Key advances in the development of artificial neural networks came from psychologists seeking to understand how the human mind works.

Explore how core mathematical concepts like linear algebra, probability, and optimization drive AI, revealing its pattern-recognition capabilities.

The strength of certain neural connections can predict how well someone can learn math, and mildly electrically stimulating these networks can boost learning, according to a study published in the ...

Abstract: There has been significant recent work on solving PDEs using neural networks on infinite dimensional spaces. In this talk we consider two examples. First, we prove that transformers can ...

Computations can be performed in parallel at very high speeds only limited by the speed of light. However, so far, there have been two significant challenges: Firstly, realizing the necessary complex ...

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks. Artificial intelligence ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.