The new paradigm of computational economics is taking shape.

Imagine a fully coordinated supply chain system — edge nodes, GPU clusters, and cloud resources no longer operate independently, but as a unified execution layer working in harmony. This is not just a technological upgrade, but a restructuring of the economic framework.

How to achieve this? Through a combined approach of parallelized EVM and hybrid inference stack:

**Edge Layer** handles fast, low-latency lightweight model tasks, reducing network round-trip by being close to the user; **Cloud and GPU Providers** focus on compute-intensive inference work, leveraging hardware advantages; **L1 Layer** ensures a trust foundation by anchoring and verifying decision hashes — all critical computational results are traceable and verifiable.

The core is the invisible **Scheduler**, which spans heterogeneous computing environments, coordinating workload distribution, execution, and result aggregation like a central nervous system.

The significance of this architecture lies in: retaining the speed advantage of edge computing, harnessing the deep computing power of centralized cloud resources, and ensuring a decentralized trust mechanism through blockchain L1. The three are no longer in competition but are complementary — the democratization of computing is truly beginning.