I Asked ChatGPT: Is it beneficial to train a LLM on its own prompted responses?
Answer:
Training a large language model (LLM) on its own responses is generally not recommended. Here's why:
Error Propagation: LLMs are not perfect. Reusing their own responses can amplify small errors or inaccuracies over time, leading to degraded performance.
Bias Reinforcement: LLMs may generate biased or unbalanced responses. Refeeding those back into the training process can solidify those biases, making the model less accurate or fair.
Reduced Diversity: Training on its own responses can narrow the diversity of information and perspectives the model learns from, making it less versatile and creative.
Instead, it's better to focus on high-quality, diverse, and human-generated data for training. This helps ensure the model remains robust and general-purpose.
