… OpenShell is designed to add privacy and security controls for AI agents. NVIDIA is collaborating with security partners, including Cisco , CrowdStrike , Google Cloud , Microsoft Security and TrendAI , to align runtime policy management and enforcement for agents across the enterprise stack. …
… Creative Intelligence Meets Performance Intelligence With Policy-Governed Agents Governed environments such as the ones enabled by this collaboration act as a set of “guardrails” that keep AI operations observable and auditable, preventing the system from acting outside of a company’s specific data… …
… As a global leader in enterprise applications and business AI, SAP is an important catalyst in the application layer, running finance, procurement, supply chain and manufacturing workflows where agents must operate within policy, identity and process controls. …
… For researchers, the bottleneck is building enough controlled environments and policy rollouts to understand how robot behavior changes across tasks, settings and embodiments — work that typically means stitching together simulation environments, task variations, policy training and evaluation by h… …
… The policy then acts on that annotated view rather than the raw scene. For a policy trained purely in simulation, adding PEEK produced a 41x real-world improvement in accuracy. For large VLA models and smaller policies, gains range from 2-3.5x. …
… With deep visibility into network activity, Forescout applies network segmentation to contain lateral movement and enforce zero trust controls precisely where they matter most, without impacting operations. …
… By combining advanced simulation with structured evaluation, RoboLab accelerates the path from virtual training to real-world deployment. RoboLab features will be incorporated into the roadmap of NVIDIA Isaac Lab-Arena , an open source framework for large-scale policy setup and evaluation. …
… In robotics research, the SONIC project from NVIDIA’s GEAR Lab trains a humanoid controller on over 100 million frames of motion-capture data, then deploys the resulting policy on a physical robot where the kinematic planner runs on Jetson Orin at around 12 milliseconds per pass. …