Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

In 2014, Ian Goodfellow introduced Generative Adversarial Networks (GANs), a revolutionary AI concept pitting two neural networks against each other. One network creates images, while the other ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

There are many stories of how artificial intelligence came to take over the world, but one of the most important developments is the emergence in 2012 of AlexNet, a neural network that, for the first ...

Sometimes in the rush to explore our interactions with neural nets (often in the form of LLMs) we forget to think about our own operating system and how it works. Of course, scientists did spend a lot ...

For years, one of the simplest explanations for human intelligence was also one of the biggest: the human brain has an enormous number of neurons. It also has an even more enormous web of connections ...

Forbes contributors publish independent expert analyses and insights. Philip Maymin, a professor of analytics and AI, covers finance and AI. Is this a deep learning neural network, with blue inputs, ...