“We’re using a visual analysis of the data,” Bier said. “The technology learns from the data. We try to focus on making a system that’s fast. A lot of the analysts we work with have had bad experiences with systems that might have needed hours or days to get a report. We like to focus on getting answers in seconds.”
Ford AI scheduling
At Ford Motor Co., managers are using an AI system to take on what was becoming a massive, and time-consuming, job of scheduling new hires through a three-year training program.
Instead of a group of people spending hours trying to organise a growing number of program participants, job requests and assignments, the AI system – built, coincidentally, by one of the new hires – handles it for them.
“It was [a problem] that was taking away time from people who didn’t have time,” said Leonard Kinnaird-Heether, an AI researcher at Ford who built the program. “AI was a good idea for this because this problem represents a core function that AI can take care of … We developed a tool to automate it so we can give that time back.”
Google search
While some companies use artificial intelligence for individual projects, Google is focused on building AI into its core search technology.
“How important is AI to Google? Very,” said Geoffrey Hinton, a distinguished researcher at Google and a professor at the University of Toronto. “A lot of the problems Google needs to solve — to bring you the stuff you want to know about — are AI problems… In search, understanding what a document is saying is going to give you much better retrieval. Until a few years ago, image retrieval was done using text that described the image. To better retrieve images for you, the system needs to understand what the images are about — what’s in the images.”
For that, Google relies on artificial intelligence.
According to Hinton, that intense focus on AI research at companies like Google, and institutions like Carnegie Mellon, is resulting in significant progress in the field.
“Things are looking very positive,” he told Computerworld. “We’re beginning to solve problems a few years ago we couldn’t’ solve, like recognising images. We’re suddenly getting better at machine translation. That’s had a big impact on speech recognition and object recognition. That is closer to the core of Google because it involves understanding sentences, and if you can understand what a document is saying, you can do a much better search.”
Integrated AI
Lynne Parker, a professor at the University of Tennessee and a division director in Information and Intelligent Systems with the National Science Foundation, said many people still think artificial intelligence is a future technology, but they’re missing out on how integrated AI has become in the enterprise.
“For most companies, if there’s a technology that will help them do their jobs better and more efficiently, they just want it to be reliable, dependable and understandable. My guess is AI is not a scary term anymore.”
Carnegie Mellon’s Smith said the more enterprises delve into AI technology, the more AI will lose its mystique.
“That tech transition has always been a challenge. You kind of have to move in steps,” Smith said. “As users get more comfortable with these systems and see the decisions they’re making, they’ll see they’re not doing crazy things, and you’ll have the opportunity for better plans and better scheduling and you’ll be more productive.”
Sharon Gaudin, IDG News Service
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