Summary:
- This article discusses a new technique called "Fault-Tolerant LLaMA Training" developed by researchers at Anthropic.
- The technique allows for training large language models (LLMs) like LLaMA with simulated hardware failures, without the need for checkpoints, to make the models more robust and reliable.
- The researchers were able to train LLaMA on a cluster of 40 GPU servers, simulating over 2,000 hardware failures every 15 seconds, and the model was still able to complete the training successfully.