Agents2h ago
Apple Proposes Environment-Free Synthetic Data for Agents
Apple researchers developed a method to generate API-calling trajectories using LLMs as digital world models. This approach removes the need for executable APIs or pre-populated backend databases during training. By relying solely on API specifications, developers can scale training data without building complex environments. This streamlines the pipeline for creating stateful AI agents.