Artificial intelligence and machine learning could become dramatically more efficient, thanks to a new type of computer ...

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 ...

The study shows how probabilistic clustering supports intelligent data transmission strategies. The authors propose leveraging cluster probabilities to define transmission rules: sensors with a high ...

The probabilistic approach to artifical intelligence has been responsible for most of the recent progress in artificial intelligence, such as voice recognition systems, or the system that recommends ...

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' ...

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: ...

Imagine a world where your computer doesn’t just work harder but smarter, tapping into the very chaos that surrounds us. It’s not science fiction—it’s the dawn of probabilistic and thermodynamic ...

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 ...