Understanding AI Hallucinations and Data Quality

This chapter explores the phenomenon of hallucinations in AI models, where outputs can be coherent yet factually incorrect. It emphasizes the importance of quality training data and tailored datasets specific to industries to enhance accuracy. Additionally, the discussion covers techniques like data reduction and the role of machine learning in improving data analysis within IT operations.