Healthcare

Picture this: You’re a doctor at the end of a grueling 12-hour shift. Your eyes are tired, your coffee has gone cold for the third time, and there’s still a stack of blood smears waiting to be analyzed. Each one contains thousands of tiny cells, and somewhere in that microscopic haystack might be the needle that indicates leukemia. Now imagine having an assistant that never gets tired, never loses focus, and — here’s the kicker — actually knows when it’s unsure about something. ...

Nous Research’s NousCoder-14B is an open-source coding model landing right in the Claude Code moment Nous Research, backed by crypto‑venture firm Paradigm, unveiled the open‑source coding model NousCoder‑14B, which was trained in just four days on 48 Nvidia B200 GPUs and reaches a 67.87 % accuracy on the LiveCodeBench v6 benchmark—about 7 percentage points higher than its base model, Alibaba’s Qwen3‑14B. The release includes not only the model weights but also the full Atropos reinforcement‑learning environment, benchmark suite and training harness, allowing anyone with sufficient compute to reproduce or extend the work. Training leverages “verifiable rewards” (binary pass/fail on executed code), dynamic‑sampling policies, and progressive context‑window expansion up to roughly 80 k tokens, while pipelining inference and verification to maximize GPU utilization. Researchers note that the 24 000 competitive‑programming problems used for training exhaust most high‑quality public data in the domain, prompting calls for synthetic problem generation and self‑play to overcome future data scarcity. With $65 million in funding, Nous Research positions its open‑source approach as a direct competitor to proprietary tools like Anthropic’s Claude Code, emphasizing transparency, reproducibility, and the next‑generation research directions of multi‑turn RL and autonomous problem creation. ...

Getting a perfectly clear video of a beating heart has always been like trying to photograph a hummingbird in flight—the constant motion makes everything blurry. But a groundbreaking AI technique called MoCo-INR is changing the game, delivering ultra-fast cardiac MRI scans up to 20x faster than traditional methods while maintaining exceptional image quality. The Heart Imaging Challenge Cardiac Magnetic Resonance (CMR) imaging is a critical diagnostic tool that offers unparalleled soft tissue contrast and provides non-invasive evaluation of heart function. However, capturing clear images of the constantly beating, twisting heart presents a fundamental challenge. ...

The quest for understanding the complex world of proteins has just taken a significant leap forward with the introduction of OpenFold3, an open-source artificial intelligence (AI) model designed to predict the 3D structures of proteins. This development is crucial because proteins are the building blocks of life, and their structures determine their functions, which in turn affect virtually every aspect of biology and medicine. Developed by the OpenFold Consortium, a non-profit collaboration of academic and private research groups, OpenFold3 uses amino acid sequences to map the 3D structures of proteins and model their interactions with other molecules, such as drugs or DNA. This capability is not just a novelty; it has profound implications for drug discovery, disease research, and our overall understanding of biological processes. ...

As the AI landscape continues to evolve, NVIDIA is furthering its commitment to open-source technologies, unveiling new models for language, robotics, and biology. This move reflects broader industry trends towards democratizing access to AI and fostering innovation. By contributing to the open ecosystem, NVIDIA aims to empower developers worldwide and drive economic growth through efficient reasoning, high-fidelity world generation, and interactive physical AI systems. The new open models, data, and tools are part of the NVIDIA Nemotron family for AI reasoning, NVIDIA Cosmos platform for physical AI, NVIDIA Isaac GR00T for robotics, and NVIDIA Clara for biomedical AI. These technologies will be made available through Hugging Face, a leading platform for AI model sharing and collaboration. As a top contributor to Hugging Face, NVIDIA has already made over 650 open models and 250 open datasets available, expanding access to cutting-edge AI resources for the global developer community. ...