AI models have absorbed enormous amounts of information from across the internet. But what happens when some of that information is wrong?

Jonathan Schaeffer (AI Researcher and Founder of Kind AI) explains that large language models are trained on Wikipedia, books, research papers, public websites, commercial databases, and other online sources. More training data can improve AI performance, but not every source is equally trustworthy.

When ChatGPT or another AI model pulls information from an unreliable source, that material can become part of a confident, convincing answer. This is one reason AI hallucinations and factual errors remain difficult to eliminate.

Can AI ever become completely reliable when its training data comes from an unreliable internet?

➡️Watch Full Episode here: https://youtu.be/SXGkW7e_rbc

👉 Follow for ChatGPT, AI training data, large language models, AI hallucinations, generative AI, data quality, and artificial intelligence.

#ChatGPT #AITrainingData #LargeLanguageModels #AIHallucinations #GenerativeAI #DataQuality #ArtificialIntelligence #LLM #AIAccuracy #AIErrorReport