🧠 Thought Experiment: Designing the Self-Evolution (Meta-Learning) Logic

[anhmtk]

##💡Vision: Beyond Session Counting
Currently, StillMe's evolution is primarily session-based.To achieve the true "Self-Evolving" goal outlined in the README,we need a more sophisticated mechanism: Meta-Learning.
We need the community's help to design this architecture.
##❓Core Architectural Questions
1.Evolution Metric: How should we measure evolution?Would measuring Knowledge Retention and Accuracy Score be better metrics than session counting?
2.Feedback Mechanism: How should the Meta-Learning Agent autonomously adjust learning parameters?E.g., if accuracy is low,should it decrease the TRUST_SCORE of the data source?
3.Vector DB Integration: Once we integrate a Vector DB (as planned),can we use Vector metrics(e.g., dispersion of embeddings)to assess the quality of newly acquired knowledge?
##🚀Call to Action:
We invite data scientists,AI researchers,and engineers to share their insights.Let's collectively shape StillMe's autonomous future!