Genie Ontology aims to unify business definitions across systems, but analysts say data quality and governance will make or ...

Traditional machine learning in banking requires 3–4 months per use case: feature engineering, data labeling, model training, validation, deployment. Zero-shot inference on knowledge graphs eliminates ...

Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...

In his provocative X article, Matt Shumer, CEO of HyperWrite and OthersideAI, declares, "Every time someone asks me what's going on with AI, I give them the safe answer. Because the real one sounds ...

One of the biggest issues with large language models (LLMs) is working with your own data. They may have been trained on terabytes of text from across the internet, but that only provides them with a ...

Big data can revolutionize research and quality improvement for cardiac ultrasound. Text reports are a critical part of such analyses. Cardiac ultrasound reports include structured and free text and ...

Cyber situational awareness is critical for detecting and mitigating cybersecurity threats in real-time. This study introduces a comprehensive methodology that integrates the Isolation Forest and ...

In 2023, Idaho National Laboratory (INL) and Idaho State University unveiled the industry’s first near real-time digital twin of a nuclear reactor. The virtual replica of the 5-Wth AGN-201 research ...

Momentum is building for digital twins in semiconductor manufacturing, tying together the various processes and steps to improve efficiency and quality, and to enable more flexibility in the fab and ...

ABSTRACT: With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with ...