Factories

Upgradeable Contracts Based on Machine Learning Output Supports contracts that can be updated based on insights derived from machine learning outputs, enabling dynamic responses to changing conditions or new data. Upgradeable contracts are designed to allow their logic or parts of their data storage to be changed post-deployment. This is particularly useful for AI-driven applications where the model might need to be updated as new data becomes available or as better algorithms are developed.

Example: A smart contract that uses a machine learning model to score credit applications could start with a simplified logistic regression model. Over time, as more data is collected and analyzed off-chain, the model could be upgraded to a more sophisticated neural network. This upgrade can be facilitated through a proxy contract or a similar upgradeable pattern, where the address pointing to the logic contract can be updated to a new one containing the improved AI model.