In artificial intelligence, a hallucination refers to an output generated by an AI model that appears confident and factual but is actually false or unsupported by real data. This phenomenon often occurs in large language models and generative systems when they fill gaps in knowledge or misinterpret training information. Hallucinations can take the form of incorrect facts, fabricated sources, or unrealistic images, depending on the AI application. They highlight one of the biggest challenges in AI development—ensuring reliability, accuracy, and verifiable outputs. Researchers and developers use techniques like model fine-tuning, retrieval-augmented generation, and human oversight to reduce hallucinations and build more trustworthy systems.
Opera today introduced Neon, an AI-powered browser that can run tasks and navigate pages autonomously — aiming to shift web browsing from passive to “agentic.”
OpenAI’s next version of its Sora video generator will default to including copyrighted content unless owners explicitly opt out – drawing criticism from media creators.
OpenAI introduces ChatGPT Pulse, a proactive feature delivering daily updates and suggestions directly in the app, positioning it as a potential challenger to social media feeds.
AI search startup Perplexity has reportedly raised $200 million at a $20 billion valuation, just two months after a $100 million round – signaling its rapid rise as a major rival to Google.