AI HW: NPU vs GPU; TOPS

NPU vs GPU: What's the Difference? | IBM

Efficiency: While GPUs are capable of handling many demanding tasks associated with AI, NPUs are purpose-built for these requests and can meet similar or even better performance benchmarks while requiring exponentially less power, a particularly valuable feature for battery-powered devices with finite capacity.

CPU vs GPU vs NPU: What's the difference? | CORSAIR

Neural Processing Units (NPUs)...are designed to efficiently handle matrix multiplication and addition, which is essential for artificial intelligence (AI) and machine learning (ML) workloads
such as image recognition, natural language processing, and machine learning."

A guide to AI TOPS and NPU performance metrics | Qualcomm

TOPS quantifies an NPU's processing capabilities
by measuring the number of operations (additions, multiplies, etc.)
in trillions executed within a second.

AI accelerator - Wikipedia

An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator[1] or computer system[2][3] designed to accelerate artificial intelligence and machine learning applications

All about neural processing units (NPUs) - Microsoft Support

NPU uses less power and is far more efficient at AI tasks than a CPU or GPU.

for Copilot+ PCs.

Do we really need NPUs now? - YouTube by TechAltar

micro "neural network" example, image detection with matrix multiplication

A specialized NPU does not take up much space on processor chips.