From Facts to Fallacies: Deciphering LLM Hallucinations

4 min read

blue and white striped textile

Imagine asking a language model a straightforward question about climate change, expecting a concise and factual answer backed by scientific data. But instead, the model goes off the rails, spouting blatantly incorrect or nonsensical information. Welcome to the enigmatic and increasingly common issue known as Large Language Model (LLM) hallucinations. This phenomenon is as intriguing as it is unsettling, a curious blend of technological prowess and fallibility. You’re not alone if you’ve encountered this bewildering experience. In fact, it’s an issue that experts are becoming increasingly concerned about, especially as LLMs are deployed in more critical applications. As we grow…...

This article is free to read

Login to read the full article


By subscribing to our main site, you will also be subscribed to DDIntel - our regular letter showcasing our featured articles and applications.

Manas Joshi Manas is a seasoned senior software engineer at Microsoft, where he leverages his expertise in AI and ML to enhance large scale backend systems used by millions of people everyday globally. He was a founding member of Bing Shopping Experiences, where he lead and designed numerous projects, imprinting a lasting mark with his innovative approaches. He has published award winning research paper during his work at Microsoft. Now, at Bing Maps, he is the driving force behind efforts to revolutionize navigation technology, working tirelessly to improve user experiences globally. Beyond his primary full time role, Manas embodies a philanthropic spirit, founding FullVision AI, a non-profit aimed at making glaucoma detection both accessible and affordable through AI-enhanced visual field tests.