As CMOS technology reaches the nanoscale level, researchers are looking at 'noise' and other perturbations. And some of them at the Georgia Institute of Technology have taken advantage of this 'noise' ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

The techniques for evaluating the probabilistic properties of systems having identical operational and spare units with different facilities for repairs are discussed in this paper. The important ...

Researchers at the Georgia Institute of Technology announce energy savings by a factor of more than 500 in simulations with their ultra energy efficient embedded architecture based on Probabilistic ...

A DARPA-funded processor start-up has made bold claims about a new kind of processor that computes using probabilities, rather than the traditional ones and zeroes of conventional processors. Lyric ...

Understanding the differences between probabilistic and deterministric AI will help manufacturers make more informed choices and achieve measurable results.

Richie Etwaru, Co-founder & CEO of Mobeus, is an evangelist for the probabilistic math revolution and a pioneer in emerging technologies. I’ve spent decades building software. Early on, it was simple: ...

Richie Etwaru, Co-founder & CEO of Mobeus, is an evangelist for the probabilistic math revolution and a pioneer in emerging technologies. For most of business history, systems followed deterministic ...

In the 1950s and '60s, artificial-intelligence researchers saw themselves as trying to uncover the rules of thought. But those rules turned out to be way more complicated than anyone had imagined.