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At Open Source Summit Europe 2026 in Prague, openKylin presented a plan to move Linux from merely hosting AI applications to helping AI understand intent, call operating-system capabilities and coordinate tasks. The proposal centers on a unified AI runtime, a system-agent execution environment and Linux support for AI-focused RISC-V hardware.
What openKylin announced in Prague
Open Source Summit Europe ran from October 7 to 9, 2026, in Prague, Czechia. openKylin’s post-event account says Executive Director Liu Min delivered the October 8 main-forum keynote, From AI Runtime to System Agents: Reimagining Linux for the AI Era with openKylin.
There is a discrepancy in the project’s official event records. An earlier preview listed the same keynote for October 8 from 09:25 to 09:35 local time at the Prague Congress Centre, but named Wu Qingbo, chairman of the openKylin Technical Committee, as the speaker. The preview and post-event report should therefore be treated as separate records rather than silently combined.
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From “AI on the OS” to “AI for the OS”
openKylin’s central argument is that large models are moving into desktop environments, so the operating system should become an active participant in AI workflows. The project contrasts two approaches:
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| Dimension | Standalone AI applications | openKylin’s stated direction |
|---|---|---|
| Integration depth | AI operates inside individual applications. | Agents can understand user intent and access system capabilities. |
| Architecture | Each application builds its own AI integration. | A unified runtime exposes operating-system functions as tools callable by agents. |
| Task handling | The user moves between separate applications and assistants. | A system-agent environment coordinates tools and intelligent tasks. |
| Hardware reach | Conventional desktop targets dominate. | The roadmap includes RISC-V desktops, vector extensions and heterogeneous computing. |
| Ecosystem model | Development is centered on an individual application or project. | Operating-system, processor, edge-AI, research and international open-source partners collaborate. |
| Evidence maturity | Capabilities vary by application. | The summit materials document a roadmap and demonstrations, not production-scale deployment. |
The unified AI runtime
The proposed runtime is a common layer for AI integration. Instead of every program inventing a separate interface to system functions, the runtime would present those functions in a form agents can discover and call. In practical terms, that could give an agent a consistent way to work with desktop services, hardware resources and other operating-system tools.
openKylin presented this as infrastructure rather than a single assistant application. The goal is to reduce fragmented integrations and make system capabilities available to multiple agents and workloads.
The system-agent execution environment
The second element is an execution environment in which agents can invoke operating-system tools and coordinate multi-step tasks. This is the difference between an assistant that answers a question inside one application and an agent that can use several system capabilities to complete an objective.
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The presentation describes the intended architecture; it does not establish that every proposed capability is already available in a stable openKylin release.
RISC-V and the hardware demonstrations
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Li Jianfeng’s lightning talk addressed the hardware and software work needed to make RISC-V desktops suitable for AI workloads. Topics included hardware enablement, optimization for vector extensions, integration with the AI runtime and heterogeneous computing, in which different processing units share a workload according to their strengths.
This matters because an agent-oriented operating system needs more than a model interface. It also needs efficient access to CPU, accelerator and memory resources on a range of architectures. The talk presented that work as an ongoing direction rather than a published performance result.
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SpacemiT K3
SpacemiT presented its K3 processor, ecosystem progress and software frameworks for AI-computer and AI-robot scenarios. At the booth, the K3 ran openKylin 3.0 and supported on-device AI demonstrations. The combination showed how the project’s runtime ideas could be paired with a RISC-V platform without requiring every demonstration to depend on a remote service.
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openKylin 3.0 AI PCs
The booth also displayed AI PCs powered by openKylin 3.0, alongside partner demonstrations. These systems illustrated the project’s effort to position AI features as part of the desktop platform, not only as optional software installed above it.
The partners behind the demonstrations
The official event report names KylinSoft, SingNova Singapore, Haihe Laboratory and SpacemiT as partners. Their demonstrations covered different parts of the proposed stack:
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- SingNova Singapore: AI edge-computing applications for video processing, desktop intelligence and digital-human interaction.
- Haihe Laboratory: a RISC-V-centered virtual-reality experience.
- SpacemiT: the K3 processor, related software frameworks and on-device AI running with openKylin 3.0.
- openKylin and KylinSoft: the operating-system platform and its AI-PC demonstrations.
openKylin also described a closed-door exchange with Thierry Carrez of the Linux Foundation and the OpenAtom Foundation. Discussion topics included global ecosystem building, cross-border developer collaboration, AI-era governance and future community and industrial cooperation. That meeting indicates that the project is treating governance and international participation as part of its AI strategy, not merely as administrative concerns.
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The summit provides concrete evidence of demonstrations, partner participation and a technical roadmap. It does not provide benchmark results, production deployment figures or adoption statistics for the unified runtime or system-agent environment.
- The K3 booth demonstration confirms that openKylin 3.0 ran on that processor in an event setting.
- The RISC-V lightning talk confirms work on enablement, vector optimization, runtime integration and heterogeneous computing.
- The AI-PC displays show hardware and software integration at the showcase level.
- No published figures in the event materials establish performance, reliability, security boundaries or broad user adoption for system agents.
For developers, the immediate significance is architectural: openKylin is proposing common interfaces between agents and Linux capabilities. For users, the eventual benefit would depend on whether those interfaces become stable, permission-aware and easy to control in ordinary desktop releases.
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Why the summit setting matters
The Linux Foundation’s account of the Prague event placed openKylin’s announcement alongside discussions of open AI and data, digital trust, safety-critical software, cloud-native orchestration, embedded Linux and related infrastructure. The foundation reported more than 40 million lines of code and described Linux as marking 35 years. Its CEO, Jim Zemlin, summarized the open-source premise: “The world’s most important technology is built in the open.”
That context helps explain openKylin’s emphasis on shared runtimes and cross-project cooperation. If AI agents are allowed to act through an operating system, developers will need common interfaces, clear authority boundaries and community oversight across distributions, hardware vendors and model frameworks.
What to watch next
The next meaningful milestones are not additional booth concepts but working software that developers can install, inspect and test. Signs of progress would include a documented runtime API, permission and sandboxing rules for agent tool calls, reproducible RISC-V builds, published performance measurements and evidence that applications can adopt the same interfaces without bespoke integration.
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Until those details are published, openKylin’s appearance at Open Source Summit Europe 2026 is best understood as a well-defined direction: Linux should expose its capabilities to intelligent agents through a common runtime, while extending that model to RISC-V and heterogeneous AI hardware.
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