Artificial intelligence can rev up recommendation engines and make self-driving cars safer. It can even beat humans at their own games. But what else will it do?
At today’s session of the Global Artificial Intelligence Conference, a panel of techies took a look at the state of AI applications — and glimpsed into their crystal balls to speculate about the future of artificial intelligence.
The panelists included Chanchal Chatterjee, AI leader at Google Cloud; Ashvin Naik, CEO of Salespal, which markets AI-enabled sales analysis tools; Rachel Batish, vice president of product for Audioburst, an audio indexing service; and Chip Reno, senior advanced analytics manager at T-Mobile. The moderator was Shailesh Manjrekar, head of product and solutions marketing for SwiftStack, a multi-cloud data storage and management company.
Here are five AI frontiers that came up in today’s conversations, plus a couple of caveats to keep in mind:
Smarter grocery stores: AI-enabled grocery shopping was pioneered right here in Seattle at Amazon Go’s checkout-less convenience stores, but the trend is catching on. Today Walmart unveiled an AI-monitored store called the Intelligent Retail Lab in Levittown, N.Y. Britain’s Ocado online grocery takes a different tack: Users fill up a virtual shopping cart, then schedule a one-hour delivery slot. Google Cloud helped Ocado develop the AI-enabled back end for the ordering system, including a recommendation engine that figures out customers’ shifting preferences, an algorithm that handles and prioritizes customer service emails, and a fraud detection system that’s 15 times as vigilant as Ocado’s previous system.
Energy-saving server farms: Chatterjee pointed to how Google used its DeepMind machine learning platform to cut down on the energy bill for its massive data centers. Before AI was put on the case, 10 years’ worth of efficiency measures could reduce energy usage by merely 12 percent, he said. Within six months, AI brought about a 40 percent reduction. “That was a huge difference that AI made in a very short amount of time that we could not do with 10 years of research,” Chatterjee said.
Financial market prediction: Hedge fund managers and bankers are already using artificial intelligence to shape trading strategies, detect market manipulation and assess credit risks. But Chatterjee said the models are getting increasingly sophisticated. AI is being used to predict how margin trades could play out, or whether undervalued financial assets are ripe for the picking. AI models could even anticipate when large blocks of a company’s stock are likely to be sold off. “When the lock-in period expires … that’s a great time to short,” Chatterjee said.
Deeper, wider AI conversations: Chatterjee predicted that our conversations with voice assistants are likely to get wider, deeper and more personal as AI assistants become smarter. Audioburst’s Batish said conversational AI could provide a wider opening for smaller-scale startups and for women in tech. “Women are very much prominent in conversational applications and businesses,” she said. Salespal’s Naik agreed with that view — but he worried about the dearth of compelling applications, based on his own company’s experience with voice-enabled devices like Amazon Echo and Google Home. “They’re gathering dust. … We use them just to listen to music or set up alarms. That’s it,” he said.
AI for good, or evil? Chatterjee said AI could be a powerful tool to root out fraud and corruption. AI applications could be built “to see what influence relationships have on outcomes — that tells you if there are any side deals being made,” he said. But Batish worried about the rise of “deep fake” videos, lifelike virtual avatars and lifelike synthetic voices. “I’m actually afraid of what that could bring into our world,” she said. “It would be interesting to see how companies are trying to be able to monitor or identify fake situations that are being built out of very complicated AI.”
Watch out for job disruption: Many studies have pointed out that automation is likely to disrupt employment sectors, especially in the service, manufacturing and transportation sectors. “Anything that is repetitive, that can be extracted from multiple sources, that doesn’t have a lot of creativity amd innovation, is at risk due to AI,” Chatterjee said. “That means that more people will have to move into other sectors.”
Watch out for the hype: “I’d like to see people get away from the hype a little bit,” T-Mobile’s Reno said. “I’m on the client side, so I see all the pitches involving AI and ML or deep learning. … A lot of times, AI is not applicable to certain use cases where we’re applying it. Just good old-fashioned statistics or business intelligence is fine. So I think that the future of AI relies on getting past the hype and getting more into aligning these awesome tools and algorithms to specific business cases.”
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