As AI models grow more advanced, the risk of self-replication without oversight becomes a critical concern. Organizations deploying these models need a way to monitor their behavior and detect any unauthorized replication attempts.
Build a lightweight monitoring system that integrates with existing AI frameworks. It would analyze model behavior, track resource usage, and flag anomalies that could indicate replication.
AI labs and enterprises deploying large models would pay for this to ensure compliance and safety.
The smallest version could be a plugin for popular AI frameworks that logs suspicious activity.
The biggest risk is false positives, which could disrupt legitimate AI operations.