The machine-learning programs that underpin their ability to “see” still have blind spots—but not for much longer ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: ...

A team at Carnegie Mellon University is helping kids understand artificial intelligence with a soft, squishy, LED-lit neural ...

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 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 ...

Neural networks are algorithmic systems created based on the principle of the human nervous system. They consist of many interconnected neurons that process information in several layers. Each neuron ...

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 ...