“We’re working at pushing the boundaries of what’s possible, and that’s very exciting.”
In his role with Xerox research, Julien has been able to follow an unconventional approach for a research scientist — working in a multi-disciplinary team focused on business needs, while also conducting basic research. It has, he says, provided an ideal platform for discovery.
For as long as people have been interested in creating artificial intelligence, they’ve naturally been drawn to the prospect of teaching machines to read — sensing that when computers master language, they’ll finally have access to the full sweep of human knowledge.
Even Mary Shelley’s novel Frankenstein, published almost two centuries ago, reaches a turning point when the monster discovers a cache of books, and learns about human emotions and behavior.
In reality, however, enabling artificial intelligence so that devices can read and understand written text remains an important, but elusive goal. At Xerox Research Centre Europe, Julien Perez is part of a team of machine learning scientists leading the chase.
“From the very beginning of AI,” Julien says, “scientists had good reason to believe that the day machines mastered text would be a clear milestone on the road to machine intelligence.”
True machine reading, he explains, goes far beyond analyzing and categorizing text, as most search engines do today. It’s about actually grasping meaning.
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