We’re already seeing a wave of innovation across industries. From real-world data, computers are learning to recognize patterns too complex, too massive, or too subtle for hand-crafted software or even humans. Already it’s enabling the futuristic cars we only dreamed of — cars that drive themselves — a development that’s changing the huge swathes of the transportation industry.
The potential for AI in healthcare is awe-inspiring. It promises to predict disease in time to prevent it, speed drug development, and help doctors diagnose and treat cancer . In agriculture, Blue River Technology (recently acquired by John Deere) pioneered the use of deep learning to help farmers monitor livestock, manage crops, and pinpoint weeds. AI is even changing sports — helping coaches plan strategy, providing insights that improve player performance, and predicting game outcomes.
My friends in the San Francisco Bay Area love their Golden State Warriors, winners of two out of the last three NBA championships. They and the Cleveland Cavaliers, the 2016 champs, use AI to put their teams at the top of their game . Retailers have been among the most active adopters of deep learning-powered intelligence. The consulting firm Gartner predicts that by 2020, 85 percent of customer interactions in retail will be managed by AI.
For now, deep learning is making shopping faster and easier. San Francisco-based Stitch Fix, for example, provides personalized clothing recommendations based on shopper preferences. Online supermarket Jet.com | Prices Drop As You Shop (recently acquired by Walmart) developed algorithms designed provide the best pricing for a basket of products in a shopper’s cart. Procter & Gamble’s Olay brand has an app that helps people find the right skin care products. Companies like Pinterest and Microsoft’s Bing let online shoppers search for images within images to find and buy products they fancy.
Financial services companies like banks and investment firms are among the earliest adopters of deep learning. Many are already using it to augment investment research, improve investment performance, and bolster fraud detection, and others are in the process of implementing AI. […]