Master of Information and Data Science (MIDS) alums Beth McBride, Ishani Cheshire, Indri Adisoemarta, Chase Martin, and Ambro ...
Industrial AI may be all the rage, but it’s useless-to-dangerous without standardized, relevant data to work from. And yet, ...
GTM Bench scores LLMs and AI agents on real go-to-market work across two axes, how much of the job the system finishes and whether the output is groun ...
Learn how LLMs are transforming schema matching through semantic reasoning while deterministic validation keeps enterprise ...
AI models without strong business context risk costly errors, but vendor approaches to “context” vary. Enterprises must take ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
Prediction markets allow people to trade on the outcome of real-world events, from basketball games to elections. And trading volume on Kalshi and Polymarket – the two leading prediction markets – has ...
Abstract: Graph anomaly detection is a challenging task in graph data mining, aiming to recognize unconventional patterns within a network. Recently, there has been increasing attention on graph ...
Andrew Bloomenthal has 20+ years of editorial experience as a financial journalist and as a financial services marketing writer. Samantha (Sam) Silberstein, CFP®, CSLP®, EA, is an experienced ...
Schema.org is a collection of vocabulary (or schemas) used to apply structured data markup to web pages and content. Correctly applying schema can improve SEO outcomes through rich snippets.
Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather ...
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