The Road to Artificial Intelligence

Tuesday, May 2, 2017

The Road to Artificial Intelligence

Self Driving Cars

Once seen as purely science fiction, self driving cars are becoming more than a vision for the future; they are becoming a reality. But with this new technology comes concerns about safety. Premiering at the Red Hat Summit, the “Road to A.I.” is a documentary film that asks some of the most crucial questions facing the transportation and technology.

Premiering at Red Hat Summit, the “Road to A.I.” documentary film asks some of the most crucial questions facing the transportation and technology industries as we shift to a more autonomous future. How is artificial intelligence being programmed to make decisions we can live with? Can sharing data make self-driving cars more safe?

Part of Red Hat’s Open Source Stories film series, “Road to A.I.” is the latest installment from Red Hat to highlight and share stories about how openness is a catalyst for change.

Open source is changing the world in many different ways - from technology innovation and management advancements to innovations across sectors. Red Hat has long understood the power of collaboration to produce amazing results. With Open Source Stories, the team is showing what people can do when they make things in the open.

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The film features luminaries from the world of artificial intelligence including: Chris Nicholson, CEO of Skymind; Liam Paull, founder of Duckietown; Karl Iagnemma, CEO and co-founder of nuTonomy; Mary “Missy” Cummings, professor in the Department of Mechanical Engineering and Materials Science at Duke University; and Francois Chollet, A.I. researcher and author of Keras, a deep learning library for Python development.

"What is going to happen is that AI is going to become increasingly integral to our lives, to society. It will become basically part of the infrastructure of society," states Chollet. "It will become our interface to the world. To a world that will become increasingly information-rich and complex. AI is going to change what it means to be human."

From Tesla, to Uber, to Google, to BMW, to Toyota and more, businesses are betting and investing billions on self-driving cars, making them more than just a vision of the future (U.S. proposed $4B in 2016 to support movement). They are here now, and could make up 15% of all new cars bought by 2030 according to McKinsey, making it a timely conversation to dissect the open collaboration and data-driven approach behind the movement’s development.

"The application of AI to self-driving cars is the living-edge of AI," comments Nicholson. "It is really a great test of whether AI is really ready for the real world."

"We're kind of sewing the parachute on the way down."
Iagnemma states, "The self driving car industry is really at an interesting moment. We're kind of sewing the parachute on the way down, if you will. There is immense promise in this technology, because you could argue that it's a moral imperative that we should move quickly. We have within our grasp a technology, that once we get it right, we can put on the road and reduce or eliminate the tens of thousands of lives that are lost in the U.S. alone from motor vehicle accidents. So we have to move fast."

The technology though, for a large part, and despite the hype, is still in a research phase.

"When we talk about autonomous vehicles, and how they work, they all kind of work the same way regardless of whether or not we are talking about a drone or an automated car, or an automated train," says Cummings. "Any automated transportation device has to develop something we call the 'world model.' If you understand what the world around you is, then you then make decisions based on your world model."

The video presents how collaborative work on large amounts of data will lead to better algorithms for self driving technology. This includes computer vision, and the translation of data from the numerous sensors that are being used to develop automated driving, from motion sensors to LIDAR, to interpreting the behavior and intent of other road users.

SOURCE  Red Hat Open Source Stories

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