How Telcos Build Autonomous Networks with Agentic AI | NVIDIA Technical Blog
… Those proposals can be passed to agents that apply changes under policy, monitor post‑change telemetry, and trigger fallbacks or new research when targets are not met. …
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How does in-silicon security change the traditional security model?
Purpose-built for AI infrastructure, NVIDIA BlueField DPUs combine high-performance networking, programmable compute, hardware acceleration, and advanced security capabilities into a single platform embedded into every AI factory compute node. Unlike traditional security approaches that rely on host system software, BlueField establishes a hardware-enforced, in-silicon, and workload-independent security layer. Operating within its own trusted execution domain, BlueField isolates infrastructure and security services from the host system. Monitoring, policy enforcement, and telemetry operate eve
Advancing AI Infrastructure for Agentic AI with NVIDIA DOCA In-Silicon Security | NVIDIA Technical BlogHow does DOCA Flow accelerate advanced security services?
DOCA Flow is a foundational library within the DOCA software platform that enables developers and cybersecurity providers to create high-performance, hardware-accelerated packet processing pipelines on BlueField processors. Through a programmable API, developers can define packet processing “pipes” that execute directly in networking hardware, offloading networking and security operations from the host CPU while maintaining ultra-low latency and high throughput. By executing packet inspection, encryption, filtering, and policy enforcement directly in silicon, DOCA Flow enables network security
Advancing AI Infrastructure for Agentic AI with NVIDIA DOCA In-Silicon Security | NVIDIA Technical BlogDevelop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T | NVIDIA Technical Blog
… Run the policy by launching the client from the Arena container: /isaac-sim/python.sh isaaclab arena/evaluation/policy runner.py \ --viz kit \ --policy type isaaclab arena gr00t.policy.gr00t remote closedloop policy.Gr00tRemoteClosedloopPolicy \ --policy config yaml path isaaclab arena gr00t/policy… …
Advancing AI Infrastructure for Agentic AI with NVIDIA DOCA In-Silicon Security | NVIDIA Technical Blog
… This establishes a consistent, hardware-enforced security foundation across the platform. Built on BlueField-4 silicon, a new class of NVIDIA DOCA security capabilities extends protection across the full AI lifecycle and the Vera Rubin platform. …
How to Govern Autonomous Agents in Enterprise AI Factories | NVIDIA Technical Blog
… Use GitOps for policy intent: Store VM profiles, network rules, policy metadata, and release information in Git. GitOps should reconcile the desired platform state, while signed runtime policy bundles are distributed through a controlled release channel. …
Scaling Agentic AI Factories Through Extreme Co-Design with NVIDIA BlueField | NVIDIA Technical Blog
… Learn more Agentic AI changes the infrastructure pattern for AI factories. One request can trigger many model calls, tool calls, memory lookups, policy checks, storage accesses, and network transfers before a final answer is produced. …
Beyond VLAs: How World Action Models Reshape Robot Manipulation | NVIDIA Technical Blog
… Cosmos3-Nano-Policy-DROID is a 16B-parameter policy post-trained from Cosmos 3 Nano for the DROID platform, which is a Franka Panda arm with a Robotiq gripper.A 4B version, Cosmos3-Edge-Policy-DROID , is post-trained the same way, which can be used for on-device deployment. …
How to Self-Host a Validated AI Coding Assistant with NVIDIA NeMo Guardrails | NVIDIA Technical Blog
… If a suggestion is blocked, you can inspect the NeMo Guardrails policy. If a package is rejected, you can inspect the dependency scan output. If AI-assisted changes regress, you can inspect the same production metrics you use for human-authored changes. …
How to Post-Train Autonomous Vehicle Models in Closed-Loop with NVIDIA Alpamayo | NVIDIA Technical Blog
… Alpamayo serves as an example model here. uv run -m alpagym host.cli \ policy=alpamayo \ policy.model.kind=alpamayo r1 \ policy.model.path=/path/to/checkpoint \ reward=progress safety This will bring up AlpaGym with AlpaSim on a single GPU. …
Reducing High-Bandwidth Memory Bottlenecks in JAX-Based LLM Training with Host Offloading | NVIDIA Technical Blog
… Figure 1 shows the activation offloading policy for the repeated MoE decoder layer, which dominates the stack. The first three dense MLP layers are not shown; they use a similar policy, with selected up and down projection outputs offloaded. …
Maximize Spectral Efficiency with AI-Native RAN and NVIDIA AI Aerial | NVIDIA Technical Blog
… Deep reinforcement learning DRL link adaptation changes this by learning the MCS-selection policy directly from observed radio behavior. …