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"The future of AI processing"

Heterogeneous compute and a new paradigm for AI at the edge.

Artificial Intelligence (AI) is emerging in everyday use cases, thanks to advances in foundational models, more powerful chip technology, and abundant data. To become truly embedded and seamless, AI computation must now be distributed—and much of it will take place on device and at the edge. 

To support this evolution, computation for running AI workloads must be allocated to the right hardware based on a range of factors, including performance, latency, and power efficiency. Heterogeneous compute enables organizations to allocate workloads dynamically across various computing cores like central processing units (CPUs), graphics processing units (GPUs), neural processing units (NPUs), and other AI accelerators. By assigning workloads to the processors best suited to different purposes, organizations can better balance latency, security, and energy usage in their systems. 

“The future of AI processing” is an MIT Technology Review Insights report produced in partnership with Arm. 

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