WIRED spoke with DeepMind’s Pushmeet Kohli about the recent past—and promising future—of the Nobel Prize-winning research ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...

In this video, we will look at the details of the RNN Model. We will see the mathematical equations for the RNN model, and ...

GPUs, born to push pixels, evolved into the engine of the deep learning revolution and now sit at the center of the AI ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures, allows ...

This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here. The problem is in the sparsification which is claimed to ...

Abstract: Deep learning is a powerful technique for data-driven learning in the era of Big Data. However, most deep learning models are deterministic models that ignore the uncertainty of data. Fuzzy ...