Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...
As agentic and RAG systems move into production, retrieval quality is emerging as a quiet failure point — one that can ...
When developing machine learning models to find patterns in data, researchers across fields typically use separate data sets for model training and testing, which allows them to measure how well their ...
Distributed database consistency models form the backbone of reliable and high-performance systems in today’s interconnected digital landscape. These models define the guarantees provided by a ...
Artificial intelligence (AI) is transforming a variety of industries, including finance, manufacturing, advertising, and healthcare. IDC predicts global spending on AI will exceed $300 billion by 2026 ...
Giant AI data centers are causing some serious and growing problems – electronic waste, massive use of water (especially in arid regions), reliance on destructive and human rights-abusing mining ...
How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in ...
Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI models. Unlike generative diffusion models, the team's Discrete Spatial ...
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