If you are interested in learning more about how to use Llama 2, a large language model (LLM), for a simplified version of retrieval augmented generation (RAG). This guide will help you utilize the ...

Much of the interest surrounding artificial intelligence (AI) is caught up with the battle of competing AI models on benchmark tests or new so-called multi-modal capabilities. But users of Gen AI's ...

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

Also: Make room for RAG: How Gen AI's balance of power is shifting For that reason, researchers at Amazon's AWS propose in a new paper to set a series of benchmarks that will specifically test how ...

A new study from Google researchers introduces "sufficient context," a novel perspective for understanding and improving retrieval augmented generation (RAG) systems in large language models (LLMs).

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.

A consistent media flood of sensational hallucinations from the big AI chatbots. Widespread fear of job loss, especially due to lack of proper communication from leadership - and relentless overhyping ...

Imagine asking a question to your favorite AI assistant, only to receive an outdated or incomplete answer.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 hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...