We demonstrate meta-optic based accelerators that can off-load computationally expensive operations into high-speed and low-power optics. The key to these architectures are the new freedoms afforded by metasurfaces such as optical edge isolation, polarization discrimination, and the ability to spatially multiplex, and demultiplex, information channels. I will discuss how these freedoms can be utilized for accelerating optical segmentation networks and objection classifiers, both based on incoherent illumination. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine-vision and artificial intelligence.
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