AI hallucination occurs when models generate confident but factually incorrect information..Hallucinations arise from probabilistic text generation rather than true understanding or factual verification..Large language models predict patterns, which can fabricate plausible yet entirely incorrect responses..Lack of real time data grounding increases hallucination risks in dynamic information environments..Domain specific gaps in training data significantly raise error rates in specialized queries..Hallucinations can mislead users in critical fields like healthcare, law, and finance..Retrieval augmented generation reduces hallucinations by grounding outputs in verified external data..Fine tuning and reinforcement learning improve accuracy but cannot fully eliminate hallucinations..Human oversight remains essential for validating high stakes AI generated information..Read more stories..Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp