Part 3/7:
The Concept of Reflection Tuning
Reflection 70B departs from conventional methods of training AI models by incorporating "reflection"—the model's ability to recognize its mistakes and self-correct during inference. Schumer outlined that typical large language models (LLMs) often make an initial miscalculation and thereafter treat that error as fact. Unlike humans, who readily backtrack and amend mistakes, previous models lacked this self-correcting capability.
The innovative reflection tuning process helps the model to think more like a human. By structuring the training data to include conditions under which the AI could make errors and learn from them, the developers aimed for a more nuanced and reliable response system from the AI.