We are in an exciting era where AI advancements are transforming professional practices. Since its release, GPT-3 has “assisted” professionals in the SEM field with their content-related tasks.

The problem: Generative AI Large Language Models (LLMs) can only answer questions or complete tasks based on what they been trained on - unless they’re given access to external knowledge, like your ...

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.

Knowledge graph startup Diffbot Technologies Corp., which maintains one of the largest online knowledge indexes, is looking to tackle the problem of hallucinations in artificial intelligence chatbots ...

Wikidata has built the semantic web backbone supporting knowledge cards in popular engines. Now, it's extending this foundation using a vector database to enhance its existing knowledge graph and ...

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

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...

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

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...