In the race to build bigger and more powerful AI systems, organizations are discovering that simply adding more GPUs isn’t the golden ticket to faster results. While GPU clusters with thousands—or even hundreds of thousands—of chips offer unparalleled computational power, they also introduce a formidable challenge: synchronization and checkpointing. This blog explores why checkpointing is critical for AI training, why it becomes exponentially more challenging as GPU clusters grow, and how Clockwork’s innovative solution transforms this bottleneck into an opportunity for efficiency and cost savings. Why is Checkpointing a Requirement for AI Training? Training a modern AI model relies on […]