Solutions, a leading software company that is powering enterprise planning and decisioning models across 30-plus industry verticals with its groundbreaking Digital Brain platform, today announced the ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...
The release includes an embedded MCP server that exposes Spring project analytics to AI coding assistants, along with first-class support for Spring AI and automated property refactoring.
Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...
The new G-LIDE GBXH5600 models shed nearly 30 percent of their weight while keeping tide tracking, surf forecasts, fitness ...
Sales, a function that obviously runs on language, has been among the least changed by the technology built on language.
Telecom networks generate an enormous amount of operational data, and the people running them have spent years trying to make sense of it at scale. A modern 5G network exposes dozens of metrics per ...
One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...
Abstract: Burgeoning graph contrastive learning (GCL) stands out in the graph domain with low annotated costs and high model performance improvements, which is typically composed of three standard ...
Genomic prediction and design require models capable of integrating local sequence features with long-range regulatory dependencies. Nucleotide Transformer v3 (NTv3) is a multi-species genomic ...
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