Android Police

Neural Networks: Everything you need to know

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 ...

Key Technical Points for Learning Artificial Intelligence: Parallel Computing and Acceleration Techniques for Neural Networks

Therefore, parallel computing and acceleration techniques have become crucial in the research and application of neural networks, as they can significantly enhance the performance and efficiency of ...
InfoWorld

The most popular neural network styles and how they work

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 ...
Nature

Explainability Methods for Deep Learning Neural Networks

Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved remarkable ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

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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Supervised Learning Achieved in DNA Winner-Take-All Neural Networks

Can a neural network be constructed entirely from DNA and yet learn in the same way as its silicon-based brethren? Recent breakthroughs indicate that the answer is affirmative, with a molecular ...
VentureBeat

10 years later, deep learning ‘revolution’ rages on, say AI pioneers Hinton, LeCun and Li

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Artificial intelligence (AI) pioneer ...