A neural network is a computational machine-learning model that follows the structure of the human brain. It consists of networks of interconnected nodes or neurons to process and learn from data, run ...

Youngsters who once built things, played games, and read books are now immersed in one-dimensional, passive tidbits of ...

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. Neural networks are the ...

Researchers have developed a new tool to more precisely guide cancer treatment. Described in a paper published in Nature ...

In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models.

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 ...

Neural networks usually run on electronics, but Caltech researchers are pushing boundaries by building networks out of DNA molecules . Instead of using digital signals, these molecular systems compute ...

Understanding the brain's functional architecture is a fundamental challenge in neuroscience. The connections between neurons ultimately dictate how information is processed, transmitted, stored, and ...