Your question is Distributed Training at Scale. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How would you design a distributed training pipeline for a multi-billion parameter model across thousands of accelerators?
Discuss the end-to-end system, including data ingestion, parallelism strategy, accelerator communication, checkpointing, evaluation, observability, and recovery from failures. Make reasonable assumptions where details are unspecified, and explain the tradeoffs among throughput, convergence, reliability, and cost.