Spent the last four months working with my team on training an AI model based on a decade of market research and analysis data. The model still needs significant refinement and calibration, but it's starting to show real promise.

Decided to test it with a practical question: what's the probability that Bitcoin has already topped within the current 4-year market cycle, given our assumptions? Fed it a set of specific parameters—market indicators, historical cycle patterns, on-chain metrics—and ran the analysis.

The results are interesting, though preliminary. There's a lot of tweaking ahead of us, but having a machine learning model work through this kind of probabilistic analysis on a 10-year dataset feels like we're onto something. The model is picking up patterns that would take forever to verify manually.

Still early days, but this is exactly the kind of tool traders and analysts need when trying to navigate Bitcoin's multi-year cycles. More updates as we fine-tune the model further.