Current approaches to deep learning are beginning ... and quickly learning new tasks. Similarly, such pre-trained models are often used to create embedding representations for various types of data, ...

In a study published in Nature Communications, researchers at the University of Wisconsin–Madison introduced a deep learning ...

Boosting digital rock images with AI-powered augmentation and quality analysis could improve subsurface engineering decisions.

S3 decouples RAG search from generation, boosting efficiency and generalization for enterprise LLM applications with minimal data.

Sid Probstein, CEO, SWIRL, led the Data Summit's session, 'Uncovering Data You Know is There But Can't Find,' exploring the ways in which LLMs can dramatically improve document retrieval.

The new platform will first focus on research around the root causes of autism, the Department of Health and Human Services said, and, in the long term, link data for research on other chronic ...

In recent years, the rapid evolution of deep learning technology has been applied to various machine vision tasks such as classification, detection, denoising, and super-resolution. In this study, a ...

These kernels leverage topic modeling and deep word embeddings to capture thematic and semantic information within textual data. Text kernels consider global and local semantics for text analysis ...

Pro Football Focus data helped determine the top 10 deep ball throwers for the 2025 college football season. Candidates had to be rostered on Power Four for the 2025 season and must have ...