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In recent years The Linux Foundation Networking launched a set of Open Source Networking "Super Blueprints" that outline architectures for common networking use cases and are built using OSS technology. Those blueprints consists of collections of OSS projects and commercial products, integrated together by the open source community and documented for free use by any interested party. Several of these blueprints started incorporating AI technologies and we expect that trend is expected to accelerate, as existing blueprints inspire additional AI-driven solutions. One promising area is intent-based network automation. There is current work on blueprints that use NLP and LLM to translate user intent, expressed in natural spoken language to network requirements, and generate full network configuration based on those requirements. Such approach can significantly simplify existing network operation processes, and enable new automated services that can be directly consumed by the end users in an automated manner, commonly known as Network-as-a-Service (NaaS).
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Experience with OSS in other domains shows that whenever there is an OSS technology that powers commercial products or offerings, there is a need to validate the products to make sure they are properly using the OSS technology and are ready to serve the end users use in a predictable manner. Such validation/verification programs have existed for a while as part of OSS ecosystems . They are often created and maintained by the same OSS community that develops the OSS projects themselves. for a while. The Cloud Native Computing Foundation (CNCF) has a successful "Certified Kubernetes" program that helps vendors and end users ensure that Kubernetes distributions provide all the necessary APIs and functionality. A similar approach should needs to be applied to any OSS Networking AI projects. End users Users should have a certain level of confidence, knowing that the OSS based AI Networking solution they use will behave as expected.
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At the heart of this transformation lies the concept of the intelligence plane, where AI-driven systems leverage natural intent interaction to seamlessly bridge the gap between users and networks. Cognitive smart Smart orchestration ensures optimal resource allocation and dynamic adaptation to meet evolving demands, thereby enhancing network performance and user experiencesexperience. Real-time meta network verification, powered by AI algorithms, ensures continuous monitoring and validation of network behavior, preempting potential issues and maintaining operational integrity. Additionally, built-in knowledge open-loops enable networks to autonomously learn and adapt, fostering resilience and responsiveness.
Moreover, the The concept of ubiquitous intelligence envisaged by IMT-2030 underscores the pervasive presence of AI across the communication systemtelecommunications community. From autonomous network management to context-aware devices, AI will imbue touch every aspect of network operations with enhanced intelligence, efficiency, and adaptability. AI-enabled air interfaces, coupled with distributed computing, will pave the way for end-to-end AI applicability, fostering convergence between communication across the telecommunications and computing domains.
Drawing from the IMT-2030 vision, the integration of AI into mobile networks unlocks transformative capabilities. Advanced human-machine interfaces, such as extended reality (XR) displays and haptic sensors, offer immersive experiences, blurring the boundaries between physical and virtual realms. Intelligent machines, equipped with machine perception and autonomous capabilities, facilitate seamless interactions and drive digital economic growth and societal changes.
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The Linux Foundation's role in joining the AI revolution underscores the importance of open-source collaboration in advancing network capabilities. By harnessing open-source technologies, network operators can leverage the collective expertise of the community to accelerate innovation and adoption of AI-driven solutions. This collaborative approach not only democratizes access to advanced AI capabilities but also fosters interoperability and scalability across diverse companies and network environments.
The future of Intelligent Networks and AI adoption in the telecom industry is in the hands of the individuals and organizations who are already contributing to projects and initiatives, and those who will join them. If you are involved in building and operating networks, developing network technology or consuming network services, you are most heartily encouraged to getting involved. Engaging with OSS communities is a way to shape the future of Networkingnetworking. Your contribution could be small or large, and does not necessarily involve writing code. In fact the community is very much in need of contributors of white papers such as this one, evangelists and big thinkers who want to drive the realization of some really cool and useful leading edge technologies come to fruition. Some of the ways to contribute include:
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In conclusion, the future of networks in the era of 6G and beyond hinges on the transformative power of AI, fueled by open-source collaboration. By embracing AI-driven intelligence, networks can enhance situational awareness, performance, and capacity management, while enabling quick reactions responses to address undesired states. As we navigate this AI-powered future, the convergence of technological innovation and open collaboration holds the key to unlocking boundless opportunities for progress and prosperity in the telecommunications landscape.
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