A recent study published in Engineering presents a novel framework named ERQA (mEdical knowledge Retrieval and Question-Answering), which is powered by an enhanced large language model (LLM). This ...

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform ...

In the age of AI, enterprises want to drive critical internal functions with large language models (LLMs). They are investing millions, but bringing those use cases to life – with ROI – is far from ...

A practical overview of security architectures, threat models, and controls for protecting proprietary enterprise data in retrieval-augmented generation (RAG) systems.

Researchers from China and Singapore proposed AURA (Active Utility Reduction via Adulteration) to protect GraphRAG systems ...

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.

Imagine asking a question to your favorite AI assistant, only to receive an outdated or incomplete answer. Frustrating, right? Large Language Models (LLMs) are undeniably powerful, but they have a ...

The hallucinations of large language models are mainly a result of deficiencies in the dataset and training. These can be mitigated with retrieval-augmented generation and real-time data. Artificial ...

As IT-driven businesses increasingly use AI LLMs, the need for secure LLM supply chain increases across development, ...