Introducing Strong Stochastic Flow Maps
TLDR: Stochastic Flow Maps where we learn the stochastic solution path.
Work led by Sam McCallum, @zwblasingame, with Timothy Herschelll, @AlexanderTong7, and @JamesFosterBath
Arxiv: https://t.co/Hy8WWZOnjE
Code: https://t.co/PMe6RoqyZA
Someone on reddit built an automated Pigeon defense system for their balcony.
pigeons kept shitting and nesting on his balcony so he built a fully autonomous AI sentry gun to snipe them with water.
here’s how it works:
→ a usb camera spots the pigeon
→ a neural net identifies it in real-time
→ 2 servos aim a water gun
→ fires automatically.
runs on a $50 orange pi 5. zero human input.
100% open source.
Introducing new data layers for building footprints, land parcels, and AI powered layers that spot infrastructure assets from Street View imagery. Try these new layers now ➡️ https://t.co/x7VjSUUanY
With information right at your fingertips you can spend less time combining data, manually identifying assets, and combing through imagery. These premium layers are now available for Professional & Professional Advanced customers on web and Android.
👀 Kall Morris Inc.’s REACCH system capturing a target object during testing on the ISS.
Instead of a single small satellite test, the team completed 172 test runs, validating the system for debris removal and in-orbit relocation: https://t.co/HiLLKs1lGj
#SpaceDebris#ISS
Wow. This is crazy.
A developer trained an AI agent in simulation and deployed it onto a real robotic air hockey table using reinforcement learning.
This robot can track the puck with millimeter-level accuracy and react in roughly 20 milliseconds, fast enough to challenge even skilled human players.
We’re moving from robots that follow programmed rules to machines that learn strategies in simulation and execute them in the physical world.
This is THE moment of Physical AI!
We are officially announcing Cosmos 3: Omnimodal World Models for Physical AI 🚀
- Cosmos 3 is an omnimodal world model: within a unified architecture, it can understand and generate language, images, video, audio, and actions.
- It is not just a VLM, not just a video generator, not just an audio-visual generative model, and not just a physics simulator / world-action model. It can understand images and videos, generate images, videos, and audio, simulate future worlds, predict actions, and generate robot policies—enabling models to truly begin to “touch the world.”
- Cosmos 3 is the #1 open-weight reasoner / T2I / I2V / robot policy across many benchmarks.
Huge thanks to every teammate who fought side by side on this journey—from architecture, data, training, infra, serving, and evaluation to post-training. Every part of this project carries an incredible amount of hard work. This was my first time leading a project as Tech Lead, and I feel truly fortunate.
The future of Physical AI needs models that can not only “see” and “describe” the world, but also “imagine,” “simulate,” and “act”—and eventually close the loop with the real world. I hope Cosmos 3 can become an important starting point for this direction, and I’m excited to push Physical AI into its next stage together with the open-source community.
Welcome to the era of Physical AI.
HuggingFace: https://t.co/QW5h5pIWWM
Project Website: https://t.co/Jppa0gkn16
Code: https://t.co/aJgaLm5BaG
gm. 🚦🚗
Simple traffic simulator built with ClaudeAI. Not even Claude Code. Pretty fun to watch the impacts of red light timings and the green wave coordination.