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Posits, a New Kind of Number, Improves the Math of AI

Back in 2017, John Gustafson, then jointly appointed at A*STAR Computational Resources Centre and the National University of Singapore, and Isaac Yonemoto, then at Interplanetary Robot and Electric Brain Co., developed a new way of representing numbers. These numbers, called posits, were proposed as an improvement over the standard floating-point arithmetic processors used today.

Now, a team of researchers at the Complutense University of Madrid have developed the first processor core implementing the posit standard in hardware and showed that, bit-for-bit, the accuracy of a basic computational task increased by up to four orders of magnitude, compared to computing using standard floating-point numbers. They presented their results at last week’s IEEE Symposium on Computer Arithmetic.