To be sure, as everyone was also quick to point out, it’s early days. It’s not just the first inning, “the first guy’s at bat,” as Amazon’s Bezos put it. It’s also, in his view and that of others, “the edge of a golden era.”
“The combination of new and better algorithms, vastly improved [computing] power, and ability to harness huge amounts of training data…are coming together to solve some previously unsolvable problems,” Bezos said. “It has been a dream since…the early days of science fiction to have a computer that you can talk to in a natural way and have conversation with and ask it to do things for you. And that is coming true.”
Amazon has more than 1,000 people working on its Alexa and Echo ecosystems. “We [also] have a big set of third-party apps that…people have built using our SDK [software development kit],” Bezos said.
Google’s Pichai put it this way: “When it comes to machine learning and AI…when it comes to what we can bring to users…I think we are in the phase of transitioning from computing being these physical devices and screens…to you just expecting them to be there ambiently in context and just working for you. That’s a transition that is happening.”
IBM’s Rometty prefers the term “cognitive solutions,” which she points out are already “a really big part of our analytics business, which is $18 billion [in revenue] and grew 16% last year.” She describes IBM’s Watson capability as a “silver thread [that’s] already happening through lots of [our] products.” For example in health care, one of the industry verticals in which IBM is investing heavily, the company is rolling out an AI oncology advisor that can serve 3 million cancer patients in China, India, and Southeast Asia.
Other companies are active as well. Facebook is building an AI-based technology called Deep Text that can understand the intended meaning of a user’s post, rather than simply recognize keywords, and make recommendations or take actions as a result. Google is at work on multiple applications of similar technologies. Devin Wenig, eBay’s CEO, says that his company uses machine learning technologies to help recognize and eliminate fraud. “There’s getting close on a billion items for sale [on eBay]; there’s no way humans can do it.”
Anup Ghosh, the founder and CEO of software security company Invincea and the former program manager at the Defense Advanced Research Projects Agency (DARPA), predicts that “the security industry is ripe for the same kind of disruption in the enterprise space, and, ultimately, in the consumer product space. Artificial intelligence will replace large teams of tier-one SOC [system on chip] analysts who today stare at endless streams of threat alerts. Machines are far better than humans at processing vast amounts of data and finding the proverbial needle in the haystack.”
Technology companies are the big players in AI today, but their leaders expect that to change. Bezos said, “right now, bigger companies like Amazon have an advantage because of…the training data sets that are required to do this, but there will also be hundreds of startup companies and new advances.” Rometty put it this way: “We picked verticals like health care to go into, but I think most of the innovation is going to come from others, and we are going to give them that platform. On our cloud, almost 60% to 70% of everybody who comes in uses Watson.…We want the rest of the world to do this.”
There is a potential dark side, of course. Issues of job loss from AI-based automation, of privacy loss, and, ultimately, of control of the future, loom large. Tech leaders recognize the job issue but expect the net employment effect to be positive. Google (among others) believes that AI can help improve user privacy. “The onus is on us to give enough value that people trust us.…Actually, I think all the machine learning and AI work we do will help us do privacy better. Over time I think we can get smarter at giving users sophisticated privacy controls,” Pichai said.
There’s also widespread recognition of the potential threat of AI to its creators. No one wants to end up having created Hal. As Tesla Motors CEO Elon Musk observed, “Not all AI futures are benign.” He’s put his money where his mouth his, cofounding a not-for-profit organization, OpenAI, “with a very high sense of urgency…to democratize AI power.” In his view, “It’s important if we have this incredible power of AI that it not be concentrated in the hands of a few and potentially lead to a world that we don’t want.”
According to Rometty, “What really matters is who teaches these things. It’s both the data you use to teach and who does the teaching.”
All in all, the message from the 2016 Code Conference was clear. AI will fuel the next wave of technology disruption in business. Companies that are leading the charge in digital transformation will have a competitive advantage in deploying AI techniques for better customer engagement and business productivity. And there is a huge opportunity for technology companies and disruptive startups to provide platforms, applications, and services to support these business model changes.
When you consider the speed with which the smartphone went from cool new gadget to ubiquitous use—around five years—CEOs will not want to take much comfort in the claims of this being early days in AI. Commercial applications are already real, the technology is developing fast, and it must be on every chief executive’s agenda.