MAI-Image keeps climbing! MAI Image 2.7 Preview is now #3 on @arena's image editing leaderboard. #2 by lab and ahead of GPT-Image-2. That's a +45 point jump from 2.6.

Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence. > 6 model instances, across text, audio, vision, and omni modalities, generative and decision models. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding > 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages. > 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language. > 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input. > fine-tune on 1 GPU. > a new tri-hybrid architecture > architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒 Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device. 1/ 🧵

This is Genie 4, our most realistic and interactive world model yet. 🌐 Explore dynamic environments in real time to see how the scene responds, sounds, and how the people in it move, react, and speak.

The largest math proof in human history is now computer-verified. Today, Axiom announces a complete Lean auto-formalization of the Classification of Finite Simple Groups, the "periodic table of symmetry." About 15,000 pages, built by over 100 mathematicians across generations.

Now open source: Ling-3.1-flash-1019. 44 on the Artificial Analysis Intelligence Index v4.3.2, up from 41 for Ling-3.1-flash. Also releasing Ling-3.1-flash-base, an open foundation for further training.

NVIDIA and @Meta will expand our partnership on @Muse models to improve inference and training performance. Together, we’re exploring NVIDIA OpenShell for safe AI agent deployment and NVIDIA Sentry for monitoring agent behavior. Meta plans broader deployments of NVIDIA Vera Rubin and Vera CPUs. Read the press release: nvda.ws/4zVYmDY

Imagine a machine that can track a runner through a dense forest without relying on a single GPS signal. Researchers at the Purdue University IDEAS Lab have developed a new autonomous drone capable of navigating complex woodland environments completely off the grid. Engineered to operate without satellite or cloud networks, the system uses LiDAR inertial odometry to generate precise 3D maps in real time during flight. Because all obstacle avoidance processing occurs directly onboard, the drone can actively weave through branches and predict human movement even when the target is temporarily obscured by the canopy. While this currently remains a research demo requiring further verification for practical performance and safety, it highlights a significant advancement in independent edge computing and computer vision. Media: Aniket Bera on LinkedIn