NVIDIA and AWS describe how to run a continuous Physical AI “model factory” pipeline using NVIDIA Cosmos 3 on Amazon SageMaker HyperPod, moving through synthetic-data generation, post-training, and closed-loop evaluation on a single shared cluster and storage setup. Cosmos 3-Super is a 64B-parameter model that can be post-trained into a deployable policy. The workload no longer requires separate GPU pools per pipeline stage because the same persistent node pool under one control plane time-shares generation, training, and evaluation for better GPU goodput across the whole loop.
InstantStart lets an AI agent run multi-stage Amazon SageMaker HyperPod cluster setup by driving the same control-plane APIs behind the web console and terminal workflows. EKS control-plane creation takes about 8–12 minutes before dependency installation and HyperPod cluster creation proceed. As a result, long-running steps become retryable, the agent asks only decision inputs (like zone and instance details), and it returns a verified running cluster with storage mounted instead of a pending request.
Experian partnered with ServiceNow to roll out an agent operating system that lets customers embed Experian’s risk, identity, and decisioning capabilities into enterprise workflows. The first partner deployment is scheduled with ServiceNow connecting to Experian’s Ascend analytics and development platform. This shifts Experian’s AI from an internal virtual assistant into enterprise scaling via APIs and a model context protocol, with controlled agent access and human-in-the-loop for regulated decisions.
A team that previously shipped an AI agent based on small test chats found that later changes (like retrieval configuration and a model upgrade) could cause skipped required citations and incorrect tool selection. The article argues evaluations must be repeatable and used as a release gate, starting with 10 real tasks frozen with fixtures such as pinned account state and versions of prompts, retrieval configuration, tools, permissions, and traces. Teams will keep an evaluation suite alongside the agent so each release can be blocked on deterministic high-risk failures and scored with evidence rather than relying on demos or one-off transcript checks.
Microsoft named its developer-optimized Windows experience “Project Zenith” for new developer-focused devices. The devices are built with 64GB or more of unified memory. Microsoft will ship a preconfigured Windows setup plus curated development tools on those machines so developers can run large models locally without metering for experimentation.
Google DeepMind released WeatherNext 3, a global weather forecasting model that uses live geostationary satellite data and reinitializes every hour to improve local detail and reduce latency versus relying on delayed NWP analysis.
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