Significant work is underway in analog computing in the context of machine learning, machine intelligence, and biomimetic circuits, an important consideration as digital computers approach their efficiency limits, writes Columbia University professor Yannis Tsividis.
He notes one of his colleagues built an analog computer on a single chip, and more recently a Columbia team developed a second-generation single-chip analog computer.
"All blocks in our device operated at the same time, processing signals in a way that in the digital realm would require a highly parallel architecture," Tsividis says.
He notes the system uses power more efficiently and connects more easily with digital computers, offering analog for high-speed approximate computations and digital for high-speed programming, storage, and computation.
Tsividis cites the chip's circuit design for its ability to continuously compute arbitrary mathematical functions via analog-to-digital and digital-to-analog converters.
The chip's analog core supports direct interfacing with sensors and actuators, while its high speed enables real-time engagement with users in complex computations.
From IEEE Spectrum
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