A recent article in Technology Review introduces some cool technology from Lyric Semiconductor, a probability-based processor.
The electrical signals inside Lyric’s chips represent probabilities, instead of 1s and 0s. While the transistors of conventional chips are arranged into components called digital NAND gates, which can be used to implement all possible digital logic functions, those in a probability processor make building blocks known as Bayesian NAND gates. … Whereas a conventional NAND gate outputs a “1” if neither of its inputs match, the output of a Bayesian NAND gate represents the odds that the two input probabilities match. This makes it possible to perform calculations that use probabilities as their input and output.
Sounds like their initial impact will be in the flash memory market, making error-checking faster and more efficient. But I can definitely see how this kind of hardware could have a major impact in Machine Learning and Robotics. Most of statistical machine learning has its roots in the kind of math that this processor is designed for. This could make reasoning about larger (more real-world) problems increasingly feasible.