The Open Questions Surrounding Open Source AI with Nathan Lambert and Keegan McBride
Scaling Laws
00:00
Exploring Open vs Closed AI Models
This chapter examines the distinctions between open-source and closed AI models, focusing on the essential components that define true openness. It highlights the complexities and debates surrounding openness in AI, including commercial incentives that deter companies from fully releasing their data. The discussion also contrasts the dynamics of open source AI development in China and the United States, shedding light on the shifting landscape and collaboration between industry and academia.
Transcript
Play full episode
