Artificial intelligence has traditionally been developed through a process that separates training from deployment. Engineers collect data, design architectures, train models using massive computing resources, and then release the trained system into real-world applications. Once deployed, the model generally remains static until a new version is trained. However, in recent years researchers have begun exploring…