AI hallucinations produce confident but false outputs, undermining AI accuracy. Learn how generative AI risks arise and ways to improve reliability.

Phil Goldstein is a former web editor of the CDW family of tech magazines and a veteran technology journalist. The tool notably told users that geologists recommend humans eat one rock per day and ...

Large language models are increasingly being deployed across financial institutions to streamline operations, power customer service chatbots, and enhance research and compliance efforts. Yet, as ...

Artificial intelligence is a deep and convoluted world. The scientists who work in this field often rely on jargon and lingo to explain what they’re working on. As a result, we frequently have to use ...

A lot of focus around reducing hallucinations has been applied during the training of a large language model (LLM), or when it is learning from data. But to mitigate hallucinations, GSK instead ...

Over the last few years, businesses have been increasingly turning to generative AI in an effort to boost employee productivity and streamline operations. However, overreliance on such technologies ...

Humans are misusing the medical term hallucination to describe AI errors The medical term confabulation is a better approximation of faulty AI output Dropping the term hallucination helps dispel myths ...

An international database tracking artificial intelligence hallucinations in legal documents reveals California leads the nation, followed by Texas and Florida. If ever there was support for attorney ...

Who are they trying to convince? The ostensibly unthinking and unfeeling LLM this is directed at? What possible motivation could a (one presumes) motivation-free LLM have for being helpful, or not ...

Hallucinations are unreal sensory experiences, such as hearing or seeing something that is not there. Any of our five senses (vision, hearing, taste, smell, touch) can be involved. Most often, when we ...