Author: Alan Weissberger

AI wireless and fiber optic network technologies; IMT 2030 “native AI” concept

Posted on by Alan Weissberger

To date, the main benefit of AI for telecom has been to reduce headcount/layoff employees. Light Reading’s Iain Morris wrote, “Telecom operators and vendors, nevertheless, are already using AI as the excuse for thousands of job cuts made and promised. So far, those cuts have not brought any improvement in the sector’s fortunes. Meanwhile, ceding basic but essential skills to systems that hardly anyone understands seems incredibly risky.”  Some say that will change with 6G/ IMT 2030, but that’s a long way off.  Others point to AI RAN, but that has not gotten any real market traction with wireless telcos.

As Gen AI development accelerates, robust wireless and fiber optic network infrastructure will be essential to accommodate the substantial data and communication volume generated by AI systems. Initially, the existing network ecosystem—encompassing wireless, wireline, broadband, and satellite services—will absorb this traffic load. However, the expanding requirements of AI are anticipated to drive the future emergence of entirely new network architectures and communication paradigms.

For sure, AI needs massive, fast, reliable connectivity to function, driving demand for low latency optical networks and 6G/ IMT 2030, which AI itself will optimize, leading to better efficiency, security, resource management, and new services like real-time AR/VR, ultimately boosting telecom revenue and innovation across the entire digital ecosystem.

Source: Pitinan Piyavatin/Alamy Stock Photo

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Key emerging and evolving network types and technologies include:
  • AI Backend Scale-Out and Scale-Up Networks: These are specialized, private networks within and across data centers designed to connect numerous GPUs and enable them to function as one massive compute resource. They utilize technologies like:
    • InfiniBand: A long-standing high-bandwidth, low-latency technology that has become a top choice for connecting GPU clusters in AI training environments.
    • Optimized Ethernet: Ethernet is gaining ground for AI workloads through the development of enhanced, open standards via the Ultra Ethernet Consortium (UEC). These enhancements aim to provide lossless, low-latency fabrics that can match or exceed InfiniBand’s performance at scale.
    • High-Speed Optics: The use of 400 Gbps and 800 Gbps (and soon 1.6 Tbps) optical interconnects is critical for meeting the massive bandwidth and power requirements within and between AI data centers.
  • Edge AI Networking: As AI inferencing (generating responses from AI models) moves closer to the end-user or device (e.g., in autonomous vehicles, smart hospitals, or factories), specialized edge networks are needed. These networks must ensure low latency and localized processing to enable real-time responses.
  • AI-Native 6G Networks: The upcoming sixth-generation (6G) wireless networks are being designed with AI integration as a core principle, rather than an add-on. 
    • These networks are expected to be fully automated and self-evolving, using AI to optimize resource allocation, predict issues, and enhance security autonomously.
    • They will support extremely high data rates (up to 1 Tbps), ultra-low latency (around 1 ms), and new technologies like AI-RAN (Radio Access Network) that integrate AI capabilities directly into the network infrastructure.
    • More in next section below.
  • Self-Evolving Networks: The ultimate goal is the development of “self-evolving networks” where AI agents manage and optimize the network infrastructure autonomously, adapting to new demands and challenges without human intervention. 

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In IMT 2030/6G networks, AI will shift from being an “add-on” optimization tool (as in 5G) to a native, foundational component of the entire network architecture. This deep integration will enable the network to be self-organizing, highly efficient, and capable of supporting advanced AI applications as a service. Native AI for IMT-2030 (6G) means building AI directly into the network’s core architecture, making it AI-first and pervasive, rather than adding AI as an overlay; this enables self-optimizing, intelligent networks that can autonomously manage resources, provide ubiquitous AI services, and offer seamless, context-aware experiences with minimal human intervention, fundamentally transforming both network operations and user applications by 2030.

Core Concepts of Native AI in IMT-2030 (6G):

AI-Native Architecture: AI isn’t just an application; it’s a foundational, intrinsic component throughout the entire system, from the radio interface (RAN) to the core.
  • Ubiquitous Intelligence: Embedding AI everywhere, enabling distributed intelligence for AI model training, inference, and deployment directly within the network infrastructure, extending to the network edge.
  • Autonomous Operations: AI handles complex tasks like network optimization, resource allocation, and automated maintenance (O&M) in real-time, reducing reliance on manual intervention.
  • AI-as-a-Service (AIaaS): The network transforms into a unified platform providing both communication and AI capabilities, making AI accessible for various applications.
  • Intelligent Processing: AI drives functions across the air interface, resource management, and control planes for highly efficient operations.
  • Data-Driven Automation: Leverages big data and real-time analytics to predict issues, optimize performance, and automate complex decision-making.
  • Seamless User Experience: Moves beyond touchscreens to AI-driven interactions, offering more natural and contextual computing.
AI for Network Management and Optimization (“AI-Empowered Networks”):
AI and Machine Learning (ML) will be intrinsically embedded within the network’s functions to enhance performance, reliability, and efficiency in ways that conventional, rule-based algorithms cannot. 
  • Autonomous Operations: AI will enable self-monitoring, self-optimization, and self-healing networks, drastically reducing the need for human intervention in operation and maintenance (O&M).
  • Dynamic Resource Management: ML algorithms will analyze massive amounts of network data in real-time to predict traffic patterns and user demands, dynamically allocating bandwidth, power, and computing resources to ensure optimal performance and energy efficiency.
  • AI-Native Air Interface: AI/ML models will replace traditional, manually engineered signal processing blocks in the physical layer (e.g., channel estimation, beam management) to adapt dynamically to complex and time-varying wireless environments, improving spectral efficiency.
  • Enhanced Security: AI will be critical for real-time threat detection and automated incident response across the hyper-connected 6G ecosystem, identifying anomalies and mitigating security risks that are not well understood by current systems.
  • Digital Twins: AI will power the creation and management of real-time digital twins (virtual replicas) of the physical network, allowing for sophisticated simulations and testing of network changes before real-world deployment. 
Network as an Enabler of AI Services (“Network-Enabled AI” or “AI as a Service”):
The 6G network itself will serve as a platform for pervasive, distributed AI, bringing compute power closer to the end-users and devices.
  • Pervasive Edge AI: AI model training and inference will be distributed throughout the network, from the cloud to the edge (devices, base stations), reducing latency and enabling real-time, localized decision-making for applications like autonomous driving and industrial automation.
  • Support for Advanced Use Cases: The massive data rates (up to 1 Tbps), ultra-low latency, and high reliability enabled by AI in 6G will facilitate new applications such as holographic communication, remote robotic surgery with haptic feedback, and collaborative robotics that were not feasible with 5G.
  • Federated Learning: The network will support distributed machine learning techniques, such as federated learning, which allow AI models to be trained on local data across various devices without the need to centralize sensitive user data, thus ensuring data privacy and security.
  • Integrated Sensing and Communication (ISAC): AI will process the rich environmental data gathered through 6G’s new sensing capabilities (e.g., precise positioning, motion detection, environmental monitoring), allowing the network to interact with and understand the physical world in a holistic manner for applications like smart city management or augmented reality. 

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AI‑native air interface and RAN:

IMT‑2030 explicitly expects a new AI‑native air interface that uses AI/ML models for core PHY/MAC functions such as channel estimation, symbol detection/decoding, beam management, interference handling, and CSI feedback. This enables adaptive waveforms and link control that react in real time to channel and traffic conditions, going beyond deterministic algorithms in 5G‑Advanced.​

At the RAN level, IMT‑2030 envisions “native‑AI enabled” architectures that are simpler but more intelligent, with data‑driven operation and distributed learning across gNBs, edge nodes, and devices. AI/ML will be applied end‑to‑end for resource allocation, mobility, energy optimization, and fault management, effectively turning the RAN into a self‑optimizing, self‑healing system.​

Integrated AI and communication services:

The framework defines “Artificial Intelligence and Communication” (often phrased as Integrated AI and Communication) as a specific usage scenario where the network provides AI compute, model hosting, and inference as a service. Example use cases include IMT‑2030‑assisted automated driving, cooperative medical robotics, digital twins, and offloading heavy computation from devices to edge/cloud via the 6G network.​

To support this, IMT‑2030 includes “applicable AI‑related capabilities” such as distributed data processing, distributed learning, AI model execution and inference, and AI‑aware scheduling as native capabilities of the system. Computing and data services (not just connectivity) are treated as integral IMT‑2030 components, especially at the edge for low‑latency, energy‑efficient AI workloads.​

System intelligence and new use cases:

AI is central to several new IMT‑2030 usage scenarios beyond classic eMBB/mMTC/URLLC, including Immersive Communication, Integrated Sensing and Communication, and Integrated AI and Communication. In integrated sensing, AI fuses multi‑dimensional radio sensing data (position, motion, environment, even human behavior) to provide contextual awareness for applications like smart cities, industrial control, and XR.​

Embedding intelligence across air interface, edge, and cloud is seen as necessary to manage 6G complexity and enable “Intelligence of Everything,” including real‑time digital twins and AIGC‑driven services. The vision is for the 6G/IMT‑2030 network to act as a distributed neural system that tightly couples communication, sensing, and computing.

IMT 2030 Goals:

  • To create self-healing, self-optimizing networks that can adapt to diverse demands.
  • To enable new AI-driven applications, from intelligent digital twins to advanced immersive experiences.
  • To build a truly intelligent communication fabric that supports a hyper-connected, AI-enhanced world.

​Summary table: AI’s roles in IMT‑2030:

Dimension AI role in IMT‑2030
Air interface AI‑native PHY/MAC for channel estimation, decoding, beamforming, interference control.​
RAN/core architecture Native‑AI enabled, data‑driven, self‑optimizing/self‑healing network functions.​
Compute and data services Built‑in edge/cloud compute for AI training, inference, and data processing.​
Usage scenarios Dedicated “Integrated AI and Communication” plus AI‑rich sensing and immersive use cases.​
Applications and ecosystems Support for digital twins, automated driving, robotics, AIGC, and industrial automation.​

In summary, AI in IMT‑2030 is both an internal engine for network intelligence and an exported capability the network offers to verticals, making 6G effectively AI‑native end‑to‑end.

References:

https://www.lightreading.com/ai-machine-learning/the-lessons-of-pluribus-for-telecom-s-genai-fans

https://www.ericsson.com/en/reports-and-papers/white-papers/ai-native

https://www.5gamericas.org/wp-content/uploads/2024/08/ITUs-IMT-2030-Vision_Id.pdf

ITU-R WP 5D Timeline for submission, evaluation process & consensus building for IMT-2030 (6G) RITs/SRITs

ITU-R WP 5D reports on: IMT-2030 (“6G”) Minimum Technology Performance Requirements; Evaluation Criteria & Methodology

Ericsson and e& (UAE) sign MoU for 6G collaboration vs ITU-R IMT-2030 framework

Nokia and Rohde & Schwarz collaborate on AI-powered 6G receiver years before IMT 2030 RIT submissions to ITU-R WP5D

NTT DOCOMO successful outdoor trial of AI-driven wireless interface with 3 partners

Verizon’s 6G Innovation Forum joins a crowded list of 6G efforts that may conflict with 3GPP and ITU-R IMT-2030 work

ITU-R WP5D IMT 2030 Submission & Evaluation Guidelines vs 6G specs in 3GPP Release 20 & 21

Dell’Oro: Analysis of the Nokia-NVIDIA-partnership on AI RAN

Highlights of 3GPP Stage 1 Workshop on IMT 2030 (6G) Use Cases

Draft new ITU-R recommendation (not yet approved): M.[IMT.FRAMEWORK FOR 2030 AND BEYOND]

 

Subsea cable systems: the new high-capacity, high-resilience backbone of the AI-driven global network

Posted on by Alan Weissberger

Introduction:

The subsea cable industry is entering a high-growth, high-complexity phase driven primarily by AI, hyperscale cloud expansion, and geopolitical risk.  Subsea fiber-optic systems that carry more than 95% of international data traffic are being reassessed, re-engineered, and re-regulated. As of 2024, there were reportedly more than 600 submarine cable systems (532 operational + 77 planned).

According to a Mordor Intelligence report, the global subsea-cable market is expected to grow from $5.31 Billion in 2025 to $8.95 Billion in 2030 for a CAGR of 11.02 %.  That’s mostly due to rising demand for both throughput and redundancy.   Here’s the market overview from Mordor Intelligence:

• The demand for submarine optical fiber cables continues to increase, driven by the growth in global internet usage, cloud services, and data consumption. The expanding digital communication needs, video streaming services, and requirements for real-time connectivity necessitate high-capacity, low- latency infrastructure for intercontinental data transmission. Submarine cables now transport more than 95% of international internet traffic, establishing themselves as essential components of global communications infrastructure.

• The expansion of data centers and investments by hyperscale companies, including Google, Meta, Amazon, and Microsoft, significantly influences market demand. These technology companies are developing private submarine cable networks to reduce their reliance on external providers and enhance platform connectivity. Their investments expand the submarine cable network and advance cable technology through improvements in wavelength-division multiplexing (WDM) and increased fiber pair capacity.

• The market growth also reflects broader geopolitical and economic developments. Developing nations seeking digital inclusion require integration into global submarine cable networks. Government initiatives and regional partnerships are implementing cable projects to connect underserved regions, improve network redundancy, and support economic growth. Geopolitical considerations have prompted countries to establish diverse cable routes, reducing dependence on specific regions or nations.

• The need for environmental resilience and network redundancy further strengthens demand. Natural disasters and geopolitical events highlight vulnerabilities in existing routes, increasing the implementation of multiple cable pathways. New opportunities for transcontinental connections are emerging, such as Arctic routes becoming viable as polar ice diminishes. These factors indicate sustained demand for submarine optical fiber cables, with ongoing investments continuing to shape international communications infrastructure.

Technology roadmaps are shifting from incremental upgrades to large-scale architectural redesign. As AI workloads surge and hyperscale cloud deployments scale globally, the priority is shifting from basic connectivity to resilient, strategically differentiated network infrastructure.

Capacity and Architecture Evolution:

  • Throughput is accelerating from traditional 20–40 Tbps systems to 400 Tbps+ class designs, enabled by:

    • Space-division multiplexing (SDM) with higher fiber-pair counts

    • Advanced coherent optics and probabilistic constellation shaping

    • More efficient repeaters and lower-loss fibers

  • Subsea cable systems are increasingly co-designed with hyperscalers for AI-training workloads that require extreme bandwidth and consistent low latency.

  • Hyperscalers support global cloud services, AI/ML workloads, and massive data flows — requirements that only high-capacity, high-performance undersea cables can satisfy. By owning or co-owning cables, these companies reduce dependency on traditional telecom carriers, improve redundancy, and gain more control over routing, latency, and capacity planning.

  • Historically telcos and specialized carriers laid and operated undersea cables. Now, cloud giants themselves are wrapping subsea infrastructure into their global network stacks.

  • Here’s a summary of hyperscalers in the Subsea-Cable Market:

    Google

    • Google is among the most prolific investors: reportedly involved in about 33 subsea cables globally.

    • Recent and planned projects include the upcoming Humboldt Cable (linking Chile and Australia), intended to create a new South America ↔ Asia-Pacific route.

    • Google’s involvement typically aims to serve its cloud and data-center operations, improving capacity, latency, and resiliency across its global network.

    Meta (parent of Facebook / Instagram / WhatsApp)

    • Meta has significantly broadened its subsea footprint. According to recent reporting, it plans a major new global cable project — possibly its largest — which would mark the first time the company is the sole owner of a fully private, global-scale undersea cable. TechCrunch+2suboptic.org+2

    • This shift underscores the company’s drive to fully own its data transport infrastructure (rather than rely on traditional telco-owned cables), giving it greater control over capacity, latency, and where traffic moves. TechCrunch+1

    Amazon Web Services (AWS / Amazon)

    • AWS is also listed among the major hyperscalers investing in subsea cables globally. americangovernancetoday.com+1

    • This investment reflects the growing need for cloud providers to ensure high-bandwidth, low-latency, and resilient global connectivity to support cloud services and AI workloads. FlipHTML5+1

    Microsoft

    • Microsoft is likewise involved in the construction and ownership of subsea infrastructure. americangovernancetoday.com+2German Marshall Fund+2

    • Historically, it has co-owned systems — for example, with Meta — but as with other hyperscalers, the motivation is strategic: ensuring predictable capacity, performance, and data-center interconnectivity for cloud services.

Resilience-by-Design:

  • The market is shifting from “best-effort” reliability to assumed-failure design, incorporating:

    • Diversified routing (avoiding choke points and geopolitically sensitive zones)

    • Deeper burial and armoring for seabed stability

    • Carrier-neutral landing stations that allow rapid rerouting

  • Operators are integrating real-time monitoring, predictive maintenance, and autonomous fault detection into cable management platforms.

Integration with Cloud and Edge:

  • New cables are being deployed with cloud data center adjacency as a primary requirement, not an afterthought.

  • Growth in regional AI/ML clusters is prompting:

    • More mid-ocean branching units to improve localization

    • Distributed landing sites connected to edge compute locations

    • Greater dependence on software-defined interconnection and global WAN orchestration

Pressure Points – Capacity, Risk, and Regulation:

Network operators and governments are navigating three major challenges:

1.  Geopolitical and security risk: Accidental cuts, anchor strikes, and deliberate interference are increasingly treated as systemic vulnerabilities.

2. Permitting, route diversity, and climate exposure: Coastal erosion, the need for protected landing zones, and more complex regulatory regimes are reshaping route planning and deployment timelines.

3. AI-driven bandwidth requirements: Next-generation systems must support orders-of-magnitude higher capacity with lower latency, optimized for AI-training and high-density cloud workloads.

These forces are shifting strategies from “What is the lowest-cost route?” to “What routes provide strategic resilience, scalability, and long-term value?”

Key Takeaways from the Modor Intelligence Report:

  • By component, wet-plant equipment held 53.20% of the submarine optical fiber cable market share in 2024, and auxiliary and marine services are projected to advance at a 12.03% CAGR between 2025-2030.
  • By cable type, single-mode fiber accounted for 67.89% of the submarine optical fiber cable market size in 2024, and SDM multi-core fiber is forecast to grow at a 13.89% CAGR through 2030.
  • By client type, telecom operators still held a 62.00% market share in 2024 of the submarine optical fiber cable market size, while hyperscale cloud providers are outpacing them at a 12.98% CAGR through 2030.
  • By capacity design, systems rated 16-60 Tbps held 56.00% market share in 2024, and above-60 Tbps links are advancing at a 13.70% CAGR through 2030.
  • By geography, North America led with a 36.78% revenue share in 2024; the Asia Pacific is poised for the fastest expansion at an 11.56% CAGR through 2030.

Case Study: Mid-Atlantic Positioning:

Smaller jurisdictions are emerging as strategic nodes traditionally dominated by major cable hubs. Bermuda is one example: the island’s 2020 Submarine Communications Cable Act introduced one of the Atlantic region’s most transparent frameworks for landing-site permitting and protection zones.

With multiple new systems planned or announced, Bermuda demonstrates how geography combined with regulatory clarity can create a defensible strategic position. Rather than relying on promotional incentives, the jurisdiction offers disciplined permitting processes, alignment with investor timelines, and compatibility with broader route-diversification strategies.

Three trends will define the next phase of subsea-cable strategy:

  1. Explosive throughput growth: Designs are moving toward 400-Tbps-class systems and high-fiber-pair architectures purpose-built for AI-training workloads.

  2. Resilience and route diversity by default: Outages are assumed rather than hypothetical. Systems are being engineered with alternative paths, deeper burial, and more carrier-neutral landing facilities.

  3. Regulation as part of core infrastructure strategy: Governments are treating subsea cables as strategic assets, increasing scrutiny on landing rights, environmental permitting, and data-sovereignty implications.

Security and Sovereignty Considerations:

  • Governments are classifying subsea cables as strategic infrastructure, driving:

    • Tighter control over landing rights and ownership structures

    • Requirements for physical and logical segmentation

    • Increased surveillance for tampering, espionage, and sabotage

  • Encryption and trust architectures are being embedded deeper into cable system design.

Deployment Speed and Regulatory Overhead:

  • As climate risk, permitting complexity, and geopolitical scrutiny increase, deployments take longer and require more contingencies.

  • Technology choices now depend partly on which routes can be approved, protected, and operationally supported long-term.

Implications for Site-Selectors, Executives, and Policymakers:

  • For site-selectors and investors, landing-site decisions now hinge on risk exposure, operational flexibility, and regulatory transparency.
  • For C-suite leaders, infrastructure alignment and ecosystem partnerships influence not only latency and cost, but also resilience, compliance readiness, and diversification.
  • For policymakers, agile and predictable regulatory frameworks will determine whether a jurisdiction becomes a preferred landing point or is bypassed entirely.

Conclusions:

The subsea cable market is rapidly evolving into a hyperscale-driven, AI-optimized, resilience-centric segment of global infrastructure. Future systems will be defined not just by terabits per second, but also by architectural flexibility, geopolitical robustness, integration with cloud and AI ecosystems, and regulatory alignment.  In summary, the subsea-cable sector is becoming a foundational layer of the global digital economy—an economy increasingly shaped by AI, cloud expansion, and geopolitical complexity. Jurisdictions that anticipate these shifts and design for resilience and scalability will play disproportionate roles in the decade ahead. The question is no longer simply where cables land, but how the broader ecosystem supports the next wave of digital growth.

References:

https://www.thefastmode.com/expert-opinion/46323-the-future-arteries-of-the-internet-subsea-fiberoptic-cables-in-the-age-of-ai-environmental-resilience-and-geopolitics

https://www.mordorintelligence.com/industry-reports/submarine-optical-fiber-cable-market

Google Cloud announces TalayLink subsea cable and new connectivity hubs in Thailand and Australia

FCC updates subsea cable regulations; repeals 98 “outdated” broadcast rules and regulations

India’s Data Transmission Capacity to Quadruple in 2025 via New Submarine Cables

TechCrunch: Meta to build $10 billion Subsea Cable to manage its global data traffic

Google’s Bosun subsea cable to link Darwin, Australia to Christmas Island in the Indian Ocean

HGC Global Communications, DE-CIX & Intelsat perspectives on damaged Red Sea internet cables

“SMART” undersea cable to connect New Caledonia and Vanuatu in the southwest Pacific Ocean

Telstra International partners with: Trans Pacific Networks to build Echo cable; Google and APTelecom for central Pacific Connect cables

NEC completes Patara-2 subsea cable system in Indonesia

SEACOM telecom services now on Equiano subsea cable surrounding Africa

Orange Deploys Infinera’s GX Series to Power AMITIE Subsea Cable

China seeks to control Asian subsea cable systems; SJC2 delayed, Apricot and Echo avoid South China Sea

Intentional or Accident: Russian fiber optic cable cut (1 of 3) by Chinese container ship under Baltic Sea

Bharti Airtel and Meta extend 2Africa Pearls subsea cable system to India

Google’s Equiano subsea cable lands in Namibia en route to Cape Town, South Africa

Altice Portugal MEO signs landing party agreement for Medusa subsea cable in Lisbon

Wireless Broadband Alliance Report: WiFi 7, converged Wi-Fi and 5G, AI/Cognitive networks, and OpenRoaming

Posted on by Alan Weissberger

The Wireless Broadband Alliance (WBA) has today released its annual industry report and survey findings. The “WBA Industry Report 2026” contains the results of its annual industry survey across the Wi-Fi, cellular and enterprise ecosystem. Among its chief findings is that 62% of respondents have grown more confident to invest in Wi-Fi over the last 12 months (18% are as confident). Wi-Fi 7 is the technology most likely to be deployed in 2026, with 38% of respondents planning deployments. Closely behind that is the impact of AI, with 32% planning to deploy AI/Cognitive networks, which can transform Wi-Fi networking, with an ability to improve the performance and reliability of networks.

Here are a few highlights:

  • 60% of respondents see converged Wi-Fi and 5G as key to enterprise flexibility and that both will co-exist.
  • 38% plan to roll out Wi-Fi 7 in 2025/2026, while 65% say 6 GHz availability is important or critical to their Wi-Fi business.
  • 32% plan to deploy AI/Cognitive networks.

Convergence matters more:

When asked about the role of Wi-Fi in converged networks with both 5G and private enterprise implementations, responses reinforced the view that the technologies are complementary and together benefit organizations. Six in ten (60%) said combining them would give their organization greater enterprise flexibility. The same proportion expect Wi-Fi and 5G to co-exist, rather than be a binary choice for enterprise networks.

OpenRoaming momentum:

The industry survey shows OpenRoaming transitioning into a period of mainstream planning with the need for seamless onboarding and roaming between Wi-Fi and cellular networks now seen as central business drivers. 38% of respondents say they had already deployed a OpenRoaming and/or Passpoint compliant network with a further 32% wishing to deploy in 2026, and 18% in 2027.

When asked what is driving investment in OpenRoaming/Passpoint, the top three reasons given were Enablement of frictionless Wi-Fi (63%), seamless access between Wi-Fi and 5G/LTE (60%) and seamless access across different networks (40%). Each of these responses relates to network access, highlighting that this element is the most important factor for the industry.

Wi-Fi’s role in business continuity:

Respondents also gave their views on the aspects of Wi-Fi they considered most important to their business at present, and what they expected to be the most important in the future. Network security and privacy was identified as the most important area for businesses today, with 76% of all responses. Tied second position for the current most important aspect of Wi-Fi, both with 70% of responses, were end user experiences (Quality of Experience and Quality of Service), and seamless authentication to Wi-Fi.

Asked about the most important new or improved feature of Wi-Fi 6E and Wi-Fi 7, respondents rated Multi-Link Operation (MLO) as the single most important at 46%, highlighting a sharp focus on latency, resilience and spectrum efficiency in dense environments. This was followed in joint second place by OFDMA Uplink & Downlink, and Mandatory WPA3 compliance (both 33%). Multi-User MIMO Uplink took third position at 32%.

Additional key survey findings:

  • 6 GHz band availability seen as ‘important’ or ‘critical’ by 65% of respondents to the future of their Wi-Fi business and rollout, underscoring the centrality of 6 GHz to future Wi-Fi strategies
  • City-wide public Wi-Fi deployed by 33% of relevant respondents, with a further 39% planning deployments for 2026/2027. The top three services organizations see Public Wi-Fi underpinning were supporting city services (70%), the provision of seamless, affordable, and secure internet access to users (65%), and to provide offload to carriers (49%). City governments around the world, such as the Tokyo Metropolitan Government (TMG), are already utilizing OpenRoaming to deliver all these services

Tiago Rodrigues, President and CEO of the Wireless Broadband Alliance, said: “This year’s WBA Industry Report survey makes it clear that the Wi-Fi community has moved to building the next generation of converged connectivity and the momentum is strong: Wi-Fi 7 and AI-driven networks, which can cut costs, while improving the operational efficiency, performance and reliability of networks, are at the top of deployment plans. 6 GHz is viewed as critical spectrum, and almost half of respondents are already deploying or planning OpenRoaming networks. Respondent’s priorities of security, privacy, Quality of Experience and seamless roaming between Wi-Fi and 5G are exactly where the WBA is focused through our programs of work. In a world where connectivity is business continuity, these findings show that Wi-Fi has become essential infrastructure for enterprises, operators and cities alike.”

The WBA Industry Survey 2026 collected input from 185 participants worldwide, with diverse job roles ranging from the C-suite and business strategy to those in research & development (R&D) and product management in a wide range of sectors.

About the Wireless Broadband Alliance:

Wireless Broadband Alliance (WBA) is the global organization that connects people with the latest Wi-Fi initiatives. Founded in 2003, the vision of the WBA is to drive seamless, interoperable service experiences via Wi-Fi within the global wireless ecosystem. The WBA’s mission is to bring together global industry leaders, collaborating to accelerate the development, integration and adoption of next-generation Wi-Fi and wireless technologies to deliver business growth, through innovation, technical and standards development, and real-world deployment programs.

Key programs include NextGen Wi-Fi, OpenRoaming, 5G, 6G, IoT, Smart Cities, Testing & Interoperability and Policy & Regulatory Affairs.

www.twitter.com/wballiance

www.facebook.com/WirelessBroadbandAlliance

www.linkedin.com/company/2919934/

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References:

https://wballiance.com/industry-report-2026/

WiFi 7: Backgrounder and CES 2025 Announcements

WiFi 7 and the controversy over 6 GHz unlicensed vs licensed spectrum

MediaTek to expand chipset portfolio to include WiFi7, smart homes, STBs, telematics and IoT

CableLabs to bring mobility to WiFi for a better user experience

AT&T to provide free WiFi and private 5G at DFW airport; will invest $10 million worth of network upgrades

Qualcomm FastConnect 7800 combining WiFi 7 and Bluetooth in single chip

 

Analysis: OpenAI and Deutsche Telekom launch multi-year AI collaboration

Posted on by Alan Weissberger

Deutsche Telekom (DT) has formalized a strategic, multi-year collaboration with OpenAI to integrate advanced artificial intelligence (AI) solutions across its internal operations and customer engagement platforms. The partnership aims to co-develop “simple, personal, and multi-lingual AI experiences” focused on enhancing communication and productivity. Initial pilot programs are slated for deployment in Q1 2026. AI will also play a larger role in customer care, internal copilots, and network operations as the Group advances toward more autonomous, self-healing networks.DT plans a company-wide rollout of ChatGPT Enterprise, leveraging AI to streamline core functions including:

  • Customer Care: Deploying sophisticated virtual assistants to manage billing inquiries, service outages, plan modifications, roaming support, and device troubleshooting [1].
  • Internal Operations: Utilizing AI copilots to increase internal efficiency.
  • Network Management: Optimizing core network provisioning and operations.
This collaboration underscores DT’s long-standing strategic imperative to establish itself as a leader in European cloud and AI infrastructure, emphasizing digital sovereignty. Some historical initiatives supporting this strategy include:
  • Sovereign Cloud (2021): DT’s T-Systems division partnered with Google Cloud to offer sovereign cloud services.
  • T Cloud Suite (Early 2025): The launch of a comprehensive suite providing sovereign public, private, and AI cloud options leveraging hybrid infrastructure.
  • Industrial AI Cloud (Early 2025): A collaboration with Nvidia to build a dedicated industrial AI data center in Munich, scheduled for Q1 2026 operations.

The integration of OpenAI technology strategically positions DT to offer a comprehensive value proposition to enterprise clients, combining connectivity, data center capabilities, and specialized AI software under a sovereign framework, according to Recon Analytics Founder Roger Entner.  “There are not that many AI data centers in Europe and in Germany,” Entner explained, noting this leaves the door open for operators like DT to fill in the gap. “In the U.S. you have a ton of data centers that you can do AI. Therefore, it doesn’t make sense for a network operator to have also a data center. They tried to compete with hyperscalers, and it failed. And the scale in the U.S. is a lot bigger than in Europe.”
OpenAI and Deutsche Telekom collaborate. © Deutsche Telekom
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Tekonyx President and Chief Research Officer Sid Nag suggests the integration could extend to employing ChatGPT-based coding tools for developing proprietary Operational Support Systems (OSS) and Business Support Systems (BSS).   He anticipates the partnership will generate new revenue streams through offerings including:
  • Edge AI compute services for enterprises.
  • Vertical AI solutions tailored for healthcare, retail, and manufacturing sectors.
  • Integrated private 5G and AI bundles for industrial logistical hubs.

“Telcos – if they execute – will have a big play in the edge inferencing space as well as providing hosting and colo services that can host domain specific SLMs that need to be run closer to the user data,” he said. “Furthermore, telcos will play a role in connectivity services across Neocloud providers such as CoreWeave, Lambda Labs, Digital Ocean, Vast.AI etc. OpenAI does not want to lose the opportunity to partner with telcos so they are striking early,” Nag added.

Other Voices:

  • Roger Entner notes the model is highly applicable to European incumbents (e.g., Orange, Telefonica) due to the relative scarcity of existing AI data centers in the region, allowing operators to fill a critical infrastructure gap.  Conversely, the model is less viable for U.S. operators, where hyperscalers already dominate the extensive data center market.
  • AvidThink Founder and colleague Roy Chua cautions that while DT presents a robust “reference blueprint,” replicating this strategy requires significant scale, substantial financial investment, and regulatory alignment—factors not easily accessible to all network operators.
  • Futurum Group VP and Practice Lead Nick Patience told Fierce Network, “This deal elevates DT from being a user of AI to being a co-developer, which is pretty significant. DT is one of the few operators building a full-stack AI story. This is an example of OpenAI treating telcos as high-scale distribution and data channels – customer care, billing, network telemetry, national reach and government relationships. This suggests OpenAI is deliberately building an operator channel in key regions (U.S., Korea, EU) but still in partnership with existing cloud and infra providers rather than displacing them.”
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Open AI’s Telco Deals:

OpenAI has established significant partnerships with several telecom network providers and related technology companies to integrate AI into network operations, enhance customer experience, and develop new AI-native platforms. Those deals and collaborations include:

  • T-Mobile: T-Mobile has a multi-year agreement with OpenAI and is actively testing the integration of AI (specifically IntentCX) into its business operations for customer service improvements. T-Mobile is also collaborating with Nokia and Nvidia on AI-RAN (Radio Access Network) technologies for 6G innovation.
  • SK Telecom (SKT): SK Telecom has an in-house AI company and collaborates with OpenAI and other AI leaders like Anthropic to enhance its AI capabilities, build sovereign AI infrastructure, and explore new services for its customers in South Korea and globally. They are also reportedly integrating Perplexity into their offerings.
  • Deutsche Telekom (DT): DT is partnering with OpenAI to offer ChatGPT Enterprise across its business to help teams work more effectively, improve customer service, and automate network operations.
  • Circles: This global telco technology company and OpenAI announced a strategic global collaboration to build a fully AI-native telco SaaS platform, which will first launch in Singapore. The platform aims to revolutionize the consumer experience and drive operational efficiencies for telcos worldwide.
  • Rakuten: Rakuten and OpenAI launched a strategic partnership to develop AI tools and a platform aimed at leveraging Rakuten’s Open RAN expertise to revolutionize the use of AI in telecommunications.
  • Orange: Orange is working with OpenAI to drive new use cases for enterprise needs, manage networks, and enable innovative customer care solutions, including those that support African regional languages.
  • Indian Telecoms (Reliance Jio, Airtel): Telecom providers in India are integrating AI tools from companies like Google and Perplexity into their mobile subscriptions, providing millions of users access to advanced intelligence resources.
  • Nokia & Nvidia: In a broader industry collaboration, Nvidia invested $1 billion in Nokia to add Nvidia-powered AI-RAN products to Nokia’s portfolio, enabling telecom service providers to launch AI-native 5G-Advanced and 6G networks. This partnership also includes T-Mobile US for testing.

Conclusions:

With more than 261 million mobile customers globally, Deutsche Telekom provides a strong foundation to bring AI into everyday use at scale. The new collaboration marks the next step in Deutsche Telekom’s AI journey – moving from early pilots to large-scale products that make AI useful for everyone

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Deutsche Telekom: successful completion of the 6G-TakeOff project with “3D networks”

Deutsche Telekom and Google Cloud partner on “RAN Guardian” AI agent

Deutsche Telekom offers 5G mmWave for industrial customers in Germany on 5G SA network

Deutsche Telekom migrates IP-based voice telephony platform to the cloud

Open AI raises $8.3B and is valued at $300B; AI speculative mania rivals Dot-com bubble

OpenAI and Broadcom in $10B deal to make custom AI chips

Custom AI Chips: Powering the next wave of Intelligent Computing

OpenAI orders HBM chips from SK Hynix & Samsung for Stargate UAE project

OpenAI announces new open weight, open source GPT models which Orange will deploy

OpenAI partners with G42 to build giant data center for Stargate UAE project

Reuters & Bloomberg: OpenAI to design “inference AI” chip with Broadcom and TSMC

Telecom network outages: causes, effects, and remedies for telecom providers & IT enterprise

Posted on by Alan Weissberger

Network outages, historically caused by misconfigurations, software defects, or hardware failures, are increasingly disruptive for several reasons, such as hyper-connectivity, single points of failure and over-reliance on concentrated hyperscaler cloud infrastructures. This leads to an expanded “blast radius” from single points of failure.  The latest Cloudflare outage reveals that enterprises heavily reliant on a dangerously few major IT providers face critical single points of failure, leading to authentication issues, lost revenue, and broken customer experiences.

Cloudflare is a global cloud services and cybersecurity firm. It provides data centers, website and email security, protection from data loss and defences against cyber threats, among other things. It describes itself as providing an “immune system for the internet”, with technology that sits between its clients and the wider world that blocks billions of cyber threats daily. It also uses its global infrastructure to speed up internet traffic. It makes more than $500m – a quarter from nearly 300,000 customers operating in 125 countries, including China. Users of several heavy-traffic websites reported that they went offline at the same time as the Cloudflare outage.

Akamai’s Reuben Koh advocates for a distributed compute and edge architecture, which acts as autonomous cells to mitigate systemic risk and improve resilience via graceful degradation.   He also suggests adopting strategies like graceful degradation and diversifying cloud providers which help telecom operators and other organizations limit the spread of outage disruption.

Computer outage, error or failure causing by software update mistake, operating system crash or cyber attack, server down or technical issue concept, people victims looking at computer laptop outage.

Image credit:  https://www.telecomstechnews.com/
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Koh notes that many organizations – including telecom operators – rely heavily on a narrow set of cloud and SaaS providers/platforms.  “Outages are a reminder that many businesses have concentrated too much of their digital infrastructure on a small number of cloud, SaaS, and network platforms,” he says.
Such concentration means a single cloud region or single provider issue can affect multiple dependent services. It also gives attackers a clearer target, since centralised systems create fewer but more tempting points of failure.
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Regulatory Implications of Cloud Concentration:
Telecom regulators worldwide are actively addressing the systemic risks posed by high concentration in the cloud service provider (CSP) market, while Application Program Interface (API) security in the telecom sector is shifting towards comprehensive lifecycle management and zero trust models.
Regulators now view heavy reliance on a few major global cloud platforms as a national systemic risk rather than a mere IT issue. This is driven by the potential for a single CSP’s failure to cause widespread, cascading service disruptions across critical national infrastructure (CNI) like banking, emergency services, and communications networks.  Key regulatory trends and responses include:
  • Systemic Risk Assessment: Regulations, such as the EU’s Digital Operational Resilience Act (DORA) which is effective from January 17, 2025, are moving from assessing a single firm’s risk to evaluating the broader market impact of a critical third-party provider failure. DORA specifically designates critical ICT third-party providers subject to direct oversight.
  • Operational Resilience Mandates: Jurisdictions are pushing firms to demonstrate the ability to maintain operations or safely exit a non-performing CSP relationship. This includes requirements for robust contingency and exit plans.
  • Geographic Examples:
    –Singapore is framing cloud infrastructure as essential national computing, issuing specific resilience guidelines.
    –Australia has issued warnings to financial institutions regarding over-dependence on a narrow set of US-based hyperscalers.
    –Japan is tightening scrutiny and expectations around managing third-party cloud risks. 
Suggested API Security Measures for Telecom Network Operators:
Network APIs present a significant and growing attack surface, facilitating data exchange between internal systems, partners, and external applications. The security strategy needs to encompass the entire API lifecycle and align with regulatory requirements like the the UK’s Telecommunications Security Act [1.]. 
Some best practices include:
  • Continuous Discovery & Inventory: Telecom operators must maintain an up-to-date, comprehensive inventory of all APIs (managed, unmanaged, “shadow,” and “zombie”) across the enterprise.
  • Shift-Left Security: Integrate security testing and design principles early into the software development lifecycle to identify and remediate vulnerabilities before APIs reach production environments.
  • Implement Zero Trust Architecture (ZTA): Adopt a “never trust, always verify” approach, assuming an attacker may already be internal. This means applying strict authentication and authorization controls at the API level, not just the network perimeter.
  • Strong Authentication and Authorization: Use robust mechanisms like OAuth 2.0 and OpenID. Connect, employing the principle of least privilege to ensure entities only have the minimum necessary access.
  • Runtime Protection and Monitoring: Implement API gateways for centralized traffic management, rate limiting to prevent Denial-of-Service (DoS) attacks, and use behavioral analytics to detect anomalous activity indicative of abuse.
  • Input Validation and Data Handling: Strictly validate and sanitize all data inputs to prevent injection attacks, and ensure APIs only expose necessary information to minimize data leakage.
  • Human Oversight in AI: As AI and automation increase, maintain robust human oversight in change management and incident response, as AI systems can behave unpredictably.   Telecom staff should be closely involved in change management and incident response, even as network automation increases.

Note 1. The UK’s Telecommunications Security Act – 2021 is a landmark law establishing mandatory, tough security standards for public telecom networks, making cybersecurity a legal duty for providers to protect critical infrastructure. It empowers regulator Ofcom, introduces penalties for non-compliance (up to 10% of turnover), and mandates adherence to specific security measures in the Code of Practice (CoP) through phased deadlines, requiring strong governance, supply chain security, and proactive threat management.

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Conclusions:

Koh advocates for the implementation of resilient network architectures and improved operational maturity to enhance system fault tolerance. Key steps include distributed design, optimized operational protocols, comprehensive network visibility, and pragmatic capacity planning. These measures are becoming increasingly important as telecommunications infrastructure underpins essential societal functions.

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References:

What telecom operators can learn from recent network outages

Cloudflare outage highlights enterprise infrastructure dependence

https://www.techtarget.com/whatis/feature/8-largest-IT-outages-in-history

España hit with major telecom blackout after power outage April 28th

Comcast frequent, intermittent internet outages + long outage in Santa Clara, CA with no auto-recovery!

AT&T wireless outage effected more than 74,000 U.S. customers with service disruptions lasting up to 11 hours for some

Rogers Telecommunications restores service after 19 hour outage disrupting life in Canada

GSMA, ETSI, IEEE, ITU & TM Forum: AI Telco Troubleshooting Challenge + TelecomGPT: a dedicated LLM for telecom applications

Rogers Telecommunications restores service after 19 hour outage disrupting life in Canada

 

 

Custom AI Chips: Powering the next wave of Intelligent Computing

Posted on by Alan Weissberger

by the  Indxx team of market researchers with Alan J Weissberger

The Market for AI Related Semiconductors:

Several market research firms and banks forecast that revenue from AI-related semiconductors will grow at about 18% annually over the next few years—five times faster than non-AI semiconductor market segments.

  • IDC forecasts that global AI hardware spending, including chip demand, will grow at an annual rate of 18%.
  • Morgan Stanley analysts predict that AI-related semiconductors will grow at an 18% annual rate for a specific company, Taiwan Semiconductor (TSMC).
  • Infosys notes that data center semiconductor sales are projected to grow at an 18% CAGR.
  • MarketResearch.biz and the IEEE IRDS predict an 18% annual growth rate for AI accelerator chips.
  • Citi also forecasts aggregate chip sales for potential AI workloads to grow at a CAGR of 18% through 2030. 

AI-focused chips are expected to represent nearly 20% of global semiconductor demand in 2025, contributing approximately $67 billion in revenue [1].  The global AI chip market is projected to reach $40.79 billion in 2025 [2.] and continue expanding rapidly toward $165 billion by 2030.

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Types of AI Custom Chips:

Artificial intelligence is advancing at a speed that traditional computing hardware can no longer keep pace with. To meet the demands of massive AI models, lower latency, and higher computing efficiency, companies are increasingly turning to custom AI chips which are purpose-built processors optimized for neural networks, training, and inference workloads.

Those AI chips include Application Specific Integrated Circuits (ASICs) and Field- Programmable Gate Arrays (FPGAs) to Neural Processing Units (NPUs) and Google’s Tensor Processing Units (TPUs).  They are optimized for core AI tasks like matrix multiplications and convolutions, delivering far higher performance-per-watt than CPUs or GPUs. This efficiency is key as AI workloads grow exponentially with the rise of Large Language Models (LLMs)  and generative AI.

OpenAI – Broadcom Deal:

Perhaps the biggest custom AI chip design is being done by an OpenAI partnership with Broadcom in a multi-year, multi-billion dollar deal announced in October 2025.  In this arrangement, OpenAI will design the hardware and Broadcom will develop custom chips to integrate AI model knowledge directly into the silicon for efficiency.

Here’s a summary of the partnership:

  • OpenAI designs its own AI processors (GPUs) and systems, embedding its AI insights directly into the hardware. Broadcom develops and deploys these custom chips and the surrounding infrastructure, using its Ethernet networking solutions to scale the systems.
  • Massive Scale: The agreement covers 10 gigawatts (GW) of AI compute, with deployments expected over four years, potentially extending to 2029.
  • Cost Savings: This custom silicon strategy aims to significantly reduce costs compared to off-the-shelf Nvidia or AMD chips, potentially saving 30-40% on large-scale deployments.
  • Strategic Goal: The collaboration allows OpenAI to build tailored hardware to meet the intense demands of developing frontier AI models and products, reducing reliance on other chip vendors.

AI Silicon Market Share of Key Players:

  • Nvidia, with its extremely popular AI GPUs and CUDA software ecosystem., is expected to maintain its market leadership. It currently holds an estimated 86% share of the AI GPU market segment according to one source [2.]. Others put NVIDIA’s market AI chip market share between 80% and 92%.
  • AMD holds a smaller, but growing, AI chip market share, with estimates placing its discrete GPU market share around 4% to 7% in early to mid-2025. AMD is projected to grow its AI chip division significantly, aiming for a double-digit share with products like the MI300X.  In response to the extraordinary demand for advanced AI processors, AMD’s Chief Executive Officer, Dr. Lisa Su, presented a strategic initiative to the Board of Directors: to pivot the company’s core operational focus towards artificial intelligence. Ms. Su articulated the view that the “insatiable demand for compute” represented a sustained market trend. AMD’s strategic reorientation has yielded significant financial returns; AMD’s market capitalization has nearly quadrupled, surpassing $350 billion [1]. Furthermore, the company has successfully executed high-profile agreements, securing major contracts to provide cutting-edge silicon solutions to key industry players, including OpenAI and Oracle.
  • Intel accounts for approximately 1% of the discrete GPU market share, but is focused on expanding its presence in the AI training accelerator market with its Gaudi 3 platform, where it aims for an 8.7% share by the end of 2025.  The former microprocessor king has recently invested heavily in both its design and manufacturing businesses and is courting customers for its advanced data-center processors.
  • Qualcomm, which is best known for designing chips for mobile devices and cars, announced in October that it would launch two new AI accelerator chips. The company said the new AI200 and AI250 are distinguished by their very high memory capabilities and energy efficiency.

Big Tech Custom AI chips vs Nvidia AI GPUs:

Big tech companies, including Google, Meta, Amazon, and Apple—are designing their own custom AI silicon to reduce costs, accelerate performance, and scale AI across industries. Yet nearly all rely on TSMC for manufacturing, thanks to its leadership in advanced chip fabrication technology [3.]

  • Google recently announced Ironwood, its 7th-generation Tensor Processing Unit (TPU), a major AI chip for LLM training and inference, offering 4x the performance of its predecessor (Trillium) and massive scalability for demanding AI workloads like Gemini, challenging Nvidia’s dominance by efficiently powering complex AI at scale for Google Cloud and major partners like Meta. Ironwood is significantly faster, with claims of over 4x improvement in training and inference compared to the previous Trillium (6th gen) TPU.  It allows for super-pods of up to 9,216 interconnected chips, enabling huge computational power for cutting-edge models. It’s optimized for high-volume, low-latency AI inference, handling complex thinking models and real-time chatbots efficiently.
  • Meta is in advanced talks to purchase and rent large quantities of Google’s custom AI chips (TPUs), starting with cloud rentals in 2026 and moving to direct purchases for data centers in 2027, a significant move to diversify beyond Nvidia and challenge the AI hardware market. This multi-billion dollar deal could reshape AI infrastructure by giving Meta access to Google’s specialized silicon for workloads like AI model inference, signaling a major shift in big tech’s chip strategy, notes this TechRadar article. 
  • According to a Wall Street Journal report published on December 2, 2025, Amazon’s new Trainium3 custom AI chip presents a challenge to Nvidia’s market position by providing a more affordable option for AI development.  Four times as fast as its previous generation of AI chips, Amazon said Trainium3 (produced by AWS’s Annapurna Labs custom-chip design business) can reduce the cost of training and operating AI models by up to 50% compared with systems that use equivalent graphics processing units, or GPUs.  AWS acquired Israeli startup Annapurna Labs in 2015 and began designing chips to power AWS’s data-center servers, including network security chips, central processing units, and later its AI processor series, known as Inferentia and Trainium.  “The main advantage at the end of the day is price performance,” said Ron Diamant, an AWS vice president and the chief architect of the Trainium chips. He added that his main goal is giving customers more options for different computing workloads. “I don’t see us trying to replace Nvidia,” Diamant said.
  • Interestingly, many of the biggest buyers of Amazon’s chips are also Nvidia customers. Chief among them is Anthropic, which AWS said in late October is using more than one million Trainium2 chips to build and deploy its Claude AI model. Nvidia announced a month later that it was investing $10 billion in Anthropic as part of a massive deal to sell the AI firm computing power generated by its chips.

Image Credit: Emil Lendof/WSJ, iStock

Other AI Silicon Facts and Figures:

  • Edge AI chips are forecast to reach $13.5 billion in 2025, driven by IoT and smartphone integration.
  • AI accelerators based on ASIC designs are expected to grow by 34% year-over-year in 2025.
  • Automotive AI chips are set to surpass $6.3 billion in 2025, thanks to advancements in autonomous driving.
  • Google’s TPU v5p reached 30% faster matrix math throughput in benchmark tests.
  • U.S.-based AI chip startups raised over $5.1 billion in venture capital in the first half of 2025 alone.

Conclusions:

Custom silicon is now essential for deploying AI in real-world applications such as automation, robotics, healthcare, finance, and mobility. As AI expands across every sector, these purpose-built chips are becoming the true backbone of modern computing—driving a hardware race that is just as important as advances in software. More and more AI firms are seeking to diversify their suppliers by buying chips and other hardware from companies other than Nvidia.  Advantages like cost-effectiveness, specialization, lower power consumption and strategic independence that cloud providers gain from developing their own in-house AI silicon.  By developing their own chips, hyperscalers can create a vertically integrated AI stack (hardware, software, and cloud services) optimized for their specific internal workloads and cloud platforms. This allows them to tailor performance precisely to their needs, potentially achieving better total cost of ownership (TCO) than general-purpose Nvidia GPUs

However, Nvidia is convinced it will retain a huge lead in selling AI silicon.  In a post on X, Nvida wrote that it was “delighted by Google’s success with its TPUs,” before adding that Nvidia “is a generation ahead of the industry—it’s the only platform that runs every AI model and does it everywhere computing is done.” The company said its chips offer “greater performance, versatility, and fungibility” than more narrowly tailored custom chips made by Google and AWS.

The race is far from over, but we can expect to surely see more competition in the AI silicon arena.

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Links for Notes:

1.  https://www.mckinsey.com/industries/semiconductors/our-insights/artificial-intelligence-hardware-%20new-opportunities-for-semiconductor-companies/pt-PT

2. https://sqmagazine.co.uk/ai-chip-statistics/

3. https://www.ibm.com/think/news/custom-chips-ai-future

References:

https://www.wsj.com/tech/ai/amazons-custom-chips-pose-another-threat-to-nvidia-8aa19f5b

https://www.techradar.com/pro/meta-and-google-could-be-about-to-sign-a-mega-ai-chip-deal-and-it-could-change-everything-in-the-tech-space

https://www.wsj.com/tech/ai/nvidia-ai-chips-competitors-amd-broadcom-google-amazon-6729c65a

AI infrastructure spending boom: a path towards AGI or speculative bubble?

OpenAI and Broadcom in $10B deal to make custom AI chips

Reuters & Bloomberg: OpenAI to design “inference AI” chip with Broadcom and TSMC

RAN silicon rethink – from purpose built products & ASICs to general purpose processors or GPUs for vRAN & AI RAN

Dell’Oro: Analysis of the Nokia-NVIDIA-partnership on AI RAN

Cisco CEO sees great potential in AI data center connectivity, silicon, optics, and optical systems

Expose: AI is more than a bubble; it’s a data center debt bomb

China gaining on U.S. in AI technology arms race- silicon, models and research

 

Dell’Oro: Optical Transport Systems market +15% year-over-year in 3Q2025 driven by Cloud Service Providers

Posted on by Alan Weissberger

Dell’Oro Group recently published its 3Q25 Optical Transport report, highlighting continued strength in the market as demand accelerates across customer segments and technology areas. Below is a summary of the key findings from this latest research.

The Optical Transport Systems market increased by 15% year-over-year (Y/Y) in 3Q2025, driven by robust demand across all major customer groups and technology segments. The most significant growth was seen in Cloud Service Providers (CSPs) which grew +58% Y/Y and the DWDM Long Haul segment which grew +24% Y/Y.  Direct sales for data center interconnect (DCI) continued to be the driving application for optical transport equipment sales, growing 34% Y/Y. Non-DCI also performed well, rising 7% Y/Y, driven by increased spending by communication service providers (CSPs).

In the first nine months of 2025, two vendors—Ciena and Nokia—gained more than one percentage point of market share. Other vendors that gained some market share included 1Finity, Adtran, Cisco, and Smartoptics.  Note that Nokia acquired Infinera -a fiber optic equipment company on February 28, 2025.

Image Source:  Jimmy Yu, Dell’Oro Group

About the Report:

The Dell’Oro Group Optical Transport Quarterly Report offers complete, in-depth coverage of the market with tables covering manufacturers’ revenue, average selling prices, and unit shipments (by speed up to 1.6 Tbps). The report tracks DWDM long haul, WDM metro, multiservice multiplexers (SONET/SDH), data center interconnect (metro and long haul), disaggregated WDM systems, and IPoDWDM ZR/ZR+ Optics. To purchase this report, please contact us at [email protected].

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Backgrounder:

Optical Network Transport Equipment deals with managing, multiplexing, and routing optical signals.  Types of optical transport equipment include:
  • Optical Transceivers: Convert electrical signals into optical signals for transmission over fibers, and vice versa, at the endpoints of a link.
  • Wavelength Division Multiplexers (WDM/DWDM): Devices that combine multiple optical signals (each on a different wavelength) into a single fiber for transmission, and separate them at the receiving end, maximizing fiber capacity.
  • Optical Add/Drop Multiplexers (OADMs): Allow specific wavelengths (channels) to be added or removed from a fiber link at intermediate points in the network without interrupting the other channels.
  • Optical Cross-Connects (OXCs) / Optical Switches: Used to route optical signals from one incoming fiber to a different outgoing fiber in the optical domain, often used in core networks.
  • Regenerators / Optical Amplifiers (EDFAs): Used to amplify or regenerate optical signals over long distances to maintain signal strength and quality.
  • OTN Terminal Equipment / Muxponders & Transponders: These devices package client signals (like Ethernet, Fibre Channel, or even SONET/SDH signals) into the standard OTN frame format (ITU G.709) for efficient transport. 
Use of OTN and/or SONET/SDH:
Both OTN and SONET/SDH define the frame structure, overhead, and management protocols used to transport various client signals across an optical network. 
  • SONET/SDH: These are legacy, connection-oriented, circuit-switched technologies originally designed for carrying voice traffic in North America (SONET) and globally (SDH). They operate at the physical layer (Layer 1) and use Time Division Multiplexing (TDM).
    • Usage: They are still widely deployed in existing network infrastructure, especially where high reliability and stringent latency requirements for legacy TDM services are necessary.
  • OTN: OTN (ITU-T G.709 standard) is the modern successor, designed to combine the management and protection capabilities of SONET/SDH with the bandwidth efficiency of WDM.
    • Usage: OTN has largely replaced SONET/SDH in new core and metro networks due to its ability to transparently carry multiple types of traffic (Ethernet, IP, Fibre Channel, and SONET/SDH frames) over a single, high-capacity infrastructure. It offers enhanced performance monitoring, Forward Error Correction (FEC) for longer reach, and greater scalability.
In modern networks, OTN equipment can be configured to transport legacy SONET/SDH signals, allowing service providers to transition to new infrastructure while still supporting older services.
2025 vendor performance:
  • Huawei has consistently maintained a leading position in the global optical networking market.
  • Ciena is a major leader, particularly in North America (holding nearly 50% share in the U.S. market) and among cloud providers, benefiting from strong demand for its WaveLogic 6e and 400ZR/ZR+ solutions.
  • Nokia has significantly strengthened its position, becoming the second-largest optical networking vendor globally (with approximately 20% market share) following its acquisition of Infinera in February 2025. The combined company saw substantial growth in revenue from cloud customers.
  • Cisco saw a 31% increase in revenue from cloud operators in Q2 2025, a key driver of market growth.
  • ZTE and FiberHome are also among the top six, often noted for their competitive solutions in global and emerging markets.
  • Excluding sales into China, the leading vendors are Ciena, Huawei, Nokia, Infinera (now part of Nokia), and Fujitsu, accounting for around 80% of that specific market segment. 
These vendors are actively competing to meet the increasing demand from hyperscalers and communication service providers driven by AI and 5G network expansions

References:

Optical Transport Market Surges 15% in 3Q25, According to Dell’Oro Group

Dell’Oro: Optical Transport market to hit $17B by 2027; Lumen Technologies 400G wavelength market

LightCounting: Q1 2024 Optical Network Equipment market split between telecoms (-) and hyperscalers (+)

Highlights of LightCounting’s December 2023 Quarterly Market Update on Optical Networking

Dell’Oro: Optical Transport Market Down 2% in 1st 9 Months of 2021

Dell’Oro: Optical Transport Equipment Market Stagnant in 1Q 2021; Jimmy Yu’s Take

Dell’ Oro: Huawei still top telecom equipment supplier; optical transport market +1% in 2020

 

New Street Research study: Cable broadband will continue its decline, but total broadband access subscribers will increase

Posted on by Alan Weissberger

A recent New Street Research broadband trends study suggests that U.S. cablecos (previously called MSOs) aren’t likely to increase the net number of broadband internet subscribers during this decade, but their broadband losses are expected to decrease. The financial market research firm doesn’t anticipate cable broadband subscriber growth to be positive for at least another four to five years. Under New Street’s “base case,” cable broadband net adds will remain negative each year until 2030.   Cable broadband  is facing fierce competition on the high end from fiber to the premises (e.g. AT&T, Frontier/Verizon) and on the lower end from 5G FWA (e.g. T-MobileUS, Verizon).

Cable “is the new copper,” New Street Research analysts David Barden and Vikash Harlalka wrote, implying declining subscribers for xDSL based broadband will also happen to cablecos. Obviously, cablecos won’t like that characterization given that their hybrid fiber/coax (HFC) networks are mostly comprised of fiber. However, declining subscriber trends is not a commentary about the cable industry’s underlying broadband access network technology.

“With industry growth remaining below pre-pandemic levels and FWA adds remaining strong, we don’t expect Cable to grow subscribers this decade. Cable needs industry growth to improve and FWA adds to slow down to return to growth,” New Street’s analysts write in their 140-page report (subscribers only).  

New Street outlines potential scenarios for how cable’s share of the broadband market will look by 2030: 

  • Best case scenario – cable has 42% of the market as 84% of the market is divvied up between cable and fiber, while FWA gets 16%. 

  • Plausible scenario – cable retains 32% share of the broadband market, with 80% of it being shared with fiber, and FWA capturing 20%. 

  • Optimistic scenario – cable captures 50% of the broadband market, fueled by “superior marketing and cheaper mobile bundles,” compared to fiber (41%) and FWA (10%). 

New Street expects cable’s “steady state terminal market share” to be just a bit higher than 40% across its footprint, down from 62% today.

The report also takes a look at how cable will fare in markets that overlap with fiber. New Street estimates that 75% of cable markets will have a fiber competitor in the years to come. When combining non-fiber and fiber markets, cable is expected to capture about 41% of the share in their footprints. That compares to fiber (34%), FWA (20%), DSL (2%) and satellite broadband (3%).

It only gets worse for cablecos, as their customer net promoter scores (NPS) [1.] are lower than their competitors (mostly telcos). Using data from Recon Analytics’ weekly survey of about 10,000 respondents, New Street’s study notes there’s a pronounced customer NPS gap for cable against its primary broadband rivals.  Customer NPS scores from Comcast (2) and Charter (1) are just above water compared to Cox Communications (-1) and Optimum Communications (-8). Fiber providers are doing much better: AT&T Fiber (25), Verizon Fios (21), Frontier (17) and Lumen Fiber (1). FWA also holds a sizable customer NPS advantage: T-Mobile (31) and Verizon FWA (29).

Note 1. NPS is a customer loyalty metric that measures the likelihood of customers recommending a company to a friend or colleague, using a scale of \(0\)-\(10\). The score is calculated by subtracting the percentage of “detractors” (those who score \(0\)-\(6\)) from the percentage of “promoters” (those who score \(9\)-\(10\)), with “passives” (those who score \(7\)-\(8\)) not being factored into the final score. NPS is a single, easy-to-understand number that ranges from \(-100\) to \(+100\) and is used to gauge customer satisfaction and predict business growth. Customers are asked, “On a scale of \(0\)-\(10\), how likely are you to recommend [company] to a friend or colleague?”

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Considering all types of broadband access, New Street expects total net U.S. broadband net adds of 1.6 million, up from the 1.2 million from an earlier estimate. Fueled by fiber and FWA, net broadband subscriber adds are expected to continue above that level through 2030.

That growth will continue even as the market becomes increasingly saturated. New Street forecasts 139 million Internet households in 2030, up from 133 million at the end of 2025. Broadband penetration is expected to reach 93% by 2030, up from 87.7% at the end of 2025.

New Street expects U.S. network service providers to have 32 million to 36 million FWA subscribers in the coming years. However, the forecast expects a slight slowdown in FWA sub adds in 2026, coming in just below the range of 3.7 million to 3.8 million seen over the past three years. Next year, New Street expects FWA subscriber adds of 3.6 million (1.7 million for T-Mobile, 1 million for Verizon and 900,000 for AT&T). The analysts  estimate that the carriers currently have enough capacity to support about 32 million FWA subs, estimating that carriers have already consumed about 55% of total capacity with new subs. That estimate does not include potential capacity coming from the upcoming auction of upper C-Band spectrum. That auction could provide capacity for another 4 million or so additional FWA subs, New Street said.

Reason for Negative Broadband Cable Forecasts :
  • Intense Competition: Cable operators are losing subscribers to FTTH, which offers faster speeds and higher reliability, and FWA services, which often appeal to customers seeking lower-priced or easily installed options.
  • Market Saturation and Demographics: The broadband market is becoming increasingly saturated, and a slowdown in new household formation and people moving is curbing a key driver of new broadband connections.
  • End of Government Subsidies: The expiration of government programs like the Affordable Connectivity Program (ACP) is impacting subscriber numbers, with major cable operators losing customers who relied on the subsidy.
  • Network Upgrades: Cable companies are investing in network upgrades, such as DOCSIS 4.0, to improve speeds and performance, but it is not yet clear if these upgrades will significantly boost subscriber numbers.

Other Analyst Opinions:

  • MoffettNathanson sees flattish cable broadband subscriber growth for the next couple of years, with  a small gain in 2028.   The firm projects subscriber losses in legacy markets will be eventually offset by gains from rural expansions and edge-out builds.  “The conclusion for the two [Comcast and Charter] is about the same: even a near worst-case scenario yields roughly flat subscribership over the next five years or so,” Moffett wrote. “That’s a far cry from the doomsday scenarios we typically hear for the bear case.”

  • In February 2025, Wolfe Research estimated that total industry net broadband additions for 2025 would be under 2 million, with cable providers bearing much of the slowdown.
  • Grand View Research forecasts the global broadband services market (all connection types) to reach ~ US$ 875 billion by 2030, growing ~ 9.8% per year from 2025. In North America, broadband services revenue is expected to grow at ~ 8.3% CAGR from 2025 to 2030.
  • Mordor Intelligence forecasts that the global market for hybrid-fiber coaxial (HFC — the backbone for many cable networks) will grow a 7.6% CAGR from $14.96 billion in 2025 to ~ $21.58 billion in 2030.
  • An Ericsson analysis noted a projected decline of around 150 million DSL and cable connections globally between 2024 and 2030, with most growth coming from fiber, FWA, and satellite.

References:

https://www.lightreading.com/cable-technology/ouch-broadband-study-casts-cable-as-the-new-copper-

https://www.lightreading.com/cable-technology/cable-broadband-faces-a-flat-future-not-doomsday

https://telcomagazine.com/top10/top-10-global-fxxt-companies-in-telecoms

 

Tampnet to expand 5G offshore connectivity in the Gulf of Mexico using Nokia AirScale 5G radios

Posted on by Alan Weissberger

Tampnet, a global leader in offshore communications, is expanding its operations in the Gulf of Mexico and is now using Nokia AirScale 5G radios across its entire on-sea network of 120 active base stations, as well as extending coverage to 350-400 platforms, rigs, floating production storage and offloading (FPSO) units, wind farms and vessels.  While Telenor Maritime operates a 4G/5G-ready offshore mobile service for the oil and gas industry in the Norwegian section of the North Sea, Tampnet has spread its operations across several parts of the world, including off the coast of the U.S.

Building on the 2025 deployment of the world’s first fully autonomous private 5G edge network on an offshore production platform on the Norwegian continental shelf (NCS), this partnership extends that innovation to U.S. offshore, setting new benchmarks for connectivity, safety and digital transformation across the global offshore energy sector.

Art by midJourney for Fierce Network

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 Arnt Erling Skavdal, CTO of Mobile Technology, Tampnet: “With Nokia’s 5G technology, we are taking a significant step towards modernizing our offshore networks in the Gulf. This investment will enable us to meet the evolving connectivity and automation needs of offshore industries, enhance worker safety and unlock new digital applications that were not possible before.”

The Gulf of Mexico is a strategic region for Tampnet, where the company operates both private and public networks and manages critical subsea fiber that connects offshore assets to the mainland. Tampnet’s infrastructure forms the digital backbone of the region’s offshore activity, delivering reliable ultra-low latency, high-availability connectivity that supports safer, smarter and more sustainable operations from site to shore.

Nokia’s 5G AirScale Radio Access Network (RAN) equipment will enable offshore industries to implement advanced capabilities including real-time telemetry and monitoring, AI-driven predictive maintenance, and scalable industrial automation. Personnel in the Gulf region will benefit from high-performance private wireless connectivity, which will enhance operational safety and drive significant efficiency gains.

Jeff Pittman, Head of North America Enterprise, Mobile Networks, Nokia: “Our collaboration with Tampnet demonstrates how Nokia’s private wireless solutions are enabling digital transformation in some of the world’s most challenging environments. Together, we are setting new standards for offshore connectivity that will deliver long-term value to energy producers and their workforce.”

 

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Advanced applications of 5G in offshore industries leverage its high speed, low latency, and reliability to enable digital transformation, enhance safety, and optimize operations. Here are a few examples:
  • Real-time remote monitoring: Onshore control centers can monitor offshore equipment and facilities in real time using vast networks of IoT sensors and high-definition video surveillance, reducing the need for physical site visits.
  • AI-driven predictive maintenance: IoT sensors on critical infrastructure like pipelines, pumps, and wind turbines continuously stream performance and environmental data (e.g., vibration, temperature, pressure) over private 5G networks. AI analytics use this data to predict potential failures before they occur, minimizing costly downtime and extending asset lifespan.
  • Scalable industrial automation: 5G provides the reliable, low-latency connectivity necessary for automated systems, including autonomous guided vehicles (AGVs) in ports and robotic arms on platforms. This allows for complex, coordinated operations with minimal human intervention.
  • Autonomous inspection with drones and robots: Drones and unmanned ground vehicles (UGVs) equipped with high-resolution cameras and sensors perform inspections of hazardous or hard-to-reach areas, such as flare stacks or wind turbine blades. 5G enables the real-time data transmission and remote control required for these operations, keeping personnel out of harm’s way.
  • Augmented reality (AR) and virtual reality (VR) support: Field workers can use AR devices for guided maintenance and troubleshooting, receiving real-time instructions and collaboration from experts onshore. VR is also used for training and detailed visualization of digital twins.
  • Enhanced safety and crew communication: 5G-enabled safety systems, such as connected worker wearables (e.g., smart helmets, gas detectors), track personnel and environmental conditions in real time, providing instant alerts in case of incidents or hazards. This also facilitates reliable crew communication across vast operational zones.
  • Remote operation of equipment: With 5G’s ultra-low latency, operators can precisely control heavy machinery and underwater robots from remote locations, improving efficiency and safety.
  • Digital twins: The massive amounts of data collected via 5G networks feed into digital twin models of offshore assets (e.g., entire wind farms or rigs), allowing operators to simulate scenarios, optimize performance, and manage assets with unprecedented accuracy.
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About Nokia:  Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile, and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.

About Tampnet: Tampnet provides first-class, high-capacity connectivity to the global energy sector, enabling digitalization, efficiency, and sustainability. By operating the world’s largest offshore network, Tampnet delivers reliable and scalable high-capacity, low-latency connectivity solutions that support safer, smarter and more sustainable operations from site to shore. Through continuous innovation and focus on reduction of carbon footprint, Tampnet revolutionises offshore operations, contributing to a more sustainable energy production landscape. The company operates offshore telecom infrastructure in the North Sea and the Gulf of Mexico (Gulf of America). More than offshore energy installations, as well as a large number of mobile rigs and vessels, receive high-speed data communication by Tampnet.

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References:

https://www.nokia.com/newsroom/nokia-and-tampnet-partner-to-expand-5g-offshore-connectivity-in-the-gulf-of-mexico/

https://www.nokia.com/industries/oil-and-gas/

https://www.tampnet.com/gom

https://www.fierce-network.com/wireless/nokia-confirms-tampnet-5g-radio-deal

Nokia and Eolo deploy 5G SA mmWave “Cloud RAN” network

Nokia wins multi-billion dollar contract from Bharti Airtel for 5G equipment

Charter Communications selects Nokia AirScale to support 5G connectivity for Spectrum Mobile™ customers

Nokia in multi-year deal with Zain to provide 5G RAN equipment throughout Jordan

Telia’s mobile network with CBTC technology deployed in Oslo metro line

Posted on by Alan Weissberger

Telia is claiming a European first with the deployment of a digital signaling system on the Oslo metro that operates over the Nordic telecom operator’s commercial 4G/5G mobile network. Sporveien is the Oslo subway transport operator.

Developed by Siemens Mobility, the system uses communications-based train control (CBTC) technology to link trains, trackside equipment and central control systems. According to Telia, CBTC enables far more precise train-position tracking than legacy signaling platforms, allowing operators to safely reduce headways and run trains more closely together.

Morten Karlsen Sørby, acting Head of Telia Norway: “As far as we know, only the New York City Subway uses a mobile network as part of a signaling system. It places high demands on availability and service quality, and Telia is ready to deliver. We congratulate Sporveien on this new system, and we’re very proud of our innovative collaboration with both Sporveien and Siemens Mobility.”

Today’s launch is on the Oslo Metro’s line 4 between Brattlikollen and Bergkrystallen, with implementation across the entire subway scheduled for 2030. The current signaling system has been in place since the Metro opened in 1966.

Birte Sjule, CEO of Sporveien: “The subway can only operate with a well-functioning signaling system, so this project is extremely important for Oslo’s residents. By replacing technology that has passed its useful life, we’ll reap additional benefits such as more frequent departures and increased capacity in the years to come.”

The solution delivered to Sporveien is part of Telia’s Enterprise Mobile Network (EMN) portfolio, which offers advanced and customized connectivity services to support industrial digitalization.  EMN can use either 4G or 5G technology, or a combination, depending on the specific needs of the business.

Private 5G is now being integrated into CBTC systems to provide higher capacity, lower latency, and improved performance, especially in urban and high-demand environments. Companies are actively rolling out and testing CBTC with 5G, making it a next-generation standard for some new and retrofitted systems. 

References;

https://www.teliacompany.com/en/news/telias-mobile-network-signals-european-first-in-oslo-subway-2025-12-02-09-30-00

Ericsson and Telia said to provide lower 5G latency & power dissipation/longer battery life

Non-coherent Massive MIMO for High-Mobility Communications

Selected Applications/Use Cases by Industry for ITU-R International Mobile Telecommunications (IMT) – 3G, 4G & 5G

 

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