Apple is unto its massive general improvement as it hires its new and first research director, Ruslan Salakhutdinov. Indeed, Apple is getting serious about artificial intelligence.
Salakhutdinov has been working on some pretty intense AI research. He primarily researches deep learning and neural networks, where computers learn from a large pool of examples. Carnegie Mellon is at the forefront of this field of research, but Salakhutdinov's research takes it a step farther -- he's trying to figure out how to get AI to learn from raw data.
This is called "unsupervised learning." Typically, learning algorithms are fed annotated data; their learning is at least partially supervised. This "holy grail" is going to be tricky to accomplish, but Salakhutdinov has the chops. Since 2009, Salakhutdinov published at least 42 papers on machine learning.
According to a Tweet from Salakhutdinov, he's going to be maintaining his position at Carnegie Mellon. He also posted an Apple job listing seeking research scientists for his new department.
According to the company, Apple's A.I. will not be technology for the sake of hiring the man. The company is always in its pursuit to protect your privacy while it brings convenience. Although, there are some who say Apple is late to this party, they are wrong. The evolutoin of machine intelligence is going to take time and while first stage machine intelligence is already transforming lives (for good and for ill) those who claim victory in that race today should simmer down a little; this industry's barely left the starting grid, the finishing line is some way ahead.
Salakhutdinov primarily researches deep learning and neural networks, where computers learn from a large pool of examples...but Salakhutdinov's research takes it a step farther -- he's trying to figure out how to get A.I. to learn from raw data.
Academically, Salakhutdinov is an associate professor at Carnegie Mellon University in Pittsburgh. His primary task is to help the company make sure that Siri and its other products make use of the fundamental breakthroughs coming out of academic A.I. research.
Salakhutdinov's work on cutting-edge machine-learning techniques could drive progress in A.I., and could be applied in different areas, including computer vision, natural language processing, and even robotics.
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