Analysis
This research explores a fascinating new approach to prompt engineering, adding mathematical axioms to a Large Language Model to enhance its Inference capabilities. The results demonstrate that by giving a model a structured way of thinking, the quality of its answers and its reasoning processes can be dramatically improved. It's a promising development for making LLMs even more insightful!
Key Takeaways
- •Adding mathematical axioms to Claude's system prompt significantly improved the depth of its responses.
- •The enhanced Claude used the axioms to inform its Inference but avoided using the axioms' terminology in its answers.
- •A comparison tool is available, allowing anyone to test the impact of the added axioms.
Reference / Citation
View Original"If a model is given a 'way of seeing'—that is, an axiomatic system for structurally grasping problems—then the quality of the Inference itself changes."