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Model Fine-Tuning

    Challenges
    Challenges
    Updated on 05 Nov 2025

    Building a large-scale Japanese LLM required extensive computational resources and a flexible infrastructure to support multi-node, multi-phase training. JAIST faced long training cycles, unpredictable infrastructure demands, and a small research team without access to large in-house GPU clusters. They needed a scalable, managed AI infrastructure that could handle complex workloads while allowing researchers to focus on model development instead of system operations.