Engineers have 3D printed a physical artificial neural network that can analyze large volumes of data and identify objects at the actual speed of light. Developed at the UCLA Samueli School of Engineering the “diffractive deep neural network” uses the light bouncing from the object itself to identify that object in as little time as it would take for a computer to “see” the object.
https://www.therobotreport.com/diffractive-deep-neural-network-3d-printed/
Budget: 290 TECH