Machine Learning Analogies
Dylan compares machine learning models to compilers and discusses the importance of labeled datasets as the analog of a general-purpose programming language. Data augmentation is highlighted as a method to encode desired properties in prediction models, emphasizing the explicit encoding of desired behaviors.In this clip
From this podcast
Generally Intelligent
Episode 10: Dylan Hadfield-Menell, UC Berkeley/MIT, on the value alignment problem in AI
Related Questions