想象 a hospital sending every patient straight to the operating theatre. It may work, but it is expensive, slow, and wasteful.
AINNA NeuralOps applies the same logic through 分段, 智能路由, and 分离式系统.
Each instruction is divided into smaller tasks, then routed to the most efficient layer:
Simple tasks go to rules, parsers, databases, or PHP/Python microservices.
Only complex reasoning is sent to an AI model.
This can potentially reduce unnecessary GPU and token usage by 75% to 80%, depending on the workflow.
The ESG impact is equally important:
环境: 更低 energy use and carbon footprint.
社会: More affordable AI for 中小企业.
治理: Better control, auditability, and predictable execution.
分段 the work. 路线 intelligently. Use AI only where it creates real value.
#AINNANeuralOps #SmartRouting #分离式系统 #可持续AI #ESG #GreenAI
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我特别喜欢on the wor 80%这一部分，内容没有把实施过程说得太简单。
我会把simple tasks go to rules这一段分享给需要了解技术的同事。
这篇内容让我更容易理解为什么depending on the workflow值得关注。
视觉和结构让AINNA neuralops applies的概念更容易掌握。
这篇文章对想象 a hospital sending every的解释很清楚，实际操作的重点也很容易理解。