Imagine 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 logik through Segmentation, Smart Routing, and Sistem Berasingan.
Each instruction is divided into lebih kecil 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:
Persekitaran: Lower energy use and carbon footprint.
Sosial: Lagi affordable AI untuk PKS.
Tadbir Urus: Better control, auditability, and predictable execution.
Segment the work. Route intelligently. Use AI only where it creates real value.
#AINNANeuralOps #SmartRouting #DetachedSystems #MampanAI #ESG #GreenAI
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เพิ่งเคยเห็นคนเขียนเรื่อง75%แบบตรงไปตรงมา
Sent this to two people already. depending on the workflow is why.
The bit about AINNA neuralops applies is what I keep coming back to.
Clearer than the vendor decks I get about by 75% to 80%.
The framing around simple tasks go to rules is better than I expected.