…9 MIN READ Dec 12, 2025 How to Build Privacy-Preserving Evaluation Benchmarks with Synthetic Data Validating AI systems requires benchmarks—datasets and evaluation workflows that mimic real-world conditions—to measure…
…Models take more steps, call more tools, run more evaluations, and interact with execution environments to perform tasks . This blog explains how NVIDIA Vera CPUs help AI factories to scale agentic AI…
…Partitioning strategies We evaluated two primary strategies for GPU partitioning supported by the NVIDIA GPU Operator. Software-based partitioning: Time-slicing and MPS Time-slicing enables multiple NVIDIA CUDA processes to share…
…Deploying autonomy in a safe and trustworthy manner requires achieving real-world fidelity, which is incredibly challenging without simulation of rare real-world scenarios. It requires accurate modeling of the physics and…
…A framework for evaluating real-world manipulation policies (RT-1, Octo) in simulation to reliably predict physical performance. NVIDIA GTC AI Conference is happening March 16–19, 2026 in San Jose with…
…Every customization decision—from a prompt tweak to a GRPO training run—should be driven by clear metrics and validated against real-world performance. Ready to customize your agents? Accelerate development with…
…Her work is centered on enabling organizations to build AI agents that are specialized, well-governed, and ready for real-world deployment. View all posts by Isabel Hulseman View all posts by…
…Her experience includes advancing the optimization and adoption of GPU-accelerated inference pipelines and agent workflows for real-world environments. She is currently developing the AIQ Research Assistant, a deep-research agent…
…Running the Slurm code Replaying production workloads or generating synthetic workloads Simulating real-world conditions, including node failures and recoveries Integrating with the metrics system for direct comparison of results This setup…