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

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

Machine learning algorithms begin with training data and create models that capture some of the patterns and lessons embedded in the data. Reinforcement learning is part of the training process ...

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.

Sheelam’s solution deploys layered deep learning agents that can anticipate network ... convolutional neural networks (CNNs), long short-term memory (LSTM) models, and reinforcement learning to ...

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, ...

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 ...