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

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...

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 ...

Confused by neural networks? This video breaks it all down in simple terms. Understand how they work and why they’re at the ...

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

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

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