The debate about artificial intelligence (AI) rages on. Will it take all of our jobs? Will we be able to find skilled workers for our organizations? Will robots self-replicate at an uncontrollable rate, taking over Earth and rendering humans useless?
For at least two technology executives in Asia, the future of AI is nothing but bright.
“If I had to do my career all over again,” says Dean Samuels, head of solutions architecture for Amazon Web Services in Hong Kong and Taiwan, “I think I’d definitely focus on the analytics or the machine learning part because it’s going to be such a large component of any large software project.”
Indeed, the potential of AI — and its many branches — is unlimited, the executives maintain.
“You go down below artificial intelligence, and the focus right now is on deep learning and machine learning,” Samuels says. “If you have a look at some of the things that are happening in the various industries around things like chatbots and natural learning, natural language processing, computer vision and other areas, they really are the tip of the iceberg.”
AI and other emerging technologies are crucial to making the high-quality business decisions required to innovate. But most organizations have yet to capture more than a fraction of their data’s value. And as AI and machine learning take hold, questions remain about how to build models that are useful.
“As these models begin to develop, I think what we’ll see is maybe the data that we didn’t think was valuable is actually the key to how we can solve complex business problems,” says Dan Angelucci, DXC Technology’s chief technology officer in Asia. “The next generation of business problems is not going to look like this one, and I think we have to be up for that kind of a challenge.”
While Angelucci sees the great potential of AI in the workplace today, he continues to look to the future.
“When I look just past the horizon, I start to see the next set of computing problems that really need solutions,” says Angelucci. “I see the nascent capabilities in something like quantum computing, which is really a paradigm change for how it is we view computing itself. I think that that’s where things are heading in a hurry.”
In the meantime, Samuels places a priority on democratizing AI, making it easier for enterprises to realize its potential today.
“We understand that we need to put the capability of deep learning and machine learning — artificial intelligence — in the hands of the everyday person,” says Samuels. “You don’t have to be a hardcore machine learning practitioner in order to take advantage of this.”