Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

CATS-Net (Concept Abstraction and Task-Solving Network) is a comprehensive framework for understanding and implementing concept abstraction in neural networks. The system combines supervised learning ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

This transcript was created using speech recognition software. While it has been reviewed by human transcribers, it may contain errors. Please review the episode audio before quoting from this ...

Anthropic describes its new Opus 4.5 model as “intelligent, efficient, and the best model in the world for coding, agents, and computer use.” It follows Opus 4.1, which Anthropic released in August.

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...

Abstract: Dynamic Graph Neural Networks (GNNs) combine temporal information with GNNs to capture structural, temporal, and contextual relationships in dynamic graphs simultaneously, leading to ...

Abstract: The Just-In-Time defect prediction model helps development teams improve software quality and efficiency by assessing whether code changes submitted by developers are likely to introduce ...