The article also clarifies a Hugging Face issue where a user asked for two components of Yi-34B to be renamed for compatibility with third-party codebases developed for Llama 2. The authors argue that such compatibility issues are common in open source releases and do not indicate any nefarious intent or dependency of 01.AI on Llama to train their model. They conclude by emphasizing that the similarities between Yi-34B and Llama 2 do not support the argument that Chinese AI firms simply rely on American open models, as all LLMs have extremely similar architecture.
Key takeaways:
- The article refutes claims that Chinese startup 01.AI's large language model Yi-34B is fundamentally indebted to Meta’s Llama 2, arguing that all modern large language models are made from the same algorithmic building blocks, and that the architectural differences between Llama 2 and the original 2017 Transformer were not invented by Meta.
- The authors argue that the similarities between Yi-34B and Llama 2 do not support the argument that Chinese AI firms simply rely on American open models, as all large language models have extremely similar architecture.
- The article explains that the main differentiator between large language models is the training data used, and in this regard, 01.AI developed and described their own English-Chinese dataset, while Meta disclosed no useful details about their data sources.
- The authors conclude by emphasizing that 01.AI followed standard industry practices in developing Yi-34B, and that the company had to solve the same problems as other language model training companies, including building out a data processing pipeline and model pretraining infrastructure from scratch.