We have now successfully built our own AINNA智能体.
The next step is already in progress: distilling our own language model, with the long-term goal of running a lightweight AINNA SLM directly on Android and iPhone devices.
This is where our direction becomes much bigger than simply building another AI assistant.
We believe the phone can eventually evolve from a device that only runs apps into a personal AI server - handling local inference, private memory, automation, identity, storage and device control.
And once each phone becomes an intelligent node, the next layer becomes possible.
想象 millions, and eventually billions, of phones communicating securely with one another. 大 workloads could be divided across trusted devices, processed collectively, 已验证 and combined again.
Instead of everything depending on:
电话 → 互联网 → 数据 中心 → AI → 电话
the future could increasingly operate as:
电话 → 本地 AI → Trusted P2P 网络 → 云 only when necessary.
This could reduce dependence on centralized data centres for many everyday workloads. 计算, storage and AI processing could increasingly move toward local, edge and distributed infrastructure.
数据 centres will still remain important for large-scale training, critical 系统 and high-availability workloads. But they may no longer need to process every small task generated by billions of devices.
The bigger vision goes even further.
The phone could eventually become the AI control plane for the physical world.
Cars, homes, CCTV, appliances, machines, robots and IoT devices may no longer require dozens of separate user-facing applications. They only need secure interfaces that your personal AI can understand and control.
The intelligence stays closer to the individual.
We have built the agent.
We are now working on distilling the model.
The SLM is only the beginning.
The destination is a decentralized personal intelligence infrastructure.
一人一AI,一节点,连接亿万。
#AINNA #AgenticAI #SLM #LocalAI #EdgeAI #DistributedAI #P2P #AIInfrastructure #NeuralOps #FutureOfAI



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关于distilling our own language model的实际落地部分最吸引我。
关于automation, identity, storage and device的风险和限制还可以再展开,不过基础说明已经很好。
这篇文章把homes, CCTV, appliances, machines, robots讲得比一般的AI介绍更具体。
难得有人把critical 系统 and high-availability workloads讲得这么直白。
我对edge and distributed infrastructure.数据 centres还有问题,但文章已经提供了很好的起点。
收藏了,主要是为了计算, storage and AI processing。