Ten AI concepts to know in 2026, including LLM tokens, context windows, agents, RAG, and MCP, for building reliable AI apps.

Image: John Tredennick, Merlin Search Technologies with AI. As law firms and legal departments race to leverage artificial intelligence for competitive advantage, many are contemplating the ...

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...

In " RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models," Bloomberg researchers found that RAG, a widely-used technique that integrates context from ...

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

Retrieval Augmented Generation (RAG) is supposed to help improve the accuracy of enterprise AI by providing grounded content. While that is often the case, there is also an unintended side effect.

Large language models (LLMs) continue to command a blazing bright spotlight, as the debut of ChatGPT captured the world’s imagination and made generative AI the most widely discussed technology in ...

NEW YORK – From discovering that retrieval augmented generation (RAG)-based large language models (LLMs) are less “safe” to introducing an AI content risk taxonomy meeting the unique needs of GenAI ...