THE HITCHHIKER'S GUIDE TO TRAINING ON COMPUTE ISLANDS

Summary from the TLDR AI newsletter

Being able to train reliably on multiple smaller clusters widens the usable training pool for frontier training. A single run could mix accelerator generations and vendors as each island runs on its own schedule. Older generations or less common chips could also participate in a frontier run. One risk with this model is that integrity and safety may become harder when models are trained across providers, as one faulty or compromised site can quietly degrade or tamper with models in ways that are harder to trace.