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Waymo has published the architecture of its robotaxi onboard computer, offering its first detailed look inside the vehicle system. The company also introduced a custom 5-nanometer chip and identified seven suppliers supporting the platform.
Moderna and Merck reported that a personalized mRNA therapy, intismeran, combined with Keytruda met key recurrence and distant-metastasis survival endpoints in a prespecified interim analysis. The approach uses AI to select up to 34 tumor-specific neoantigens for an individually manufactured treatment.
Claude can now send, reply to, and forward Gmail messages on a user's behalf. Users can grant the assistant more autonomy without approving every individual action.
AWS outlines enterprise patterns for operating many agentic AI systems across diverse frameworks, models, and providers. The guidance focuses on preserving flexibility and enabling multi-agent systems to scale together without vendor lock-in.
Waymo has disclosed key details about the high-performance computers installed in the trunks of its robotaxis. The company shared processor specifications, chip architecture, internal components, and hardware suppliers for the first time.
Rising AI server power density is turning cabinet-level Battery Backup Units from an optional component into a required part of data-center power architecture. Global BBU cell shipments reportedly reached about 276 million units in the first half of 2026, intensifying shortages and competition among Asian battery suppliers.
The Spectral Neuron is a proposed ML primitive based on the largest eigenvalue of an input-conditioned matrix. The preprint develops its mathematical properties, initialization and training methods, and evaluates scalability on synthetic and real-world datasets.
MORPHI made its first systematic domestic appearance at WRC, showcasing its newly released embodied-intelligence model architecture, MoRA. The demonstration focused on how a robot’s embodied brain supports practical long-horizon tasks.
Apple Machine Learning presents a lexical-intervention approach for improving cross-lingual knowledge transfer when target-language data is scarce. The work targets downstream capabilities such as scientific reasoning, commonsense inference, and world knowledge without relying heavily on parallel data, translation systems, or auxiliary models.
An MIT study finds that AI-generated images often cannot be traced to individual training images. As datasets grow larger, the influence of any specific example tends to fade.