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

The most appreciative advancements in statistical AI, the ones with the most meaning and potential to improve data’s worth to the enterprise, are deep learning deployments of computer vision and ...

“The goal was to learn as much as we can from unlabeled data.” In addition, he said, traditional language learning systems “compress all that meaning for a single word into a single vecto ...

Because deep learning is the most general way to model a problem, it has the potential to solve difficult problems—such as computer vision and natural language processing—that outstrip both ...

Deep learning-based software is already being integrated into virtual worlds; some examples include autonomously driving chatbots and other forms of natural language processing to ensure seamless ...

For this reason, many language scientists—including Noam ... GPT-3, arguably the most well-known of these models, is a gigantic deep-learning neural network with 175 billion parameters.

Deep-learning A.I. is the machine learning technology that powers everything from cutting-edge natural language processing to machine vision tools. It may also be powering climate change — as a ...