techtarget

What is retrieval-augmented generation (RAG) in AI?

Retrieval-augmented generation (RAG) is an AI framework that retrieves data from external sources of knowledge to improve the quality of responses. This natural language processing (NLP) technique is ...
VentureBeat

Mistral launches new code embedding model that outperforms OpenAI and Cohere in real-world retrieval tasks

With demand for enterprise retrieval augmented generation (RAG) on the rise, the opportunity is ripe for model providers to offer their take on embedding models. French AI company Mistral threw its ...

Databricks adds adaptive search model to speed agent retrieval

In one test described by Databricks, Adaptive Instructed-Retriever verified that a company did not explicitly list ...
Forbes

Retrieval-Augmented Generation Is An Engineering Problem, Not A Model Problem

Every few months, the enterprise AI conversation resets around the same flawed premise that better models solve the problem. When large language models hallucinate, the instinct is to reach for a ...
VentureBeat

Table-augmented generation shows promise for complex dataset querying, outperforms text-to-SQL

AI has transformed the way companies work and interact with data. A few years ago, teams had to write SQL queries and code to extract useful information from large swathes of data. Today, all they ...
Forbes

RAGs To Riches: How Retrieval-Augmented Generation Is Changing Advertising

Artificial intelligence (AI) is revolutionizing digital advertising, enabling brands to deliver personalized and engaging experiences at scale. However, despite the advancements in generative AI, one ...