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14 PCB007 MAGAZINE I MARCH 2018 sion, in the 1930s followed by the transistor and the microprocessor in the '50s and '60s. There can be little doubt that the rate and pace of disruptive technology has gone from an im- measurable crawl to a run and now to what is approaching supersonic speed. Before we begin discussions on a few of the most disruptive tech- nologies of the present day as well as what is right around the corner, for those of you who are as interested in disrup- tive tech and what it will do to change the look of civilization as we know it, let me rec- ommend some light reading, you might like: Dan Brown's newest novel, Origin [1] . If you read it, let me know what you think. OK, enough background, let's look at some of the most disruptive technology of the pres- ent and soon-to-be future. I have discussed vir- tual reality in recent articles, so except to state that it is clearly on the list, we are not going to cover it again here, but we will continue to watch and report. In addition, I feel that au- tonomous transportation is also in the top five, and I will be covering it in detail in the April issue, but one of the enablers for autonomous cars, trucks, etc., is another great disruptor, artificial intelligence. AI is kind of a catchall used to mean different things to different peo- ple. It basically means computer systems that can learn by themselves. There are different phrases to describe it such as deep learning, machine learning, deep influence and so forth, but all talk about how a computer can learn. One of the leaders in AI technology and computer hardware, NVIDIA, defines machine learning as "the practice of using algorithms to parse data, learn from it, and then make a determination or prediction." For example, the NVIDIA computer controlling an autonomous vehicle (Figure 4) gathers data from its myriad sensors and then parses the data and decides the direction to steer and avoid the obstacles in its path. It allows the vehicle to safely arrive at its destination in spite of the thousands of other changes and moving vehicles along the way. An excellent video published by NVID - IA describes all the different things that AI ac- tually is. You may wish to take a few minutes and watch it [2] . Let's talk economics. It is estimated that in just over a decade AI will contribute over $15 trillion to the global economy. It is expected to add 14% to the North American GDP by 2030. By 2027, just under 10 years from now, the AI-driven autonomous vehicle market is expected to be worth $127 billion. As stated earlier, much more on autonomous driving next month. Another major use of AI and one that is grow- ing rapidly is the connected or smart home. The leader in this rapidly growing segment is Amazon's AI personal assistant, Alexa. Just last month I was asked to take part in a deci- sion being made by a major retirement com- munity here in Southern California regarding which smart home assistant they would incor- porate into their assisted living units starting Figure 3: The Wright brothers' plane at Kitty Hawk, North Carolina. Figure 4: NVIDIA Drive PX Pegasus board.

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