While neural networks (also called “perceptrons”) have been around since the 1940s, it is only in the last several decades where they have become a major part of artificial intelligence.

Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the ...

Neural networks are the foundation of modern machine learning and AI. They are the most essential component in understanding what AI is and how it works. In this article, ...

Liquid neural networks may break this law to show that scale is not the whole story. A smaller model can be computed more efficiently. Also, ...

Using 19th-century math, a team of engineers revealed what happens inside neural networks they've created. The calculations are familiar.

In 1995, Powers published “Galatea 2.2,” his Pygmalion tale about training a neural network called Helen to take a graduate exam on Western literature.

Neural networks are great at fulfilling specific and well-constrained requests, but they can be overeager. Because a neural net's one directive is to produce an answer to a prompt, ...

This is because neural networks require extensive training for their inputs (such as pixels in an image) to produce the appropriate output (such as a description of the image).

You can't go out and just play through Doom right now with the support of a neural network. It is a test and not much more than that right now. Without touching on any ethical discussions of ...

University of California - Santa Barbara. "Energy and memory: A new neural network paradigm." ScienceDaily. ScienceDaily, 14 May 2025. <www.sciencedaily.com / releases / 2025 / 05 / 250514164320.htm>.