NVIDIA AI @NVIDIAAI
Teaching your AI new tricks. developer.nvidia.com Santa Clara, CA Joined June 2016-
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OpenShell v0.0.55 🧩 Google Vertex AI inference provider 🔒 Profile-backed policy visibility 🐳 Better Podman detection in the gateway 🖥️ Restored GPU procfs baseline behavior 🔧 CI and docs fixes Run agents against Vertex AI, with improved policy visibility and more reliable Podman and GPU sandbox behavior. github.com/NVIDIA/OpenShe…
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NVIDIA AI retweeted
We have worked with @nvidia to integrate their official Agent Skills catalog into the Hermes Skills Hub. These skills teach your agent how to use CUDA-X libraries, Omniverse and Physical AI workflows, NeMo training and inference tools, and other platform components.
From unboxing to AI agent in minutes. Getting an agent running used to mean sourcing a model, configuring an inference backend, installing a runtime, and wiring it all together. The new NemoClaw install path on DGX Spark replaces that with a single command. DGX Spark also simplifies the path to local, long-running AI agents, cutting out external cloud dependencies and providing predictable on-premise compute.
Inverse Dynamics: Infer the action behind change.
Multiple modalities, many applications. Cosmos 3, the first omni-model for physical AI, is here. Check out some amazing examples below 👇
Self-Evolving Hermes Agents: Enterprise AI That Gets Better With Use | Nemotron Labs x.com/i/broadcasts/1…
@NousResearch Full technical blog here nvda.ws/43GXYen
Teach an agent a workflow once. Have it remember after every rebuild. This tutorial shows how to deploy @nousresearch Hermes Agent with NVIDIA NemoClaw and OpenShell, connect it to Slack, Outlook, GitHub, and NVIDIA developer forums, then turn a chat correction into a reusable skill. Private data stays behind runtime policies. Learned skills persist across deployments.
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