Ascend-native multi-resolution visual feature extraction to cut on-device compute

Ascend-native multi-resolution visual feature extraction to cut on-device compute targets a $12.0B = 200,000 enterprises deploying vision infra x $60K average annual spend on CV model infra & tooling total addressable market with medium saturation and a year-over-year growth rate of 18%.

Key trends driving demand: Edge-AI acceleration -- shifting inference from cloud to edge increases demand for hardware-specific optimizations and compact multi-resolution models.; Hardware specialization -- NPUs (Ascend, Qualcomm, etc.) require vendor-specific kernels and compilation flows to unlock efficiency.; Sparse and efficient vision models -- advances in sparse attention and multi-scale feature extractors reduce compute and memory footprints on edge devices..