GPU acceleration can speed up compute-intensive robotics workloads, but a fast CUDA kernel alone does not guarantee a fast ROS 2 graph. As messages move between…
GPU acceleration can speed up compute-intensive robotics workloads, but a fast CUDA kernel alone does not guarantee a fast ROS 2 graph. As messages move between nodes, they may continue to be serialized or copied through CPU memory, eroding the benefits of keeping perception and AI workloads on the GPU (Figure 1). With the upstream abstraction and the CUDA buffer backend that NVIDIA recently…

When you ship an AI agent, the key question is whether it can execute a chain of work across dozens of sequential tool calls against a live environment, and…
The compute and memory demands of generative AI increasingly exceed what a single GPU can provide. NVIDIA TensorRT multi-device inference is a new capability…
Weather-sensitive industries increasingly have access to observations that offer an earlier, more local view of changing conditions. Energy companies collect…