Present-day edge AI systems rely heavily on multi-modal sensor fusion, such as camera, lidar, and radar, to enable accurate, real-time decision-making. Existing platforms, such as NVIDIA® Jetson Orin NX, are equipped to adequately support multi-camera use cases. To advance this further, NVIDIA’s latest Jetson Thor series modules have been combined with the Holoscan Sensor Bridge board – running on a Lattice FPGA – to address the increase in sensor counts and synchronization...
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Interest in edge computing has surged as organizations across industries seek smarter ways to automate processes, enhance productivity, and optimize labor. By processing data closer to its source, edge systems can provide benefits like reduced transmission and storage costs and strengthened security. They can also enable the development of advanced machines and devices, from autonomous mobile robots (AMRs) and humanoids to smart medical devices, which can operate with precision and speed.
Thes...
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Across industries and use cases, computing capacity is shifting away from centralized servers and towards the edge. Whether in the form of autonomous vehicles, smart sensors, or other technological solutions, today's intelligent applications demand faster decision-making and increased autonomy.
This shift is especially prevalent in the Industrial, defense, and aerospace industries. The unmanned aerial vehicles (UAVs) and drones used in defense applications rely heavily on edge intelligence to...
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