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 ...

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 ...

Neo4j Aura Agent is an end-to-end platform for creating agents, connecting them to knowledge graphs, and deploying to ...

While Large Language Models (LLMs) like LLama 2 have shown remarkable prowess in understanding and generating text, they have a critical limitation: They can only answer questions based on single ...

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 ...

A recent paper published in the journal Engineering delves into the future of artificial intelligence (AI) beyond large language models (LLMs). LLMs have made remarkable progress in multimodal tasks, ...

The latest trends in software development from the Computer Weekly Application Developer Network. The original title in full for this piece is: From Better Reasoning to Faster QFS, An LLM Just Can’t ...

Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...