.@NSF is hiring the inaugural Head of its Office of Metascience to apply the scientific method to how we fund, organize, and evaluate research. Continuous improvement will accelerate discovery. If you care about the science of science, apply:
nsf.gov/careers/openings/od/…

Chomsky was wrong. Researchers found your brain doesn’t store language the way every textbook since 1957 claims. For decades, the undisputed rule of linguistics, led by Noam Chomsky, was that human language is hierarchical. We were told our brains process language using complex "grammar trees." That we secretly build deep, abstract, mathematical rules in our heads before we speak. This new paper proves that is completely wrong. Researchers at Cornell University analyzed how people actually process and produce language in real time. They found sequences. Linear chunks. When we speak, we aren't calculating deep syntactic rules. We are just predicting the next most logical sequence of words based on the context of the words right before it. We string linear chunks together. If this sounds familiar, it should. This is exactly how Large Language Models like ChatGPT work. For years, critics have dismissed AI as "just a next-token predictor." They said it isn't truly intelligent because it doesn't understand deep grammatical hierarchies like humans do. But this paper suggests humans don't use those hierarchies either. We are just predicting the next chunk. Language isn't a rigid tree of mathematical rules. It's a linear stream of contextual predictions. We thought we were building AI to mimic the complexity of the human brain. It turns out, the human brain was just running a simpler algorithm all along.

Huh? Nanbeige just released Nanbeige4.3-33B, delivering surprisingly strong coding and agent performance for its size, beating similarly sized Qwen 3.8 27b and Gemma models on most benchmarks. The weights are openly available under Apache 2.0, with support for a 512K-token context window. Really really cool release!

Now THIS is a good image model. MOSS Image, 5B Apache 2.0. Already very uncensored! huggingface.co/OpenMOSS-Team… huggingface.co/OpenMOSS-Team…

FLUX 3 Image Klein is here. Open Weights with the quality of a large frontier model. Customizable and fast. 5.6B parameters and runs on a single consumer GPU. Native 4K, bounding boxes, and pixel-perfect editing.

Today, we are announcing GroundedSLAM. LaMAria is the most difficult egocentric SLAM benchmark to date. We are the first to close the gap on Aria’s SLAM and eclipse all other methods by a wide margin. SLAM is the foundation of all 3D estimation. We think this is a big unlock for better robotics 👇🧵

you don't hate math. you just never saw it like this.

These are not 3D reconstructions but 3D-native generation! Check out our new work, GAE, to generate videos and geometry simultaneously! Code and models are already released!

Magnetized neutron stars 💫💫

Thanks for the model, we were able to port Laya to coreml with 99.5% of the ops on ANE + benchmarked too. it is now blazing fast with 3.7 ms per decision on an M5 Pro. Release: github.com/FluidInference/Fl… Models: huggingface.co/FluidInferenc…

You can do better with these charts, guys.

This mosaic is 13,081 tiles, all drawn and animated in code by Opus 5.5, with no image files. The stars' reflections hatch into 22 tiny fish 😌 We're going to need a bigger bowl.

this is insane, a dead fly brain just got a new body 166,700 fruit fly neurons and more than 25 million biological connections are now sitting inside a robotic body that looks almost exactly like the animal they came from the lab gave those neurons cameras, wings and motors, then let the system figure out what those signals meant without writing normal flight behavior for it a light moves and the head turns airflow changes and the wings correct another fly crosses the camera and the robot starts following it the creepy part is how little machinery the brain actually needs before old instincts start becoming useful again nature spent hundreds of millions of years building a nervous system that can react, stabilize and chase movement someone just gave that nervous system a body made of metal the original fly is gone its wiring is still trying to fly

Meta’s Segment Anything Model (SAM) 3.1 is now available on Meta Model API, giving developers a fast and lightweight model for detection, segmentation and tracking in a single call on inference tuned for SAM 3.1's architecture. Use a short phrase to find objects in images and video. One API call returns detections, pixel-precise segmentation masks, and identity-preserving video tracks. Learn more and start building: bit.ly/4rDArq9

We've explored Schrödinger-Poisson quantum fluids in 2D under several different settings before. Here, we take the same physics into 3D with Rabi coupling allowing two quantum wavefields to continuously exchange amplitudes. The glowing golden surface follows the changing quantum density, while the fine trails trace the fluid's probability current.

Reconstructing 3D scenes with this level of quality and fidelity used to take hundreds of images - Atlas reduces this by an order of magnitude

basketball AI (95% local AI + 5% GPT-6 Astra) - detect ball and players - track players - re-identify players across plays - OCR player numbers - recognize player in possession - detect court keypoints - map player positions and trajectories Astra is powerful, but expensive tool. use it when it actually makes a difference. ↓ deep dive

🧬 Rentosertib just turned back biological age in people. ⏱️ 6 aging clocks. 6 independent groups. After 12 weeks, all 6 clocks read them 3 to 4 years younger. 🚀 The first AI-designed drug. The first clinical demonstration of 3–4 year biological age reversal. The first experiment is done. 🔬 Now run your own with Insilico’s SOTA models. #InsilicoSOTAFM

X is a front row seat to the singularity

Super Proud of my Mooshot Mate @EMostaque! Thanks for your creative genius. Excited for this idea to full mature.