Researchers challenge the "efficiency" theory of the brain, showing that neurons become more coordinated and share more information as learning occurs.

Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and Keras.Growing demand for AI profes ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a ...

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 ...

A two-chip photonic neuromorphic system performs real time spiking reinforcement learning using only light, achieving ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

Examining brain plasticity and its implications for development, aging, and brain injury recovery.

As AI systems have advanced rapidly, with large language models (LLMs) at the center, every tech executive has experienced their limits—when AI systems struggle with complex problem-solving, produce ...

Microsoft unveils AI-powered DirectX upgrades at GDC 2026, including neural rendering features, new ML tools, and DXR 2.0.