In the era dominated by Large Language Models (LLMs) and the forthcoming age of Artificial General Intelligence (AGI), the concept of "agents" is evolving to represent more complex processes. This shift underscores the imperative for a specialized operating system (OS) tailored for agents. AgentOS is designed to cater to this need, focusing on enhancing efficiency, scalability, and user-friendliness.
The premise of AgentOS extends beyond the facilitation of individual AI agents; it's about unlocking the potential for emergent phenomena that arise from the complex interplay and collaboration of countless agents. This system is the bedrock upon which the unpredictable, yet highly potent, outcomes of agent interactions can be explored and harnessed.
- Modular integration of various techniques such as LoRA, quantization, batching, paged attention, and more, facilitating continuous improvement and adaptation.
- Compatibility with a diverse range of LLMs, enabling AgentOS to operate seamlessly across different platforms, akin to how operating systems run on various hardware.
- User-friendly APIs that mirror the simplicity and functionality of system calls, streamlining the development process for agents.
- Comprehensive support for plugin development, analogous to driver support in operating systems, encouraging innovation and customization.
- Launch a basic agent to validate the core functionalities of AgentOS.
- Scale up by running multiple agents, leveraging state-of-the-art (SOTA) serving systems for enhanced performance and integration.
- Introduce system calls (syscalls) tailored for agent development, streamlining the creation and deployment process.
- Implement a plugin system to foster innovation and extend capabilities, encouraging community-driven enhancements and versatility.