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At the IEEE International Electron Devices Meeting, IBM unveiled a 8-bit analog chip with phase change memory. Abu Sebastian, the lead researcher for the project, says that in-memory calculations are a key to the efficiency of the chip. Instead of storing a single bit of information like a traditional memory cell, the variable resistance of a phase change memory cell can be used to store and access data right on the chip. A recent breakthrough allows the phase-change cells to reliably retain data when they are being read, which the researchers call a "key innovation".
The researchers tested a single-layer neural net on an 8-bit chip composed of 30 phase-change memory devices to identify pictures of the digits 1, 0, and 4, and achieved 100 percent classification accuracy. While premature, Sebastian estimates the advance could potentially bring some 100 to 1,000-fold gains in power savings to future devices, compared to traditional computing. Precision was sought in traditional computing, but with artificial intelligence, there is now an opposite trend. IBM is also reporting a digital chip today that operates at 8-bits while maintaining accuracy in neural net training. That models more closely to the human brain, which often can draw correct conclusions from little information. IBM's vice-president for research Jeff Welser likens this to looking out a foggy window and seeing a blurry person walking toward your house. "As soon as you recognize your mom, it doesn't matter how low-precision the image is,” says Welser. “You’ve got the right information you need."
The researchers tested a single-layer neural net on an 8-bit chip composed of 30 phase-change memory devices to identify pictures of the digits 1, 0, and 4, and achieved 100 percent classification accuracy. While premature, Sebastian estimates the advance could potentially bring some 100 to 1,000-fold gains in power savings to future devices, compared to traditional computing. Precision was sought in traditional computing, but with artificial intelligence, there is now an opposite trend. IBM is also reporting a digital chip today that operates at 8-bits while maintaining accuracy in neural net training. That models more closely to the human brain, which often can draw correct conclusions from little information. IBM's vice-president for research Jeff Welser likens this to looking out a foggy window and seeing a blurry person walking toward your house. "As soon as you recognize your mom, it doesn't matter how low-precision the image is,” says Welser. “You’ve got the right information you need."