TikTok video by 60 Minutes

Hiroshi Ishii and the Tangible Media Group at the MIT Media Lab have pioneered new ways for people to interact with computers.

Acclaimed keyboardist Jordan Rudess’s collaboration with the MIT Media Lab culminated in a live improvisation between an AI "jam_bot" and the artist.

In het kort Recente studies van OpenAI en MIT Media Lab onthullen een interessant verband tussen onze interacties met ChatGPT en gevoelens van eenzaamheid. Onderzoekers analyseerden meer dan 40 miljoen ChatGPT-conversaties en ondervroegen gebruikers in beide onderzoeken. Hieruit bleek dat hoe meer tijd mensen doorbrachten met ChatGPT, hoe eenzamer ze zich voelden. Invloed van persoonlijke […] The post ChatGPT & Eenzaamheid: Vergroten AI-gesprekken het gevoel van eenzaamheid? appeared first on Newsmonkey.

The MIT Media Lab’s finding that 95% of generative AI investments have produced no measurable returns highlights a familiar pitfall: Leaders are repeating the mistakes of the digital transformation er...

Joi Ito, head of the MIT Media Lab, talks about his book "Whiplash," the singularity, technology, capitalism, change, complexity, and systems thinking.

Foundation Models that are capable of processing and generating multi-modal data have transformed AI's role in medicine. However, a key limitation of their reliability is hallucination, where inaccurate or fabricated information can impact clinical decisions and patient safety. We define medical hallucination as any instance in which a model generates misleading medical content. This paper examines the unique characteristics, causes, and implications of medical hallucinations, with a particular focus on how these errors manifest themselves in real-world clinical scenarios. Our contributions include (1) a taxonomy for understanding and addressing medical hallucinations, (2) benchmarking models using medical hallucination dataset and physician-annotated LLM responses to real medical cases, providing direct insight into the clinical impact of hallucinations, and (3) a multi-national clinician survey on their experiences with medical hallucinations. Our results reveal that inference techniques such as Chain-of-Thought (CoT) and Search Augmented Generation can effectively reduce hallucination rates. However, despite these improvements, non-trivial levels of hallucination persist. These findings underscore the ethical and practical imperative for robust detection and mitigation strategies, establishing a foundation for regulatory policies that prioritize patient safety and maintain clinical integrity as AI becomes more integrated into healthcare. The feedback from clinicians highlights the urgent need for not only technical advances but also for clearer ethical and regulatory guidelines to ensure patient safety. A repository organizing the paper resources, summaries, and additional information is available at https://github.com/mitmedialab/medical hallucination.