A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

DRL, which fuses the strengths of deep learning and reinforcement learning, is increasingly used to support the core ...

Digital systems are expected to navigate real-world environments, understand multimedia content, and make high-stakes ...

As next-generation mobile networks grow more complex, high-density 5G environments are placing enormous pressure on co ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...

Learn More. Deep learning is a subset of machine learning that uses neural networks with multiple layers to model complicated patterns and representations in data. It excels at tasks like image ...

Deep Learning, and Foundation Models. If you’ve ever wondered how these terms are related, and what sets them apart, you’ll be pleased to know that we’re about to demystify it all.

From machine learning and deep learning to generative AI and natural language processing, different types of AI models serve various use cases—for example, automating tasks, developing better ...

In the concept of deep learning, the computer learns to perform on the basis of direct data feed such as image, text or sound. Such models are capable of achieving super accurate results and ...