This research introduces a novel framework that uses Large Language Models to intelligently manage computing resources across edge and cloud environments based on user intentions.

• Automates resource allocation decisions by translating high-level user intents into specific computing requirements
• Bridges the gap between edge devices (IoT) and cloud computing for optimal performance
• Creates more efficient distributed computing systems for real-time AI applications
• Addresses key challenges in managing diverse and complex computing environments

For engineering teams, this approach represents a significant advancement in how distributed computing resources can be managed, potentially reducing complexity while improving performance for time-sensitive applications.

IntentContinuum: Using LLMs to Support Intent-Based Computing Across the Compute Continuum