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Oct 24, 2018 24 min

Artificial Intelligence...Driving In the Streets

from Luminaries - Talking to the Brightest Minds in Tech Hosted by Dell Technologies, Mark Schaefer, Douglas Karr

What You'll Hear In This Episode How machine learning builds a robot's social intelligence How AI and IoT could make cities more accessible, smarter How data being used to develop autonomous vehicles can also be used for town planning How technology can improve the quality of life for the inhabitants of ""smart"" cities" Artificial Intelligence, Autonomous Vehicles, and the Smart City of the Future The average speed of traffic through London has not changed since the days of horse-drawn carts. All of the transportation advantages of the past 200 years, from the internal combustion engine to the highway system, haven’t increased the rate of travel. The infrastructure simply can’t keep up with the demands of the populace. But why is this significant? To truly serve people’s needs now and in the future, cities need to get smarter to cope with a growing population and its demands on city services. Our guest this episode is helping to create the “smart cities” of the future. Dr. Richard Kelley, Chief Engineer of the Autonomous Systems Group at University of Nevada Reno, explores how artificial intelligence, machine learning, and the Internet of Things can ease traffic congestion, increase mobility, and make civil services more accessible.

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Most cities were built for a reality that no longer exists. The streets were laid out for horse-drawn carriages. Crosswalks and intersections were designed for 1980s population levels. To make cities more livable, city planners need better insight into how people actually use the city, how they move through it and live in it. In this episode, Dr. Richard Kelley explains how artificial intelligence, machine learning and the internet of things work together to create “smart cities” – cities that reflect the needs of citizens now and in the future.

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Artificial Intelligence...Driving In the Streets

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This episode is 24 minutes long.

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This episode was published on October 24, 2018.

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