Why Training Open-Source LLMs on ChatGPT Data is Problematic
Analysis
The Hacker News article likely points out concerns regarding the propagation of biases and limitations present in ChatGPT's output when used to train other LLMs. This practice could lead to a less diverse and potentially unreliable set of open-source models.
Key Takeaways
- •Training on ChatGPT output can propagate biases inherent in the model.
- •The resulting open-source models may be less diverse or novel.
- •This practice undermines the goals of open-source LLM development.
Reference
“Training open-source LLMs on ChatGPT output is a really bad idea.”