We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision programs.

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 ...

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

What if we could peer into the brain and watch how it organizes information as we act, perceive, or make decisions? A new ...

“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 ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Using lab-grown brain tissue, researchers uncovered complex patterns of neural signaling that differ subtly between healthy ...

Neural Concept aims to accelerate these timelines by integrating AI directly into CAD and physics-based simulation ...

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...