Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...

Cramming AI into your deterministic operating model Is a recipe for failure.

A new digital system allows operations on a chip to run in parallel, so an AI program can arrive at the best possible answer ...

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 ...

What Is A Probabilistic Model? A probabilistic model is a statistical tool that accounts for randomness or uncertainty when predicting future events. Instead of giving a definitive answer, it ...

Uncertainty is an intrinsic part of neural computation, whether for sensory processing, motor control or cognitive reasoning. For instance, it is impossible to determine with certainty the age of a ...

Future events are far from certain in the business world. This is especially true for smaller businesses, which tend to have more volatility than larger organizations, or newer businesses without a ...

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 ...

Humans live in a world of uncertainty. A shadowy figure on the sidewalk ahead could be a friend or a mugger. By flooring your car’s accelerator, you might beat the train to the intersection, or maybe ...

The World Science Festival's panel on Probability and Risk started out in an unusual manner: MIT's Josh Tennenbaum strode onto a stage and flipped a coin five times, claiming he was psychically ...