DeepMind's ATLAS: Revolutionizing Multi-lingual LLM Scaling

Google DeepMind's ATLAS framework provides a groundbreaking approach to understanding how to scale 大语言模型 (LLMs) across multiple languages! This research offers a new perspective on training multi-lingual models, considering the complex interplay between model size, data volume, and language relationships.

• •ATLAS introduces a 'cross-lingual transfer matrix' to understand how training on one language affects others.
• •The research reveals that positive language transfer is correlated with shared writing systems and language families, such as Scandinavian languages.
• •The study also provides insights on when it's more efficient to fine-tune versus pre-train LLMs based on available resources.