OCTOBER 2019CIOAPPLICATIONS.COM 19electric toothbrush was mechanical; the head vibrated and that was about it. Now electric toothbrushes connect to apps that tell you how well you're brushing your teeth, when you need to replace the head, and much more. Soon everyday devices will use machine learning to understand your habits and needs almost better than you do.Developing the smart products of tomorrow requires skill in many disparate areas. Using the toothbrush example again, you need industrial and mechanical design, mechanical engineering, electrical design and engineering, embedded development and hardware design, and even machine learning expertise. To prototype your product, you need injection molding machines and on-demand printed circuit board manufacture and assembly. Most companies specialize in a few of these areas, but I've yet to find another company that provides all these capabilities under one roof--we do. And for complex systems, we're doing more of the development in a virtual environment.Could you shed light on the company's deep learning platform, aiVision? Many recent successes in AI, such as self-driving vehicles, voice processing, and healthcare, use a technique called deep learning. Deep learning utilizes computer models that roughly emulate the neural networks of the human brain. They are trained by providing the model with a very large number of examples of the items of interest. That's easy when you're looking for cats in photos because there are millions of those images online, but what if you're developing an autonomous vehicle? You need billions of driver-miles of camera and sensor data, and creating that data with test fleets could take hundreds or even thousands of years. This problem can only be solved with synthetic data, that is, data that the AI model interprets as real but is created artificially. That is the approach that Waymo and many others are taking.We were early to recognize the effectiveness of synthetic training data for deep learning, and two years The intelligent products and systems of tomorrow will be designed, engineered, and tested virtually; get on that train now or you're going to be left behind
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