Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

A hybrid approach to AI is powering Amazon’s Rufus shopping assistant and cutting-edge warehouse robots.

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 ...

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BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

Neural networks, from GPT-4 to Stable Diffusion, are built by wiring together perceptrons, which are highly simplified simulations of the neurons in our brains.

Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now the MIT spin-off is revealing several new ultraefficient models.

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Before transformers, neural networks had at most a few hundred million parameters; today, the largest transformer-based models have more than a trillion. Much of the improvement in language-model ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.