On July 31, 2026, the “Xinsuan Fusion · Empowering Industry — Heterogeneous Compute Driving Large Model Application Deployment” exchange was held in Suzhou under the guidance of the Suzhou Industrial Park Administrative Committee, jointly organized by Suzhou Yige Technology and H3C Industrial Internet. Voices from government, chips, cloud platforms and intelligent manufacturing gathered around one industry-level question: how can the value of large models be truly realized in the physical world. Xu Lixian, CEO of Zhuming Technology, delivered a keynote titled AI Runtime — Bringing AI from the Cloud into the Physical World, offering a systems-level answer from the infrastructure layer.
01 · OLD PARADIGM vs NEW PARADIGM
Not an iteration, but a wholesale revolution
Enterprises, vehicles, satellites and robots — the endpoints of the physical world are becoming AI-enabled across the board, and the main battleground for AI is extending from data centers to the wider physical world. Over the past year, “deployment” has been the most frequent keyword in the AI industry, yet as AI reaches factory floors, rail corridors and satellite telemetry sites, a clear gap remains between “capability” and “value.”
The root of this gap is neither chip supply nor model capability, but the limits of the traditional operating-system architecture: born in well-resourced, controlled central machine rooms, it cannot self-iterate in resource-constrained, network-volatile, long-unattended physical sites.
OS (cloud / desktop / device)
- Cross-generation hardware compatibility
- Reflex-arc decision mechanism
- Federated scheduling across domains
- Built-in zero-trust security
- Immune-grade self-healing
APP + AI Native Runtime
- System interpretability
- Compute-aware routing
- Multi-agent consensus
- Intent-driven interaction
- Continuous evolution and accumulation
Facing the intelligence revolution, the traditional OS cannot complete its own self-iteration. What the physical world needs is a Runtime environment built on AI Native principles — this is a revolution in which the traditional OS will gradually harden into a long tail.
02 · CENTRAL & PERIPHERAL NERVOUS SYSTEM
Central nervous system and peripheral nervous system
Around the AI Runtime Infrastructure, Zhuming Technology has built a runtime system that spans cloud, edge and device. Analogous to the human nervous system, it separates into a central nervous system (AI) and a peripheral nervous system (BASIC):
Central nervous system · AI Runtime.A
Responsible for intelligent decision-making and command. It manages activities we can deliberately control, enabling compute, models, tasks and devices to deliver fast instinctive reactions and intelligent decisions on intelligent endpoints.
AI Runtime.A (decision layer)
- Cross-generation hardware compatibility — abstracting differences upward, unifying scheduling downward
- Reflex-arc decision mechanism — autonomous detection, isolation, recovery and memory
- Federated scheduling — unified cloud-edge-device coordination
- Built-in zero-trust security — component-level signatures, security built into the system
- Immune-grade self-healing — rapid reset of security state
Peripheral nervous system · AI Runtime.BASIC
Responsible for the activities we cannot directly control but that sustain the system — like heartbeat, breathing and digestion. This corresponds to PiiOS, the immutable base operating system, providing a unified system foundation for compute nodes of different forms.
AI Runtime.BASIC (runtime layer)
- Immutable base — system integrity, secure operation
- Real-time capability — time-sensitive, continuous execution
- Controlled update and recovery — version evolution, fault recovery
- Confidential computing — runtime-state protection for sensitive workloads
- Component-level signature — integrity and trusted startup
03 · NEW OBJECTIVES
Five objectives of AI Runtime
This architecture targets five clear objectives, moving AI from “deployable” toward “truly usable”:
- Decisions that are observable and traceable, with no audit blind spots — every scheduling decision verifiable
- Ask what outcome you need, not where the compute is — pooled compute, transparent invocation
- Local group decisions without centralized command — edge autonomy, local reaction
- Describe in language, let the system execute — intent-driven, automatic orchestration
- Continuously optimize its own models and system — accumulated evolution, self-iteration
04 · PRODUCT MAPPING
From revolution to a deliverable product system
Built around “PiiOS (BASIC) + PiiEngine/PiiHive (AI) + PiiIron (hardware)”, Zhuming Technology has formed a complete product system:
PiiOS
Immutable Base Operating SystemProvides the unified runtime foundation for the peripheral nervous system, carrying system integrity, secure operation, real-time capability, controlled update and recovery
PiiEngine
Enterprise AI EngineOrganizes compute, models, tasks and AI applications for the enterprise center; as the central nervous system it supports virtualization, cloud-native, AI compute and agents running together
PiiHive
Edge AI Computing PlatformDeployed at edge sites, extending compute scheduling, real-time operation, local inference, edge autonomy and remote evolution into industrial internet and intelligent field scenarios
PiiIron
Hardware Product PortfolioProvides tiered hardware carriers and integrated software-hardware delivery for enterprise-grade, desktop-grade and lightweight edge deployment needs
05 · DELIVERY AND ECOSYSTEM
Delivery capability and ecosystem collaboration
These capabilities are not roadmap commitments; they are delivery capabilities already in production. Zhuming Technology’s solutions have already been deployed for real customers in high-reliability industries such as power, rail transit and commercial space, where disconnected autonomy and real-time response have been exercised under field conditions.
Zhuming Technology is among the providers that have connected compute-scheduling infrastructure “from the data center to the physical world.”
Ecosystem collaboration is key to amplifying capability. At this exchange, the collaboration between Zhuming Technology and Yige Technology drew particular attention: Yige Technology focuses on domestic high-end FPGA chips and heterogeneous computing systems, and its EagleSys K1 heterogeneous all-in-one machine provides a solid compute foundation for AI inference; Zhuming Technology’s AI Runtime builds the scheduling and control layer on top of it. This collaboration can be summarized as fitting AI with a “spinal reflex arc” — Yige supplies a strong “torso” (heterogeneous compute), while Zhuming supplies acute “nerve reflexes” (Runtime scheduling), enabling AI on physical endpoints to deliver fast instinctive reactions and intelligent decisions.
06 · EVALUATION REFRAMED
The evaluation system is shifting from “peak compute” to “system effectiveness”
During the “AI Inference Efficiency and Large-Scale Deployment Path” roundtable, Xu Lixian, CEO of Zhuming Technology, joined guests from H3C Industrial Internet, Yige Technology, Qili Semiconductor and the Institute of Computing Technology to discuss how heterogeneous compute can land across industries.
An important consensus emerged: the evaluation system for AI deployment is shifting from “peak compute” to “system effectiveness” — end-to-end latency, deployment cycle, operational stability and total cost of ownership are becoming the core metrics in enterprise procurement decisions.
Infrastructure truly built for production has to answer performance, real-time behavior, security, reliability and lifecycle management at the same time. That is exactly where AI Runtime starts — not single-point performance optimization, but systems-level engineering.
NEW STAGE · INFRASTRUCTURE
Bringing intelligence truly into the physical world
The AI industry is moving from “model-capability competition” into a new stage of “infrastructure competition.” As the focus shifts from “how big the model is” to “whether AI can run stably, efficiently and economically in the real world,” the strategic value of Runtime infrastructure is being re-recognized.
From cloud models to field execution, the path in between is not a simple deployment but a runtime chain that runs through compute, models, tasks, systems and devices. Zhuming Technology will keep refining its product and technology system from enterprise centers to edge sites and intelligent devices, supporting AI workloads as they enter real business and physical environments in a stable, secure and continuous way.
The electrical age had the power grid, the information age had the internet, and the intelligence age needs Runtime infrastructure that lets AI compute flow freely — so that AI compute, like water and electricity, reaches every corner of the physical world.
About Zhuming Technology
Zhuming Technology builds runtime infrastructure for AI production and the physical world, connecting enterprise data centers, edge sites and intelligent devices, and coordinating compute, models and tasks across cloud, edge and device