Generative AI tools such as ChatGPT are increasingly utilized, but they face significant challenges due to 'hallucination', leading to the creation of inaccurate outputs. The blending of these AI models with Retrieval Augmented Generation (RAG) offers a solution by incorporating reliable data from trusted sources. This integration allows for more accurate responses while reducing the risk of hallucination. By summarizing specific documents and providing citations, users can check validity and context, fostering greater trust in AI-generated answers.
Generative AI solutions like ChatGPT face challenges with hallucination, causing fear in professionals, especially when it comes to legal cases with fictitious filings.
RAG integrates GenAI with trusted data to minimize hallucinations, enabling users to obtain more reliable answers while providing links and citations for verification.
The combination of reliable content sources with Generative AI technologies leads to systems that are less prone to errors and hallucination, enhancing trustworthiness.
What if ChatGPT could search the internet for answers, providing citations and employing chain of thought reasoning to strengthen its responses?
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