Navigating Training Limits in AI Development

This chapter explores the constraints of training duration in AI and the relevance of timing in project initiation. Using space exploration as an analogy, the discussion emphasizes the balance between rapid training steps and the value of each step, while addressing the critical issue of data movement bottlenecks. The conversation concludes with insights on scaling challenges, including latency concerns and automated recovery processes necessary to manage GPU failures effectively.