Neura Robotics has launched Neuron AI, its multimodal foundation model for physical AI. Combining 3D vision, touch, audio, robot state and language with memory, Neuron AI enables robots to act on information beyond what cameras alone can capture, as well as retain relevant context when objects disappear from view. Its “Perception-Language-Action” (PLA) architecture connects what […]

Odyssey, an AI research company pioneering foundation world models, has announced Odyssey-3, its most powerful world model to date. The new model represents a significant advance toward general-purpose intelligence that can understand, predict, and interact with both physical and virtual environments. World models learn from vast examples of the world evolving to predict and simulate […]

Runway, one of the best-known developers of generative AI video technology, is moving into robotics with Praxis-1, an open-weight AI model designed to use knowledge learned from video to control physical robots. “Open-weight” means developers can download the model and run or adapt it themselves, rather than only accessing it through Runway’s servers. The company […]

Radiology AI has made remarkable strides in detecting abnormalities across chest X-rays, pathology slides, and 2D scans. Yet one of the most clinically rich and...

Radiology AI has made remarkable strides in detecting abnormalities across chest X-rays, pathology slides, and 2D scans. Yet one of the most clinically rich and data-dense modalities—the 3D computed tomography (CT) scan—remains largely underserved by modern vision language models (VLMs). Frontier general-purpose models perform poorly on volumetric imaging, and most open medical AI models lack the…

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GENCO is a neural solver that, alongside the GridFM Development Framework, unifies three core electrical grid analysis tasks.

Every byte moved has a cost. As model checkpoints grow to hundreds of gigabytes or even a terabyte, that cost adds up quickly. To make things even worse, moving...

Every byte moved has a cost. As model checkpoints grow to hundreds of gigabytes or even a terabyte, that cost adds up quickly. To make things even worse, moving these model weights around the cluster is extremely common. For instance, a cold start may pull weights from remote storage into GPU memory; autoscaling and rolling updates must populate each new replica; and RL post-training continuously…

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The NVIDIA Nemotron Model Reasoning Challenge invited the Kaggle community to explore a focused question: What techniques can improve reasoning accuracy when...

The NVIDIA Nemotron Model Reasoning Challenge invited the Kaggle community to explore a focused question: What techniques can improve reasoning accuracy when everyone starts from the same open model, benchmark, infrastructure and evaluation constraints? The response was massive. By the close of the competition, more than 5,000 active participants across 4,000 teams had generated thousands of…

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Useful quantum computers will require fault tolerant logical operations. Researchers are actively exploring many different quantum error correction (QEC) codes...

Useful quantum computers will require fault tolerant logical operations. Researchers are actively exploring many different quantum error correction (QEC) codes to enable this, improving the Logical Error Rates (LER) of Quantum Processing Units (QPUs). While it is well understood how to run logical operations with surface codes (which belong to the topological code family) via lattice surgery…

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As more teams move from humanoid robot bring-up to task-specific skill development, the need for repeatable development workflows is growing. Building humanoids...

As more teams move from humanoid robot bring-up to task-specific skill development, the need for repeatable development workflows is growing. Building humanoids remains complex, and today’s development pipelines are still highly fragmented. As a result, developers spend significant time configuring robotics infrastructure before they can focus on building robot capabilities.

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Foundation models are reshaping computational biology. Pretrained on massive corpora of protein or genomic sequences, models such as ESM2 (a protein language...

Foundation models are reshaping computational biology. Pretrained on massive corpora of protein or genomic sequences, models such as ESM2 (a protein language model) and Evo 2 (a DNA language model) capture statistical regularities of biological sequences. These transfer well to a wide range of downstream tasks, including structure prediction, variant effect, and functional annotation.

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