Unlike their more modern large language model counterparts, artificial neural networks require human input to learn and function. ANNs have been around since the 1950s. They started taking hold in ...

Nvidia’s latest pitch for the future of graphics is not about more polygons or higher memory bandwidth, it is about teaching ...

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research published in APL Machine Learning, I have used a phenomenon ...

Computing power has increased exponentially over the past few decades. We now have cameras on smartphones with incredible computational photography, voice assistants that respond near instantaneously, ...

Like a brain, a deep neural network has layers of neurons—artificial ones that are figments of computer memory. When a neuron fires, it sends signals to connected neurons in the layer above. During ...

Neural network approximation techniques have emerged as a formidable approach in computational mathematics and machine learning, providing robust tools for approximating complex functions. By ...

John J. Hopfield and Geoffrey E. Hinton received the Nobel Prize in physics on Oct. 8, 2024, for their research on machine learning algorithms and neural networks that help computers learn. Their work ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

ChatGPT has triggered an onslaught of artificial intelligence hype. The arrival of OpenAI’s large-language-model-powered (LLM-powered) chatbot forced leading tech companies to follow suit with similar ...