ADELPHI, Md.-- Army researchers discovered a way to quickly get information to Soldiers in combat using new machine learning techniques. The algorithms will play a significant role in enhancing ...

Training a machine learning algorithm to accurately solve complex problems requires large amounts of data. Previous articles in this series discussed an exascale-capable machine learning algorithm and ...

By 2014, Facebook had a machine learning algorithm, DeepFace, that could match images of faces to a person with over 97% accuracy, which approaches the performance of a typical human when it comes ...

The research reveals that although some users frame the gig economy as a space of freedom, income flexibility, and ...

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

Traditional machine learning algorithms, dataframe operations like groupby-aggregations, joins, and timeseries manipulation. Data ingestion like CSV and JSON parsing. And array computing like ...

These algorithms have evolved from early theoretical constructs into practical solutions that underpin modern cloud infrastructures, the Internet of Things (IoT) and even machine learning deployments.

The newly-open sourced Distributed Machine Learning Toolkit features fast, parallelized, and easy-to-deploy machine learning algorithms Topics Spotlight: AI-ready data centers ...

That’s why Amini focuses on algorithms for individualized learning and decision-making within the larger infrastructure. His recent paper on distributed sensing platforms for distributed machine ...

When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system Article Publication Date 18-Jun-2024 ...