17min chapter

Generally Intelligent cover image

Episode 37: Rylan Schaeffer, Stanford: On investigating emergent abilities and challenging dominant research ideas

Generally Intelligent

CHAPTER

Exploring Model Collapse in Generative Models

This chapter examines the phenomenon of model collapse in large-scale generative models, highlighting recent research that addresses its significance and implications. It discusses the impact of data accumulation on model performance and error rates while exploring the complex relationship between synthetic data generation and training effectiveness. The chapter concludes with insights into model evaluation and the strengths and weaknesses of a specific cloud-based model used for research assistance.

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