Hooks are modular, programmable extensions integrated into smart contracts that allow developers to insert and execute custom logic at predetermined points during a transaction’s lifecycle. These predetermined points, often referred to as hook points, act as checkpoints where specific actions can be triggered. This concept is similar to middleware or plugin systems in traditional software, where additional functionalities can be layered onto existing applications without altering their core logic. Hooks enable protocols to become more flexible, customizable, and interoperable, all without requiring significant overhauls of the core codebase.
Automated Machine Learning (AutoML) systems are an important part of the machine learning engineering toolbox. However, existing solutions often require substantial amounts of compute, and therefore extended running times, to achieve competitive performance.