Machine Learning

How a self-evolving AI learns to reflect, score, and rewrite its own reasoning

🧪 Summary

What if an AI could think not just solve problems, but reevaluate its beliefs in the face of new information?

In this post, we introduce a system that does exactly that. At the core of our pipeline is a lightweight scoring model called MR.Q, responsible for evaluating ideas and choosing the best ones. But when it encounters a new domain, a new goal, or a shift in task format, it doesn’t freeze it adapts.

Summary

This post provides a comprehensive guide to prompt engineering, the art of crafting effective inputs for Large Language Models (LLMs). Mastering prompt engineering is crucial for maximizing the potential of LLMs and achieving desired results.

Effective prompting is the easiest way to enhance your experience with Large Language Models (LLMs).

The prompts we make are our interface to LLMs. This is how we communicate with them. This is why it is important to understand how to do it well.