-language backbone with a flow-matching continuous action expert to predict robot action chunks from images, language instructions, and proprioceptive state. An open robot foundation model built for real-world control, with strong out-of-the-box performance and easy fine-tuning in LeRobot. Pick-and-place inference running on NVIDIA DGX Spark! Blog: Paper: Thanks to Ai2 Jiafei Duan Haoquan Fangshow more

Jalen Green hopped off the jet, said he was... going to go 10-0, and then dropped off the 3rd best team in the league by himself to go 10-0 just like he said he would. We are witnessing the rise of a superstar.show more

Announcing our commercial partnership with Booster Robotics Booster builds... humanoid robot hardware, OS, and developer tools to make humanoid robots more affordable, reliable, and practical. The partnership centers on using simulation to multiply the value of real-robot data—expanding teleoperation demonstrations into scalable training data across diverse tasks and scenes. This joint effort powers sim-real co-training and foundation-model development, accelerating progress from hardware iteration to deployable robot policies. Together, we're building simulation‑powered data infrastructure for Physical AI — making scalable training data accessible to model developers and the broader robotics ecosystem.show more

It was all so we could build homes with... robots. All of our work in floorplan AI,and generative CAD modeling, we did all of that, just so that we could build homes with robots. Early on we talked to a robotics engineer from Katerra. It took them $750k to switch from one house to another house. It takes us 25 minutes, and that's if we had a big lunch. P.S. The soundtrack is hardcore punk, lyrics written by me, but everything else is udio.show more

RoboBallet: End of Manual Robot Programming Google DeepMind/Intrinsic/UCL just... cracked multi-robot coordination. Published in Science Robotics. 🤖What it does: – 8 robots, 40 tasks, zero collisions - all planned in seconds – 25% better motion plans than expert-designed solutions – 60% faster task completion when scaling from 4 to 8 robots – Works on factory layouts, it's never seen 👩‍💻 The tech: – Graph Neural Networks map robots/obstacles as connected nodes – Reinforcement learning trains on millions of scenarios – No manual programming required - just give it CAD files and tasks ❓Question: The bottleneck to robot collaboration has always been manual prototyping. Now that we can automate the automation what will this unlock?show more

New Orleans Dancin' Mikaylah Williams and LSU Women's Basketball... run their record to 10-0 with 126-62 win at UNO. 1,588 was the official attendance, the second largest home crowd in UNO women's history. #LSUshow more

PRESIDENT TRUMP on potential talks with Venezuelan President Nicolás... Maduro: "If we can save lives, if we can do things the easy way, that's fine. And if we have to do it the hard way, that's fine too."show more

This also shows up in the representations learned by... the model. We plot the model’s representations of human and robot images. As pre-training is scaled up, the representation of humans and robots become more aligned: to a scaled-up model, human videos "look" like robot demos.show more