Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been developed by a RIKEN neuroscientist and his collaborator. In addition to shedding ...

Blending ‘old-fashioned’ logic systems with the neural networks that power large language models is one of the hottest trends ...

If you are curious and want to learn how does AI work, well, follow our detailed explainer on Artificial Intelligence's ...

A major AI architecture. A neural network is employed for many pattern recognition applications; however, its most popular use is the creation of language models used by ChatGPT, Gemini and other ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex, age, state where they live and ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

A deep neural network (DNN) is a system that is designed similar to our current understanding of biological neural networks in the brain. DNNs are finding use in many applications, advancing at a fast ...