The recent O'Reilly Strata + Hadoop World Conference focused on big data analytics and its positive effect on artificial intelligence (AI) research, advancing the state of the art for tasks such as ad targeting and personalized assistance. However, scientists are no closer to achieving an overall general AI, in the sense that a computer can behave like a human, says Salesforce.com's Beau Cronin.
Cronin says the state of AI has always been difficult to measure because a system may excel in a specific area but fall short in another, similar task. He notes many current AI research projects are designed for commercial rather than academic endeavors. "Deep learning on its own, done in academia, doesn't have the [same] impact as when it is brought into Google, scaled, and built into a new product," he says.
However, Cronin says AI methods are now being integrated into commercial services and products faster than ever before. He notes big data has helped AI research by introducing inferencing and other statistical methods.
"A lot of new innovation has come around in deep learning that has been rolled out in scale, like Google image search," says Polynumeral's Juan Pablo Velez. "But the research is very much tied to the agendas of big companies and it doesn't necessarily mean we are any closer to generalized machine intelligence."
From IDG News Service
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