Large Language Model Training

Large language model (LLM) training focuses on efficiently and reliably developing increasingly powerful models using massive datasets and computational resources. Current research emphasizes optimizing distributed training algorithms (like data, tensor, and pipeline parallelism) and mitigating bottlenecks such as communication overhead and memory limitations through techniques like compression, near-storage processing, and efficient communication topologies. This field is crucial for advancing AI capabilities, impacting various applications while also driving innovation in high-performance computing and addressing challenges related to data quality, copyright, and environmental sustainability.