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 ...

Large language models (LLMs) like OpenAI’s GPT-4 and Google’s PaLM have captured the imagination of industries ranging from healthcare to law. Their ability to generate human-like text has opened the ...

Large Language Models (LLMs) demonstrate considerable potential in enhancing the retrieval of health information. However, the hallucinatory they produce poses a security challenge. This study aimed ...

We introduce ChronoQA, a benchmark dataset for Chinese question answering focused on evaluating temporal reasoning in Retrieval-Augmented Generation (RAG) systems. Built from over 300,000 news ...

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.

RAG allows government agencies to infuse generative artificial intelligence models and tools with up-to-date information, creating more trust with citizens. Phil Goldstein is a former web editor of ...