TL;DR At Cloud Native Telco Day during KubeCon + CloudNativeCon Europe 2026, Yoshihiro Nakajima (NTT DOCOMO), Ranny Haiby (The Linux Foundation), Philippe Ensarguet (Orange), Hui Deng (Huawei), and Yanjun Chen…
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TL;DR At Cloud Native Telco Day during KubeCon + CloudNativeCon Europe 2026, Ranny Haiby and Philippe Ensarguet explained that Agentic AI in telecom builds on nearly a decade of cloudification…
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As telecom networks evolve toward autonomous, software-defined operations, AI and cloud native infrastructure must advance together. This white paper explores why Project Sylva provides the open, standardized foundation needed to…
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As networks become more distributed, dynamic, and software-driven, the industry is reaching a clear turning point: automation alone is no longer enough. The next phase is agentic AI: systems that…
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Migration marks a new chapter for open source Radio Access Network development, with continued O-RAN ALLIANCE partnership LF Networking now addresses full end-to-end network stack with formal inclusion of O-RAN…
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The FD.io community continues to push forward on both feature velocity and production-grade validation with the latest VPP 26.02 and CSIT 2602 releases. Together, these updates show steady…
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By: Sreekanth Sasidharan UTO & AVP, Infosys and LFN Board member Achieving higher levels of network autonomy requires more than just technological advancements; it demands a deliberate and structured approach…
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Author: Ciaran Johnston (Ericsson, TSC Vice Chair) The Nephio community continues to make steady progress, and we’re excited to share the latest release. We’re excited to announce the release of…
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ONE Summit India brought together key visionaries, architects and developers across operators, vendors, integrators, academia, and open source communities for a packed day focused on where telecom is headed next:…
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This paper explores how agentic AI is reshaping network architecture—enabling both “AI for Networks” (automation, assurance, and self-healing) and “Networks for AI” (infrastructure optimized for distributed training, inference, and edge…
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