Sep 19 2018

How AI Transforms Traditional Industries and Builds New Ones

AI success stories are appearing more frequently in businesses of every size and type.

When a championship player of Go, considered by many to be the world’s most complex board game, was defeated on his home turf by an AI-powered machine last year, many feared for what the defeat might mean for the future of humanity.

Not Jim McHugh. The vice president and general manager of Nvidia, a company deeply involved in AI and machine learning, made a robust case for the power of the technology at CDW’s “Executive SummIT: Orchestrating a Modern IT Strategy” in Chicago on Sept 18.

“I tell the story about Go, and people say, ‘Yeah, but Jim, doesn’t that mean robots are taking over?’ Not at all.”

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Nvidia Teaches Business Leaders How to Use AI

Nvidia is doing its part to teach humans how to harness AI to transform their businesses. At its Deep Learning Institute, the company teaches “everything from the business cases and what you can do with AI to the deep technical aspects of it,” much of it through free online courses, McHugh said. “If you really want to get started with AI, there’s courses for you; if you want to build an organization around it, we can teach that, too.”

McHugh said the technology is already changing many industries and building new ones. He cited examples of how AI is being deployed across multiple sectors, such as:

  • Financial services: Banks and other financial services companies are using AI to better protect their customers from fraud by analyzing massive amounts of data, building pictures of individual customers’ buying patterns and then identifying suspicious transactions. That’s a big step forward from less advanced fraud-detection methods, where companies look for suspicious activity based mostly on general knowledge and without much insight into individual customers. Frequent business travelers like McHugh often trip over fraud alerts when they’re in new places spending money entertaining clients.
  • Advertising and media: McHugh cited SAP’s Brand Impact as an example of how companies can use AI to understand the value of their sponsorships. Brand Impact scans images and videos for logos and other examples of branding, applies analytics and provides customers with detailed insights on how brands did on brand placement during live events.
  • Data Security: IT security companies are using AI to better understand the rapidly changing nature of attacks. “With ML, they study the characteristics of good vs. bad software and stop it based on that, rather than on static definitions of what malware looks like,” which is too easy for hackers to work around, he said.
  • Healthcare: Machine learning makes possible imaging technology with color, dimension and much richer detail than possible only a few years ago. “In the past, we couldn’t process the data needed for 3D imagery, but with deep learning, it’s possible,” McHugh said. 
  • Sports: Teams and media companies are using AI to monitor games, determine when something exciting has happened and then generate highlight reels of the action for social media and websites.
  • Oil and gas: McHugh cited a company that monitors detailed satellite images of oil wells, oil depositories, ships and other assets, and then applies analytics to the data it collects to provide the industry with detailed insights about production and distribution capacity.
  • Autonomous cars: Though still in development, self-driving automobiles represent perhaps the most advanced use cases for AI, because they use the technology in many different ways simultaneously — to detect distance between the vehicle and other objects, to see what’s around it, to know where the vehicle is on a map, and to monitor the human in the driver’s seat. “So, even when the car’s not driving itself, it will monitor that person who is,” McHugh said.

Moreover, he said, it’s necessary for a self-driving car to understand how different weather and road conditions will affect its actions; it all adds up to a staggering amount of real-time data analysis that’s not possible without AI.

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