Teaching machines to parse through large volumes of data to learn new concepts and rules is a critical area of development in artificial intelligence, experts told CNBC.
That concept is called machine learning, and it's been a longtime goal for the AI discipline: The term was coined in 1959 by AI pioneer Arthur Samuel who defined it as a computer's ability to learn without being explicitly programmed.
To do that, mathematical models are built and then fed with huge volumes of data, experts said. The algorithms learn to identify patterns and assumptions from those data sets that are then applied to process new information.
"We want to be able to use the machine's own capability to learn from complex data," Eric Chang, senior director at Microsoft Research Asia, told CNBC.
One area of machine learning that is being looked at is image recognition. Traditionally, a program would need to be specifically told to look at a facial feature — like a nose — for each photo that comes its way. With machine learning, the program learns from millions of examples what the broad category of a feature — "noses" — looks like, so it can identify new ones in future photos.
Replicate that process for hundreds of features, and you get a powerful tool. Businesses will soon be able to put it to use, experts said.
In an airport lounge, for example, machine learning technology can be used to recognize the faces of every passenger that walks in, according to Ian Massingham, global head of technical and developer evangelism at Amazon Web Services. He explained that it would allow the service staff to pull existing information on each passenger and know their preferences in advance.
"These kinds of services end up playing a role in the decision support or in service support," Massingham told CNBC. He added that such a facility allows the service staff to concentrate on what they do best — personalized interaction.
"A machine can't go up to you and warmly say hello, nice to meet you and smile. So, human beings will have that stuff, but they'll be better informed because they will be using AI and machine learning as part of the customer services workflow."