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Next-generation database reduces AI hallucinations and improves accuracy by 78%

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 ...
VentureBeat

AWS debuts advanced RAG features for structured, unstructured data

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Getting enterprise data into large language models (LLMs) is a critical ...

KAIST: "Improving Data Processing Accuracy and Speed, Key to Overcoming Barriers to Enterprise AI Adoption"

Artificial Intelligence (AI) agents based on Retrieval-Augmented Generation (RAG) technology are rapidly proliferating. RAG ...
Mirage News

KAIST Unveils Database Tech Cutting AI Errors by 78%

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination" — the generation of ...
dbta

Memgraph’s Atomic GraphRAG Speeds Up the Use of Graph-Based RAG Across Multiple Data Sources

Memgraph, a leader in open-source, in-memory graph databases, is introducing a new capability designed to accelerate business adoption of graph-based retrieval-augmented generation (GraphRAG), Atomic ...
dbta

Recognizing the Power of Graph Databases and Knowledge Graphs

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...