If you wanted to build a system that could drive a car, instead of programming it directly you might attach a sufficiently advanced neural network to its sensors and controls, and then let it ...

Artificial intelligence is largely a numbers game. When deep neural networks, a form of AI that learns to discern patterns in data, began surpassing traditional algorithms 10 years ago, it was because ...

This step-by-step breakdown of the process allows a neural net to build more sophisticated models—which in turn should lead to more accurate predictions. The layer approach has served the AI ...

Today, almost all types of AI, including those used to build large language models and image recognition systems, include sub-networks known as a multilayer perceptron (MLP).

Stable Diffusion (from Stability AI) and Imagen, both released in 2022, used variations of an architecture called a convolutional neural network (CNN), which is good at analysing grid-like data ...

This approach provides stable, expressive, and computationally efficient predictions without overly restrictive conditions on the model parameters. The work is available on the arXiv preprint server.

Fly-brain connectome helps to make predictions about neural activity It has been unclear how to build simulations of entire neural circuits with only measurements from a dead fly’s brain.