SMT007 Magazine

SMT-Sept2018

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42 SMT007 MAGAZINE I SEPTEMBER 2018 So, we know why the medical, military, entertainment, and service industries look to take advantage of XR. Meanwhile, here are some things that will speed up the adoption of XR for the average person: • Increased affordability and com- fort. If the devices become less expensive—and that has already started to happen—and if the devices are easy to use and com- fortable, you can be sure the adoption rate will increase. • XR for social and other events such as sporting events, virtual dating, virtual touring and travel, perhaps to the Grand Canyon or a space station (an extension of the virtual date). • Expand XR beyond sight, sound and touch. Improved touch is already out there with improved haptics and adding the feeling of the wind or heat from the sun, for example, is now possible and improving, but it will be a long time before we can add taste and smell as these will require con- sumables, but it is something that is being worked on. There is no doubt that XR capabil- ities are expanding. This is not a fad like 3D TV with its very limited appli- cations; this is something that has infinite uses. Stay tuned for XR cover- age from CES 2019, where it will cer- tainly be a key focal point. SMT007 Dan Feinberg is the owner and president of FeinLine Associates Inc. and the technology editor for I-Connect007. To read past columns or to contact Feinberg, click here. AI Device Identifies Objects at the Speed of Light A team of UCLA electrical and computer engineers has created a physical artificial neural network—a device modeled on how the human brain works—that can analyze large volumes of data and identify objects at the actual speed of light. The device was created using a 3D printer at the UCLA Samueli School of Engineering. Called a "diffractive deep neural network," the UCLA-devel- oped device uses the light bouncing from the object itself to iden- tify that object in as little time as it would take for a computer to simply "see" the object. The device does not need advanced computing programs to process an image of the object and decide what the object is after its optical sensors pick it up. And no energy is consumed to run the device because it only uses diffraction of light. New technologies based on the device could be used to speed up data-intensive tasks that involve sorting and identifying objects. For example, a driverless car using the technology could react instantaneously to a stop sign. With a device based on the UCLA system, the car would "read" the sign as soon as the light from the sign hits it, as opposed to having to "wait" for the car's camera to image the object and then use its computers to figure out what the object is. "This work opens up fundamentally new opportunities to use an artificial intelligence-based passive device to instanta- neously analyze data, images and classify objects," said Aydo- gan Ozcan, the study's principal investigator and the UCLA Chan- cellor's Professor of Electrical and Computer Engineering. (Source: UCLA)

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