newOS adopts the standards of the Agent Graph Trust Protocol (AGTP), an open-source standard for agent-to-agent sharing of learning signals for distributed, trusted reinforcement learning from our own AI research lab.

We are entering the Era of Experience in artificial intelligence. This marks a significant shift from AI systems that primarily learn from static, human-generated data to a new generation of agents that learn and evolve through dynamic interactions, continuous feedback, and rich contextual experiences. As AI pioneer David Silver notes,

"experience will become the dominant medium of improvement and ultimately dwarf the scale of human data used in today's systems."

In this new era, AI agents will not just process information but will actively experience the digital and physical worlds. They will inhabit streams of interaction, act autonomously, and learn from the consequences of their actions, grounded in real-world signals rather than solely human pre-judgment. This transition is crucial for moving beyond the limitations of current human knowledge and achieving superhuman capabilities in various domains.

To unlock the full potential of this experiential wave, a robust framework is needed—one that allows diverse AI agents to securely and meaningfully share, interpret, and learn from these experiences. Without such a framework, valuable experiential learning remains siloed, hindering collective progress.

Ask newOS about AGTP, or read more about our research and how to implement AGTP standards here.