Smart Software and Old School Technology
August 22, 2018
It feels strange to say that anything analog is a trend in artificial intelligence, but that certainly seems to be the case in one segment. According to reports, there’s actually a way for AI to get faster and more accurate by indulging in some old timey thinking. We learned more from a recent Kurzweil article, “IBM Researchers Use Analog Memory to Train Deep Neural Networks Faster and More Efficiently.”
According to the story:
“IBM researchers used large arrays of non-volatile analog memory devices (which use continuously variable signals rather than binary 0s and 1s) to perform computations. Those arrays allowed the researchers to create, in hardware, the same scale and precision of AI calculations that are achieved by more energy-intensive systems in software, but running hundreds of times faster and at hundreds of times lower power…”
This is an intriguing development for AI and machine learning. Next Platform took a look at this news as well and found: “these efforts focused on integrating analog resistive-type electronic memories onto CMOS wafers, they also look at photonic-based devices and systems and how these might fit into the deep learning landscape.” We’re excited to see where this development goes and what companies will do with greater AI strength.
Patrick Roland, August 22, 2018
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