The researchers at Google have devised a new technique that could let a laptop or smartphone learn to do things better and faster over time. The researchers published a paper which focuses on a common problem. The prefetching problem. Computers process information much faster than they can pull it from memory to be processed. To avoid bottlenecks, they try to predict which information is likely to be needed and pull it in advance. As computers get more powerful, this prediction becomes progressively harder.
In the paper published, Google focuses on using deep learning to improve prefetching. “The work that we did is only the tip of the iceberg,” says Heiner Litz of the University of California, Santa Cruz, a visiting researcher on the project. Litz believes it should be possible to apply machine learning to every part of a computer, from the low-level operating system to the software that users interact with.
Such advances would be opportune. Moore’s Law is finally slowing down, and the fundamental design of computer chips hasn’t changed much in recent years. Tim Kraska, an associate professor at MIT who is also exploring how machine learning can make computers work better, says the approach could be useful for high-level algorithms, too. A database might automatically learn how to handle financial data as opposed to social-network data, for instance. Or an application could teach itself to respond to a particular user’s habits more effectively.
Paper reference: https://arxiv.org/pdf/1803.02329.pdf
(via: MitTechReview)
