Over the last few years, the AI sector has been a competitive "bigger is better" race: larger models, more parameters, costly training runs, and enough energy consumption to power small cities.

A new technical paper titled “Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention” was published by DeepSeek, Peking University and University of Washington.

A Chinese AI company's more frugal approach to training large language models could point toward a less energy-intensive—and more climate-friendly—future for AI, according to some energy analysts. "It ...

Forbes contributors publish independent expert analyses and insights. Covering Digital Storage Technology & Market. IEEE President in 2024 Deepseek’s efficient AI training has caused much discussion ...

Just as machine learning, artificial intelligence, data modeling and analytics platforms have transformed manufacturing, drug discovery, health care and operations in a host of other industries, these ...

The growing popularity of generative AI, which uses natural language to help users make sense of unstructured data, is forcing sweeping changes in how compute resources are designed and deployed. In a ...