We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

A new technical paper titled “Deep-learning atomistic semi-empirical pseudopotential model for nanomaterials” was published ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

DeepSeek has introduced a new architecture, Manifold-Constrained Hyper-Connections (mHC), designed to enhance the efficiency and reliability of training large AI models.

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...