Data and Creativity
Laura discusses the potential for language models to generate novel information by learning causal mechanisms from diverse data. Yannic challenges the notion of hitting a "data wall," arguing that the focus should be on creating interesting data rather than simply increasing quantity. Together, they explore how scaling data could enhance model intelligence and the importance of selecting diverse datasets for effective learning across various tasks.In this clip
From this podcast
Machine Learning Street Talk (MLST)
How Do AI Models Actually Think? - Laura Ruis
Related Questions