Building a Self-Improving Orchestration Layer for IoT Dashboards
The article discusses the development of the Hermes Agent, an orchestration layer designed for IoT dashboards. It highlights how Hermes Agent improves upon traditional AI agents by incorporating a closed-loop learning system and a three-layer memory architecture. This innovation allows for more efficient management of decentralized data nodes and enhances the integration of IoT sensor data.
- ▪Hermes Agent features a built-in closed-loop learning system that allows it to remember and reuse successful workflows.
- ▪The agent employs a three-layer memory architecture, which includes working memory, episodic memory, and procedural memory.
- ▪Hermes Agent decouples orchestration logic from model providers, allowing flexibility in execution environments.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3780777) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Bibhu Pradhan Posted on May 26 Building a Self-Improving Orchestration Layer for IoT Dashboards #hermesagentchallenge #devchallenge #agents #iot Hermes Agent Challenge Submission: Write About Hermes Agent This is a submission for the Hermes Agent Challenge: Write About Hermes Agent When mapping out the future roadmap for AirSense AI, the primary goal was to evolve the hyper-local air quality intelligence dashboard by integrating data directly from physical IoT sensors in specific…
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