Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...
Spread the love“`html 1. Understanding MySQL and Its Importance MySQL is one of the most popular relational database management systems (RDBMS) in the world, powering countless applications ranging ...
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Paytm's Prism AI: India's No 2 global breakthrough in enterprise text-to-SQL ushers in the age of autonomous data intelligence
In a landmark moment for Indian artificial intelligence, fintech leader Paytm has developed Prism, a proprietary ...
Flatiron Telescope uses AI and transparent SQL to turn real-world evidence into quick turnaround oncology research and ...
Google Cloud Summit came to London last week, and we took the opportunity to sit down with database execs Sailesh Krishnamurthy (VP engineering) and Yasmeen Ahmad (product executive Agentic Data Cloud ...
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 ...
Prequel is a SQL query engine built in C#. The goal of this project is to demonstrate how query engines are built, and to bring a query engine to the .NET community. The project contains a ...
ESDS Software Solution Limited strengthens its enterprise security offering with Enlight Jatayoo — a purpose-built Database Activity Monitoring platform that gives organisations across BFSI, ...
Abstract: Keyword search in relational databases allows the users to query these databases using natural language keywords, bridging the gap between structured data and intuitive querying. However, ...
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