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Scaling Data Movement For Physical AI

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Scaling Data Movement For Physical AI

Physical AI poses a host of new challenges for chip engineers. These systems contain a mix of compute elements, which collectively must process a stream of real-time data, analyze it, make decisions, and still function long enough on a battery to be useful. The key here is deciding what data gets processed where, and how to minimize the movement of data. Ashley Stevens, director of product management and marketing at Arteris, talks explains why data movement plays such an important role in these systems, why coherent interconnects are better suited to CPUs and non-coherent interconnects are better for AI acceleration, and what other challenges engineers will face going forward.



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