Author: Alan Weissberger
Omdia: How telcos will evolve in the AI era
Dario Talmesio, research director, service provider, strategy and regulation at market research firm Omdia (owned by Informa) sees positive signs for network operators.
“After many years of plumbing, now telecom operators are starting to see some of the benefits of their network and beyond network strategies. Furthermore, the investor community is now appreciating telecom investments, after many years of poor valuation, he said during analyst keynote presentation at Network X, a conference organized by Light Reading and Informa in Paris last week.
“What has changed in the telecoms industry over the past few years is the fact that we are no longer in a market that is in contraction,” he said. Although telcos are generally not seeing double-digit percentage increases in revenue or profit, “it’s a reliable business … a business that is able to provide cash to investors.”
Omdia forecasts that global telecoms revenue will have a CAGR of 2.8% in the 2025-2030 timeframe. In addition, the industry has delivered two consecutive years of record free cash flow, above 17% of sales.
Omdia found that that telcos have reduced capex, which is trending towards 15% of revenues. Opex fell by -0.2% in 2024 and is broadly flatlining. There was a 2.2% decline in global labor opex following the challenging trend in 2023, when labor opex increased by 4% despite notable layoffs.
“Overall, the positive momentum is continuing, but of course there is more work to be done on the efficiency side,” Talmesio said. He added that it is also still too early to say what impact AI investments will have over the longer term. “All the work that has been done so far is still largely preparatory, with visible results expected to materialize in the near(ish) future,” he added. His presentation covered addressed the following questions:
- How will telcos evolve their operating structures and shift their business focuses in the next 5 years?
- AI, cloud and more to supercharge efficiencies and operating models?
- How will big tech co-opetition evolve and impact traditional telcos?
Customer care was seen as the area first impacted by AI, building on existing GenAI implementations. In contrast, network operations are expected to ultimately see the most significant impact of agentic AI.
Talmesio said many of the building blocks are in place for telecoms services and future revenue generation, with several markets reaching 60% to 70% fiber coverage, and some even approaching 100%.
Network operators are now moving beyond monetizing pure data access and are able to charge more for different gigabit speeds, home gaming, more intelligent home routers and additional WiFi access points, smart home services such as energy, security and multi-room video, and more.
While noting that connectivity remains the most important revenue driver, when contributions from various telecoms-adjacent services are added up “it becomes a significant number,” Talmesio said.
Mobile networks are another important building block. While acknowledging that 5G has been something of a disappointment in the first five years of the deployment cycle, “this is really changing” as more operators deploy 5G standalone (5G SA core) networks, Omdia observed.
Talmesio said: “At the end of June, there were only 66 telecom operators launching or commercially using 5G SA. But those 66 operators are those operators that carry the majority of the world’s 5G subscribers. And with 5G SA, we have improved latency and more devices among other factors. Monetization is still in its infancy, perhaps, but then you can see some really positive progress in 5G Advanced, where as of June, we had 13 commercial networks available with some good monetization examples, including uplink.”
“Telecom is moving beyond telecoms,” with a number of new AI strategies in place. For example, telcos are increasingly providing AI infrastructure in their data centers, offering GPU as-a-service, AI-related colocation, AI-RAN and edge AI functionality.
Dario Talmesio, Omdia
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AI is also being used for network management, with AI productivity tools and AI digital assistants, as well as AI software services including GenAI products and services for consumer, enterprises and vertical markets.
“There is an additional boost for telecom operators to move beyond connectivity, which is the sovereignty agenda,” Talmesio noted. While sovereignty in the past was largely applied to data residency, “in reality, there are more and more aspects of sovereignty that are in many ways facilitating telecom operators in retaining or entering business areas that probably ten years ago were unthinkable for them.” These include cloud and data center infrastructure, sovereign AI, cyberdefense and quantum safety, satellite communication, data protection and critical communications.
“The telecom business is definitely improving,” Talmesio concluded, noting that the market is now also being viewed more favorably by investors. “In many ways, the glass is maybe still half full, but there’s more water being poured into the telecom industry.”
References:
https://networkxevent.com/speakers/dario-talmesio/
Omdia on resurgence of Huawei: #1 RAN vendor in 3 out of 5 regions; RAN market has bottomed
Omdia: Huawei increases global RAN market share due to China hegemony
Dell’Oro & Omdia: Global RAN market declined in 2023 and again in 2024
Omdia: Cable network operators deploy PONs
ITU-R WP 5D Timeline for submission, evaluation process & consensus building for IMT-2030 (6G) RITs/SRITs
The ITU-R WP 5D schedule described below applies to the first invitation for IMT 2030 candidate RITs [1] or SRITs [2]
[1] RIT =Radio Interface Technology [2] SRITs =Set of RITs. That terminology was used for IMT 2020 and the IMT 2150 recommendation
Submission of proposals may begin at 54th meeting of Working Party (WP) 5D, currently planned for February 2027. The final deadline for submissions is 1600 hours UTC, 12 calendar days prior to the start of the 59th meeting of WP 5D in February 2029.
The evaluation of the proposed RITs/SRITs by the independent evaluation groups and the consensus-building process will be performed throughout this time period and thereafter. Subsequent calendar schedules will be decided according to the submissions of proposals.
References:
https://www.itu.int/dms_pub/itu-r/oth/0a/06/R0A060000C80001PDFE.pdf
https://www.itu.int/rec/R-REC-M.2150/en
ITU-R WP5D IMT 2030 Submission & Evaluation Guidelines vs 6G specs in 3GPP Release 20 & 21
Highlights of 3GPP Stage 1 Workshop on IMT 2030 (6G) Use Cases
ITU-R WP 5D reports on: IMT-2030 (“6G”) Minimum Technology Performance Requirements; Evaluation Criteria & Methodology
ITU-R: IMT-2030 (6G) Backgrounder and Envisioned Capabilities
Verizon’s 6G Innovation Forum joins a crowded list of 6G efforts that may conflict with 3GPP and ITU-R IMT-2030 work
Ericsson and e& (UAE) sign MoU for 6G collaboration vs ITU-R IMT-2030 framework
ITU-R WP5D invites IMT-2030 RIT/SRIT contributions
NGMN issues ITU-R framework for IMT-2030 vs ITU-R WP5D Timeline for RIT/SRIT Standardization
IMT-2030 Technical Performance Requirements (TPR) from ITU-R WP5D
Should Peak Data Rates be specified for 5G (IMT 2020) and 6G (IMT 2030) networks?
IBM and Groq Partner to Accelerate Enterprise AI Inference Capabilities
IBM and Groq [1.] today announced a strategic market and technology partnership designed to give clients immediate access to Groq’s inference technology — GroqCloud, on watsonx Orchestrate – providing clients high-speed AI inference capabilities at a cost that helps accelerate agentic AI deployment. As part of the partnership, Groq and IBM plan to integrate and enhance RedHat open source vLLM technology with Groq’s LPU architecture. IBM Granite models are also planned to be supported on GroqCloud for IBM clients.
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Note 1. Groq is a privately held company founded by Jonathan Ross in 2016. As a startup, its ownership is distributed among its founders, employees, and a variety of venture capital and institutional investors including BlackRock Private Equity Partners. Groq developed the LPU and GroqCloud to make compute faster and more affordable. The company says it is trusted by over two million developers and teams worldwide and is a core part of the American AI Stack.
NOTE that Grok, a conversational AI assistant developed by Elon Musk’s xAI is a completely different entity.
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Enterprises moving AI agents from pilot to production still face challenges with speed, cost, and reliability, especially in mission-critical sectors like healthcare, finance, government, retail, and manufacturing. This partnership combines Groq’s inference speed, cost efficiency, and access to the latest open-source models with IBM’s agentic AI orchestration to deliver the infrastructure needed to help enterprises scale.
Powered by its custom LPU, GroqCloud delivers over 5X faster and more cost-efficient inference than traditional GPU systems. The result is consistently low latency and dependable performance, even as workloads scale globally. This is especially powerful for agentic AI in regulated industries.
For example, IBM’s healthcare clients receive thousands of complex patient questions simultaneously. With Groq, IBM’s AI agents can analyze information in real-time and deliver accurate answers immediately to enhance customer experiences and allow organizations to make faster, smarter decisions.
This technology is also being applied in non-regulated industries. IBM clients across retail and consumer packaged goods are using Groq for HR agents to help enhance automation of HR processes and increase employee productivity.
“Many large enterprise organizations have a range of options with AI inferencing when they’re experimenting, but when they want to go into production, they must ensure complex workflows can be deployed successfully to ensure high-quality experiences,” said Rob Thomas, SVP, Software and Chief Commercial Officer at IBM. “Our partnership with Groq underscores IBM’s commitment to providing clients with the most advanced technologies to achieve AI deployment and drive business value.”
“With Groq’s speed and IBM’s enterprise expertise, we’re making agentic AI real for business. Together, we’re enabling organizations to unlock the full potential of AI-driven responses with the performance needed to scale,” said Jonathan Ross, CEO & Founder at Groq. “Beyond speed and resilience, this partnership is about transforming how enterprises work with AI, moving from experimentation to enterprise-wide adoption with confidence, and opening the door to new patterns where AI can act instantly and learn continuously.”
IBM will offer access to GroqCloud’s capabilities starting immediately and the joint teams will focus on delivering the following capabilities to IBM clients, including:
- High speed and high-performance inference that unlocks the full potential of AI models and agentic AI, powering use cases such as customer care, employee support and productivity enhancement.
- Security and privacy-focused AI deployment designed to support the most stringent regulatory and security requirements, enabling effective execution of complex workflows.
- Seamless integration with IBM’s agentic product, watsonx Orchestrate, providing clients flexibility to adopt purpose-built agentic patterns tailored to diverse use cases.
The partnership also plans to integrate and enhance RedHat open source vLLM technology with Groq’s LPU architecture to offer different approaches to common AI challenges developers face during inference. The solution is expected to enable watsonx to leverage capabilities in a familiar way and let customers stay in their preferred tools while accelerating inference with GroqCloud. This integration will address key AI developer needs, including inference orchestration, load balancing, and hardware acceleration, ultimately streamlining the inference process.
Together, IBM and Groq provide enhanced access to the full potential of enterprise AI, one that is fast, intelligent, and built for real-world impact.
References:
FT: Scale of AI private company valuations dwarfs dot-com boom
AI adoption to accelerate growth in the $215 billion Data Center market
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Will billions of dollars big tech is spending on Gen AI data centers produce a decent ROI?
Can the debt fueling the new wave of AI infrastructure buildouts ever be repaid?
OneLayer Raises $28M Series A funding to transform private 5G networks with enhanced security
Private network security startup OneLayer has scored $28 million in series A funding led by Maor Investments with participation from McRock Capital, Chevron Technology Ventures and existing investors Viola Ventures, Grove Ventures and Koch Disruptive Technologies. The Series A round brings total funding to more than $43 million.
The Boston, MA headquartered firm says they are the leader in private LTE/5G OT management and Zero Trust security. The security startup’s major rivals include Fortinet, Juniper Networks and Trend Micro.
“Private 5G represents a massive market opportunity, with enterprise demand far outpacing the industry’s ability to deliver simple, secure solutions,” said Ido Hart, Partner at Maor. “OneLayer solves this by translating cellular networks into enterprise IT language, eliminating the need for specialized cellular expertise. At its core, OneLayer is building the essential infrastructure layer that will make private 5G as ubiquitous as WiFi or any LAN.”
OneLayer’s mission is to secure and manage all private cellular network devices with enterprise-grade capabilities while eliminating the need for specialized cellular expertise. The company’s platform transforms private cellular environments from operational silos into integrated enterprise networks, providing complete device visibility, security, and control through familiar IT management tools.
The funding round was highly competitive and oversubscribed, reflecting strong investor confidence in OneLayer’s vision and proven momentum. OneLayer has demonstrated significant market traction across multiple verticals, including utilities, manufacturing, mining, airports, and critical infrastructure, with proven deployments spanning across North America, Europe and Latin America. This includes major expansions at leading fortune 100 manufacturers, with enterprises scaling from initial deployments to comprehensive multi-site deployments spanning numerous facilities.
“Enterprises are deploying private cellular networks at unprecedented scale, but they’re struggling with device visibility, security gaps, and operational complexity that didn’t exist with traditional IT infrastructure,” said Dave Mor, CEO and Co-Founder of OneLayer. “The demand for solutions that bridge this gap is explosive, customers need to manage thousands of cellular-connected devices with the same confidence and control they have over their existing IT assets. Private LTE/5G is fast becoming a dominant enterprise network. Organizations need to manage and secure it within their current network setup. We established OneLayer to bridge this gap and create one layer of security and one layer of asset management across all organization networks.” Mor added.
“OneLayer enables secure private 5G for industrial automation and autonomy – the foundation Industrial AI needs to scale,” said Scott MacDonald, Co-founder & Managing Partner of McRock Capital. “Private cellular networks represent the next wave of digital transformation, but connectivity without security is a house of cards. OneLayer provides the missing layer of trust that enterprises need to adopt private 5G with confidence.”
“OneLayer’s software platform holds promise to improve private cellular network reliability and integration for industrial companies, offering better visibility, cost efficiency and security,” said Jim Gable, Vice President of Innovation within Chevron’s Technology, Projects and Execution division and President of Technology Ventures at Chevron. “This is the latest investment from our Core Venture Fund, which focuses on high-growth startups and breakthrough technologies that have the potential to improve Chevron’s core businesses, as well as create new opportunities for growth. We welcome OneLayer to the portfolio.”
“Since coming out of stealth mode in 2022, OneLayer has gone from strength to strength, raising more than $43 million to date,” SNS Telecom & IT 5G research director, Asad Khan, told Fierce.
OneLayer’s platform has proven essential for organizations deploying private LTE and 5G networks at scale. Notable deployments include:
- Southern Linc’s regional LTE network spanning 122,000 square miles across Alabama, Georgia, and southeastern Mississippi, supporting diverse devices from grid control systems to mission-critical push-to-talk services.
- Evergy’s private LTE network, built to eventually cover their 1.7 million customers in Kansas and Missouri; currently supporting thousands of devices, including Internet of Things (IoT) sensors, smart meters, OT and other cellular devices.
- Latin America mining operations where OneLayer enabled automated processes, improved operational efficiency, and secure deployment of new production sites through comprehensive device discovery, classification, and network segmentation.
OneLayer’s comprehensive partner ecosystem spans the entire private cellular value chain, from cellular leaders Nokia and Ericsson to leading cellular router manufacturers Digi, Cradlepoint, and Multitech; CMDBs ServiceNow and SolarWinds; channel partners and integrators World Wide Technology (WWT), Burns & McDonnell (B&M), Anterix, and Future Technologies; and leading cybersecurity vendors such as Palo Alto Networks, Fortinet, Checkpoint, Claroty, and more.
Adding to the strong revenues from its expanding customer base, the company will use the Series A funding to:
- Accelerate go-to-market initiatives in response to surging enterprise demand
- Expand product capabilities to provide customers a platform that solves their critical operational pains
- Scale geographic expansion beyond North America following successful entry into Latin American markets, and further expand European operations
OneLayer’s growth reflects the broader market transformation as private cellular networks evolve from carrier-grade infrastructure to enterprise-managed networks. With partnerships across major 5G vendors and proven success in critical verticals and leading enterprises, OneLayer has become the defacto solution for managing and securing the rapidly expanding private cellular market.
About OneLayer
OneLayer provides advanced asset management, operational intelligence, and Zero Trust security for private LTE and 5G networks. Its technology empowers enterprises to manage their cellular networks seamlessly without the need for cellular expertise. For more information, visit www.onelayer.com. Media Contact: [email protected]
References:
FT: Scale of AI private company valuations dwarfs dot-com boom
The Financial Times reports that ten loss making artificial intelligence (AI) start-ups have gained close to $1 trillion in private market valuation in the past 12 months, fuelling fears about a bubble in private markets that is much greater than the dot com bubble at the end of the 20th century. OpenAI leads the pack with a $500 billion valuation, but Anthropic and xAI have also seen their values march higher amid a mad scramble to buy into emerging AI companies. Smaller firms building AI applications have also surged, while more established businesses, like Databricks, have soared after embracing the technology.
U.S. venture capitalists (VCs) have poured $161 billion into artificial intelligence startups this year — roughly two-thirds of all venture spending, according to PitchBook — even as the technology’s commercial payoff remains elusive. VCs are on track to spend well over $200bn on AI companies this year.
Most of that money has gone to just 10 companies, including OpenAI, Anthropic, Databricks, xAI, Perplexity, Scale AI, and Figure AI, whose combined valuations have swelled by nearly $1 trillion, Financial Times calculations show. Those AI start-ups are all burning cash with no profits forecasted for many years.
Start-ups with about $5mn in annual recurring revenue, a metric used by fast-growing young businesses to provide a snapshot of their earnings, are seeking valuations of more than $500mn, according to a senior Silicon Valley venture capitalist.
Valuing unproven businesses at 100 times their earnings or more dwarfs the excesses of 2021, he added: “Even during peak Zirp [zero-interest rate policies], these would have been $250mn-$300mn valuations.”
“The market is investing as if all these companies are outliers. That’s generally not the way it works out,” he said. VCs typically expect to lose money on most of their bets, but see one or two pay the rest off many times over.
“There will be casualties. Just like there always will be, just like there always is in the tech industry,” said Marc Benioff, co-founder and chief executive of Salesforce, which has invested heavily in AI. He estimates $1tn of investment on AI might be wasted, but that the technology will ultimately yield 10 times that in new value.
“The only way we know how to build great technology is to throw as much against the wall as possible, see what sticks, and then focus on the winners,” he added.
“Of course there’s a bubble,” said Hemant Taneja, chief executive of General Catalyst, which raised an $8 billion fund last year and has backed Anthropic and Mistral. “Bubbles align capital and talent around new trends. There’s always some destruction, but they also produce lasting innovation.”
Venture investors have weathered cycles of boom and bust before — from the dot-com crash in 2000 to the software downturn in 2022 — but the current wave of AI funding is unprecedented. In 2000, VCs invested $10.5 billion in internet startups; in 2021, they deployed $135 billion into software firms. This year, they are on pace to exceed $200 billion in AI. “We’ve gone from the doldrums to full-on FOMO,” said one investment executive.
OpenAI and its start-up peers are competing with Meta, Google, Microsoft, Amazon, IBM, and others in a hugely capital-intensive race to train ever-better models, meaning the path to profitability is also likely to be longer than for previous generations of start-ups.
Backers are betting that AI will open multi-trillion-dollar markets, from automated coding to AI friends or companionship. Yet some valuations are testing credulity. Startups generating about $5 million in annual recurring revenue are seeking valuations above $500 million, a Silicon Valley investor said — 100 times revenue, surpassing even the excesses of 2021. “The market is behaving as if every company will be an outlier,” he said. “That’s rarely how it works.”
The enthusiasm has spilled into public markets. Shares of Nvidia, AMD, Broadcom, and Oracle have collectively gained hundreds of billions in market value from their ties to OpenAI. But those gains could unwind quickly if questions about the startup’s mounting losses and financial sustainability persist.
Sebastian Mallaby, author of The Power Law, summed it up beautifully:
“The logic among investors is simple — if we get AGI (Artificial General Intelligence, which would match or exceed human thinking), it’s all worth it. If we don’t, it isn’t…. “It comes down to these articles of faith about Sam’s (Sam Altman of OpenAI) ability to work it out.”
References:
https://www.ft.com/content/59baba74-c039-4fa7-9d63-b14f8b2bb9e2
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Can the debt fueling the new wave of AI infrastructure buildouts ever be repaid?
Amazon’s Jeff Bezos at Italian Tech Week: “AI is a kind of industrial bubble”
Gartner: AI spending >$2 trillion in 2026 driven by hyperscalers data center investments
AI Data Center Boom Carries Huge Default and Demand Risks
Canalys & Gartner: AI investments drive growth in cloud infrastructure spending
Ericsson’s revenue drops, profits soar; deal with Vodafone and partnership with Export Development Canada look promising
Ericsson’s 3rd quarter 2025 results released today showed a 9% drop in revenues, to 56.2 billion Swedish kronor (US$5.9 billion), compared with the same period last year. Ericsson’s gross margin rose 2% to 47.6%. U.S. sales fell by as much as 17% year-over-year for the 3rd quarter, to about SEK22.5 billion ($2.4 billion), after an especially busy period in 2024. And the only region where Ericsson realized any growth was northeast Asia, and that was due to Japan’s new 5G rollout.
At Ericsson’s big mobile networks unit, sales fell 11% year-over-year, to SEK35.4 billion ($3.7 billion), while the decline on a constant-currency basis was just 4%. The division’s operating income also slid by 6%, to SEK7.1 billion ($740 million).
Sales were much better at the company’s cloud software and services group, responsible for the development of Ericsson’s core network software as well as its business and operational support systems. Reported sales rose 3%, to SEK15.3 billion ($1.6 billion), while Ericsson put the organic improvement at 9%. More importantly, it swung from an operating loss of SEK400 million ($42 million) a year earlier to a profit of SEK1.7 billion ($180 million).
Net income soared by an astonishing 191%, to SEK11.3 billion ($1.2 billion). That sharp increase in net income was due to Ericsson’s recent sale of iconectiv, a provider of number-portability and data-exchange services, to a private equity firm. The deal landed Ericsson a capital gain of SEK7.6 billion ($800 million) that flattered its profits at the operating income level. In Stockholm, Ericsson’s share price soared more than 14% in mid-morning trade, although it remained almost 2% below its level at the start of the year.
CEO Börje Ekholm said on today’s earnings call: “The margin expansion reflects actions we’ve taken over the last years to increase operational excellence and efficiency, including the work we’ve done on our cost base. Over the last year, we’ve reduced our headcount by some 6,000, leveraging new ways of working, and that of course includes AI.”
Since the end of 2022, the year Ericsson acquired VoIP software developer Vonage for $6.2 billion, headcount has fallen by more than 15,600, to just 89,898 at the end of June, the company revealed in its latest earnings report.
The Vonage business suffered a 17% drop in sales, to SEK3.2 billion ($330 million), and saw its loss widen by 50%, to SEK600 million ($63 million). It is where Ericsson believes it can monetize the network application programming interfaces (APIs) that will link software apps to networks and hopefully revitalize the 5G market. However, that’s not happening yet.
“The geopolitical situation has required us to shift resources a bit politically. As we went through that transition, we duplicated a large part of the R&D spend. We don’t need to have that anymore as we have relocated R&D,” said Ekholm. “We are not going to jeopardize technology leadership and if we feel there is any risk – and that is a risk I don’t see today – then we would of course need to reassess.”
After years of growth, R&D spending fell by 10% year-over-year for the first nine months of 2025, to SEK35.8 billion ($3.8 billion), prompting concern among analysts that Ericsson could lose competitiveness versus Chinese rivals.
AI is now being used to refine the algorithms that are fed into Ericsson’s software products, said Per Narvinger, the head of Ericsson’s mobile networks business group, on a call with Light Reading. No indication was given if that would reduce headcount any further.
Ericsson hopes the new 5G contract it announced with Vodafone earlier today will boost sales in Europe, where underinvestment in midband 5G coverage and the “standalone” variant of 5G have been constant bugbears for the company. After the rollout of “non-standalone” 5G, which maintains the 4G core, operators just continued to sell a “4G plus” service, Ekholm said.
“It was the established business model of most operators around the world, so it became very natural to take that step and then use 5G almost as a marketing icon on the phone, but, in reality, it didn’t give the extra capabilities,” he added. Standalone features such as low latency and network slicing will be critical in future apps, Ekholm correctly said, arguing that 6G will necessitate edge cloud and AI investments that have also not yet happened.
In summing up, Ericsson said “Increased uncertainty remains on the outlook, both in terms of potential for further tariff changes as well as in the broader macroeconomic environment.”
Looking ahead:
– Continue to invest in technology leadership to strengthen competitive position
– Future-proofed Open RAN-ready portfolio
– New use cases to monetize network investments taking shape
● AI applications becoming a key driver for network investments
● Structurally improving the business through rigorous cost management
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Separately,
Ericsson today announced the signing of a USD $3 billion partnership agreement with Export Development Canada (EDC) to expand investment in Canadian research and development, deepen domestic supply chains, and accelerate next-generation technologies including 5G, Cloud RAN, AI, and quantum innovation.
Börje Ekholm, President and CEO, Ericsson, says: “Canada is one of Ericsson’s most important hubs for global research and development, and this partnership with Export Development Canada will allow us to scale that leadership even further. By strengthening our collaboration with Canadian businesses, universities and government partners, we can accelerate breakthroughs in 5G, quantum, and Cloud RAN that will drive growth, create opportunities, and reinforce Canada’s position as a global leader in next generation networks.”
With more than 3,100 employees nationwide and R&D centres in Ottawa, Montreal, and Toronto, Ericsson Canada is at the heart of the company’s global innovation footprint. Canadian teams are driving advancements in 5G, 5G Advanced, and 6G, while also contributing to new research in quantum communications and AI-powered network management.
The three-year partnership will enable Ericsson to expand its Canadian-led innovation and global projects with the support of financial and insurance solutions from EDC. By reinforcing Ericsson’s Canadian supply chain and connecting the company with innovative domestic businesses, the agreement will also amplify Ericsson’s ability to bring Canadian technology to the world, strengthen competitiveness, and create new opportunities for Canadian companies within Ericsson’s global network of partners.
Across all wireless network equipment vendors, annual sales of RAN products fell from $45 billion in 2022 to $35 billion last year, according to Omdia, a Light Reading sister company. Market research firms Omdia and Dell’Oro have encouragingly guided for a more stable market this year.
Most wireless network providers have seen no incentive to spend more on 5G when their returns to date have been so disappointing. And there is skepticism about the business case for low latency services and network slicing. Telcos increasingly sell large bundles of gigabytes to their customers and have struggled to monetize other features.
References:
https://www.lightreading.com/5g/ericsson-says-world-is-flat-amid-us-gloom-and-keeps-cutting
https://www.ericsson.com/en/press-releases/6/2025/ericsson-edc-advance-canadas-technology-leadership
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OCP 2025 Meta keynote: Scaling the AI Infrastructure to Data Center Regions
At the OCP Global Summit 2025 in San Jose, CA, Meta detailed its strategy for scaling AI infrastructure to regional data center deployments, emphasizing open, collaborative, and highly scalable designs to support growing AI workloads. The October 14th keynote presentation by Meta’s VP of Data Center Infrastructure, Dan Rabinovitsj, discussed strategies for deploying and operating AI at scale across various data center regions at OCP 2025. The session highlighted innovations for building AI-ready data centers, focusing on open hardware, power innovation, and challenges in next-generation AI infrastructure.
Initiatives discussed included: new Ethernet standards for AI clusters, integration of the Ultra Ethernet Consortium standard, Meta’s vision for open networking hardware, AMD’s “Helios” rack-scale AI platform, MSI’s integrated OCP solutions, next-gen liquid cooling, and solutions for distributed and edge AI.
Rabinovitsj highlighted Meta’s contributions to open standards and hardware innovations, including the Open Rack Wide standard and advanced networking concepts for AI clusters.
Meta also announced several new milestones for data center networking:
- The evolution of Disaggregated Scheduled Fabric (DSF) to support scale-out interconnect for large AI clusters that span entire data center buildings.
- A new Non-Scheduled Fabric (NSF) architecture based entirely on shallow-buffer, disaggregated Ethernet switches that will support our largest AI clusters like Prometheus.
- The addition of Minipack3N, based on NVIDIA’s Ethernet Spectrum-4 ASIC, to our portfolio of 51 Tbps OCP switches that use OCP’s SAI and Meta’s FBOSS software stack.
- The launch of the Ethernet for Scale-Up Networking (ESUN) initiative, focused on making Ethernet suitable for connecting high-performance processors, or GPUs, within a single rack by emphasizing requirements like low latency, high bandwidth, and lossless transfers. Meta has been working with other large-scale data center operators and leading Ethernet vendors to advance using Ethernet for scale-up networking (specifically the high-performance interconnects required for next-generation AI accelerator architectures.
OCP Summit 2025: The Open Future of Networking Hardware for AI
- Open Rack Wide (ORW) standard: Meta introduced the ORW specification, a new open standard for double-wide equipment racks designed to meet the extreme power, cooling, and serviceability demands of next-generation AI systems. AMD, a partner of Meta, showcased its “Helios” rack-scale platform built to be compliant with this new standard.
- Networking fabrics for AI clusters: Meta detailed its networking architecture, revealing the following innovations:
- Disaggregated Scheduled Fabric (DSF): An updated version of DSF was discussed (see below), which now provides non-blocking interconnects for clusters of up to 18,432 XPUs (AI processors), enabling communication between a larger number of GPUs.
- Non-Scheduled Fabric (NSF): Meta unveiled NSF, a new fabric for its largest AI clusters, which runs on shallow-buffer, disaggregated Ethernet switches to reduce latency. NSF is planned for Meta’s upcoming multi-gigawatt “Prometheus” clusters. See next section below for details.
- FBNIC: Meta announced FBNIC, a network ASIC of their own design.
- 51T switches: Meta revealed new 51T network switches, which utilize Broadcom and Cisco ASICs.
- Next-generation optical connections: For faster and higher-capacity optical interconnections, Meta discussed its adoption of 2x400G FR4-LITE and 400G/2x400G DR4 optics for its 400G and 800G connectivity.
- Sustainable hardware: As part of its 2030 net-zero goals, Meta presented a new AI-powered methodology for tracking and estimating the carbon emissions of its IT hardware. The methodology will be open-sourced for the wider industry
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Deep Dive into DSF and NSF:
- Non-blocking scale: An updated, two-stage architecture for DSF can now support a non-blocking fabric for up to 18,432 XPUs (AI processors). This allows all-to-all communication between a significantly larger number of GPUs without performance degradation.
- Proactive congestion avoidance: DSF uses a Virtual Output Queue (VOQ)-based system to manage traffic flow. By scheduling traffic between endpoints, it proactively avoids congestion before it occurs, which improves bandwidth delivery and overall network efficiency.
- Open and standardized: The fabric is built on open standards like the OCP-SAI (Switch Abstraction Interface) and is managed by Meta’s own network operating system, FBOSS. This vendor-agnostic approach allows Meta to use components from different suppliers and avoid vendor lock-in.
- Optimal load balancing: Traffic is “sprayed” across all available links and switches, ensuring an equal load and smooth performance for bandwidth-intensive workloads like AI training.
- Low latency: Unlike DSF, which relies on scheduling, NSF operates on shallow-buffer, disaggregated Ethernet switches. This reduces round-trip latency, making it ideal for the most latency-sensitive AI workloads.
- Adaptive routing: The NSF architecture is a three-tier fabric that supports adaptive routing for effective load-balancing. This helps minimize congestion and ensure optimal utilization of GPUs, which is critical for maximizing performance in Meta’s largest AI factories.
- Disaggregated design: Like DSF, NSF is built on a disaggregated design. This allows Meta to scale its network by using interchangeable, industry-standard components instead of a single vendor’s closed system.
- DSF: Provides a high-efficiency, highly scalable network for its large, but still modular, AI clusters.
- NSF: Is optimized for the extreme demands of its largest, gigawatt-scale “AI factories” like Prometheus, where low latency and robust adaptive routing are paramount.
Image Credit: Meta
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References:
OCP Summit 2025: The Open Future of Networking Hardware for AI
Networking at the Heart of AI — @Scale: Networking 2025 Recap
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Gartner: AI spending >$2 trillion in 2026 driven by hyperscalers data center investments
AI Data Center Boom Carries Huge Default and Demand Risks
Analysis: Cisco, HPE/Juniper, and Nvidia network equipment for AI data centers
Qualcomm to acquire Alphawave Semi for $2.4 billion; says its high-speed wired tech will accelerate AI data center expansion
Cisco CEO sees great potential in AI data center connectivity, silicon, optics, and optical systems
Data Center Networking Market to grow at a CAGR of 6.22% during 2022-2027 to reach $35.6 billion by 2027
InterDigital led consortium to advance wireless spectrum coexistence & sharing
InterDigital, Inc, a mobile, video and AI technology research and development company, was awarded a contract by the U.S. Department of War (DoW) to lead research and conduct demonstrations of advanced spectrum coexistence for civil and military applications. Spectrum sharing optimizes the use of the airwaves, or wireless communications channels, by enabling multiple categories of users to safely share the same frequency bands.
A consortium led by InterDigital, including DeepSig, Skylark Wireless, Virginia Tech, and Radisys, will endeavor to advance spectrum coexistence. The collaboration will focus on developing and testing new technologies that leverage artificial intelligence, advanced sensing, and commercial 5G systems. The need for this work stems from the high demand for mid-band frequencies, which are essential for both defense radar and commercial wireless applications due to their balance of coverage and capacity. The goal is to enhance dynamic spectrum sharing performance, ensuring national security radar systems can function without interference while enabling commercial 5G to operate in the same frequency bands.
The consortium plans to develop new technologies that will enable government and industry systems to “more seamlessly coexist.” Examples are given as low-latency AI-based distributed spectrum sensing and interference mitigation operations performed locally at cellular base stations and user equipment.
“InterDigital’s heritage of research has produced innovations that make it possible for radar and communications to coexist in ways that were not feasible,” said InterDigital CTO Rajesh Pankaj. “Building on our groundbreaking work in sensing and AI integration, we can foster greater collaboration between government and industry to achieve more efficient sharing of one of our most valuable resources. We look forward to working with the DoW and alongside these esteemed partners and suppliers.”
“DeepSig is proud to support the DoW and InterDigital in advancing dynamic spectrum sharing technologies,” said DeepSig CEO Jim Shea. “Our AI-native spectrum sensing and communications software was developed to help meet this need and brings the speed, accuracy and adaptability needed to ensure that critical defense systems and commercial 5G networks can safely and efficiently coexist. This project represents an important step toward unlocking the full potential of mid-band spectrum for both national security and next-generation connectivity, and offers to help unlock future band-sharing for 6G and beyond.”
Skylark Director of Business Development & Product Samir Rahi added: “Skylark is pleased to have been selected as a collaborator for the DoW and InterDigital’s coalition of US-based partners to support dynamic spectrum-sharing solutions. This activity builds upon Skylark’s prior success in related DoW programs. Specifically, our flexible architecture for last-mile connectivity is designed to integrate best-of-breed technologies in real-time, from partners such as InterDigital and DeepSig, at the pace of innovation required to support national interests. Skylark believes the DoW’s initiatives such as this represent the United States’ emerging capabilities in deploying dynamic spectrum-sharing at scale, providing dual use benefits for the commercial sector while simultaneously advancing national security objectives.”
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This project will leverage InterDigital’s proven foundational dynamic spectrum sharing technologies, which have been successfully demonstrated in commercial deployments and validated through prior government initiatives. The team will build upon this baseline with new and innovative technologies, including low-latency AI-based distributed spectrum sensing and interference mitigation operations performed locally at cellular base stations and user equipment. These new technologies will enable government and industry systems to more seamlessly coexist.
Image Credit: Blue Planet Studio SHUTTERSTOCK
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About InterDigital®
InterDigital is a global research and development company focused primarily on wireless, video, artificial intelligence (“AI”), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. We license our innovations worldwide to companies providing such products and services, including makers of wireless communications devices, consumer electronics, IoT devices, cars and other motor vehicles, and providers of cloud-based services such as video streaming. As a leader in wireless technology, our engineers have designed and developed a wide range of innovations that are used in wireless products and networks, from the earliest digital cellular systems to 5G and today’s most advanced Wi-Fi technologies. We are also a leader in video processing and video encoding/decoding technology, with a significant AI research effort that intersects with both wireless and video technologies. Founded in 1972, InterDigital is listed on Nasdaq.
InterDigital is a registered trademark of InterDigital, Inc.
For more information, visit: www.interdigital.com.
InterDigital Contact:Roya StephensEmail: [email protected] +1 (202) 349-1714
About DeepSig, Inc.DeepSig is a pioneer in AI native wireless communications which are helping to shape 6G. Its transformative technology pushes the boundaries of spectrum sensing, wireless performance and network capabilities. Drawing on its expertise in deep learning, wireless systems and signal processing, DeepSig’s AI/ML-powered software enhances security, efficiency and capacity for tactical and commercial wireless communications in licensed or shared radio spectrum and in existing 5G Open RAN or AI native next generation 6G networks.
For more information, visit: https://www.deepsig.ai/
DeepSig Contact: [email protected]
About Skylark Wireless
Skylark Wireless is building the interface between the physical and digital worlds by connecting industrial, enterprise, and public sector customers through a dynamic, converged communications platform. The company designs and manufactures US-assembled critical infrastructure for last-mile connectivity that combines patented techniques to improve range, performance, and interference mitigation with a fully software-defined radio architecture. This fusion of efficiency and flexibility uniquely supports an ever-growing collection of value-add use cases as networks evolve from 5G to 6G and beyond. To learn more about Skylark’s connectivity solution, please contact [email protected]
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Other Spectrum Activities:
- Earlier in 2025, the GSMA’s global 5G spectrum landscape stated mid-band remains the backbone of 5G deployments, while interest in both low-band and mmWave “continues to evolve in line with network strategies and future 6G planning.”
- ITU-R WP 5D develops the methodologies for carrying out sharing and coexistence studies between IMT and other radio services, such as broadcasting and satellite services. These studies address issues like potential interference and define separation criteria and technical conditions for coexistence.
- WP 5D’s work also addresses the evolution of spectrum management to incorporate more efficient techniques like dynamic spectrum access (DSA).
- As part of its process, WP 5D collaborates with and receives input from various external organizations, research communities, and other ITU-R Working Parties. This collaborative approach ensures that the spectrum management and coexistence frameworks for IMT systems are robust and informed by diverse perspectives.
References:
InterDigital to Lead Research and Demonstrate Advanced Spectrum Coexistence; DeepSig to Partner
https://www.nist.gov/spectrum-sharing
Why Spectrum Sharing is Critical for the Future of Connectivity
mmWave Coalition on the need for very high frequency spectrum; DSA on dynamic spectrum sharing in response to NSF RFI
Big 5G Conference: 6G spectrum sharing should learn from CBRS experiences
AT&T deploys nationwide 5G SA while Verizon lags and T-Mobile leads
In a blog published today (October 8th), Yigal Elbaz, AT&T’s senior VP and network CTO, AT&T announced its 5G Standalone (SA) network is now deployed nationwide, marking an important milestone many years in the making. Elbaz described the 5G SA nationwide deployment as “another bold leap” in wireless connectivity and said the operator is moving customers onto the network “in select areas every day.”
In fact, that “bold leap” was expected to be realized years ago! In 2021, AT&T partnered with Microsoft to offload its mobile 5G Standalone (SA) core network and other network cloud operations to Microsoft Azure, acquiring AT&T’s Network Cloud technology, software, and network operations team in the process. The goal was for Microsoft to manage the software development and deployment of AT&T’s network functions on Azure, allowing AT&T to accelerate innovation, improve efficiency, and reduce operating costs. This move has provided a strategic win for Microsoft’s Azure for Operators division by integrating AT&T’s technology and offering it to other telecom companies.
AT&T said they have millions of customers already on their 5G SA network, and we’re expanding availability to more customers as device support and provisioning allow. Elbaz elaborated:
5G Standalone networks have now reached a level of maturity that enables our nationwide expansion. This growth is powered by an open and virtualized network, which enables us to scale efficiently and foster collaboration within an open ecosystem of partners. By embracing this open and virtualized network architecture, we are not only modernizing our infrastructure but also unlocking significant advantages for our customers and partners. This approach not only accelerates our ability to roll out new technologies like 5G Standalone but also helps ensure our customers benefit from a network that is robust, innovative, and designed with their needs in mind.
With 5G Standalone now nationwide, we’ve set the stage for the next wave of innovation, creativity, and connection. I couldn’t be prouder of our teams who made this possible, and we’ll continue to scale 5G Standalone over time and set the stage for next generation applications and services.
Compatible 5G SA smartphones include models released in the last several years starting with Apple’s iPhone 13, Samsung’s Galaxy S21 and Google’s Pixel 8.
AT&T also said its 5G Reduced Capability (RedCap) network, which uses the 5G SA core and supports the new Apple Watch Series 11, Apple Watch Ultra 3, and Apple Watch SE 3, has been expanded to 250 million points of presence. AT&T 5G RedCap customers can look forward to a growing portfolio of devices, Elbaz said.
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Separately, Verizon is closing in on completing its 5G SA upgrade. The operator says its 5G SA is deployed nationwide but there are some places where it is still in the process of being rolled out. Although the deployment is not 100% complete, “the vast majority” of 5G SA capable phones will connect to Verizon’s network in “the vast majority of places,” according to an operator spokesperson.
Verizon has launched two network slicing services based on the 5G SA network. In April, the operator launched Frontline, a network slice for first responders that is available across the country. It also offers Enhanced Video Calling, which provides a network slice for better video communications on iPhones.
T-MobileUS launched 5G SA in 2020 and has since rolled out 5G Advanced nationwide. It also offers two network slicing propositions, T-Priority for first responders and SuperMobile for enterprise customers. Both AT&T and Verizon have implemented cloud-native 5G core networks, but T-Mobile’s implementation is more traditional. At Mobile World Congress earlier this year, T-Mobile announced its telco cloud strategy for core and edge networks that is based on Red Hat (owned by IBM).
A recent Heavy Reading (now part of Omdia) survey found 5G SA is poised to scale rapidly. Gabriel Brown noted that the results show “a critical mass is building behind 5G SA that will unlock innovation in the wider mobile network services ecosystem.”
“This matters when it comes to layering in new services because a cloud native deployment allows operators to be more agile and deploy services faster,” Brown added.
References:
https://about.att.com/blogs/2025/5g-standalone-nationwide.html
https://about.att.com/blogs/2025/5g-redcap.html
https://www.lightreading.com/5g/at-t-verizon-chase-t-mobile-with-nationwide-5g-sa
AT&T 5G SA Core Network to run on Microsoft Azure cloud platform
Téral Research: 5G SA core network deployments accelerate after a very slow start
Building and Operating a Cloud Native 5G SA Core Network
Ookla: Europe severely lagging in 5G SA deployments and performance
Vision of 5G SA core on public cloud fails; replaced by private or hybrid cloud?
GSA: More 5G SA devices, but commercial 5G SA deployments lag
GSA 5G SA Core Network Update Report
Latest Ericsson Mobility Report talks up 5G SA networks and FWA
Global 5G Market Snapshot; Dell’Oro and GSA Updates on 5G SA networks and devices
Dell’Oro: Mobile Core Network market has lowest growth rate since 4Q 2017
5G SA networks (real 5G) remain conspicuous by their absence
Amazon’s Jeff Bezos at Italian Tech Week: “AI is a kind of industrial bubble”
Tech firms are spending hundreds of billions of dollars on advanced AI chips and data centers, not just to keep pace with a surge in the use of chatbots such as ChatGPT, Gemini and Claude, but to make sure they’re ready to handle a more fundamental and disruptive shift of economic activity from humans to machines. The final bill may run into the trillions. The financing is coming from venture capital, debt and, lately, some more unconventional arrangements that have raised concerns among top industry executives and financial asset management firms.
At Italian Tech Week in Turin on October 3, 2025, Amazon founder Jeff Bezos said this about artificial intelligence, “This is a kind of industrial bubble, as opposed to financial bubbles.” Bezos differentiated this from “bad” financial or housing bubbles, which cause harm. Bezos’s comparison of the current AI boom to a historical “industrial bubble” highlights that, while speculative, it is rooted in real, transformative technology.
“It can even be good, because when the dust settles and you see who are the winners, societies benefit from those investors,” Bezos said. “That is what is going to happen here too. This is real, the benefits to society from AI are going to be gigantic.”
He noted that during bubbles, everything (both good and bad investments) gets funded. When these periods of excitement come along, investors have a hard time distinguishing the good ideas from the bad, he said, adding this is “probably happening today” with AI investments. “Investors have a hard time in the middle of this excitement, distinguishing between the good ideas and the bad ideas,” Bezos said of the AI industry. “And that’s also probably happening today,” he added.
- A “good” kind of bubble: He explained that during industrial bubbles, excessive funding flows to both good and bad ideas, making it hard for investors to distinguish between them. However, the influx of capital spurs significant innovation and infrastructure development that ultimately benefits society once the bubble bursts and the strongest companies survive.
- Echoes of the dot-com era: Bezos drew a parallel to the dot-com boom of the 1990s, where many internet companies failed, but the underlying infrastructure—like fiber-optic cable—endured and led to the creation of companies like Amazon.
- Gigantic benefits: Despite the market frothiness, Bezos reiterated that AI is “real” and its benefits to society “are going to be gigantic.”
- Sam Altman (OpenAI): The CEO of OpenAI has stated that he believes “investors as a whole are overexcited about AI.” In In August, the OpenAI CEO told reporters the AI market was in a bubble. When bubbles happen, “smart people get overexcited about a kernel of truth,” Altman warned, drawing parallels with the dot-com boom. Still, he said his personal belief is “on the whole, this would be a huge net win for the economy.”
- David Solomon (Goldman Sachs): Also speaking at Italian Tech Week, the Goldman Sachs CEO warned that a lot of capital deployed in AI would not deliver returns and that a market “drawdown” could occur.
- Mark Zuckerberg (Meta): Zuckerberg has also acknowledged that an AI bubble exists. The Meta CEO acknowledged that the rapid development of and surging investments in AI stands to form a bubble, potentially outpacing practical productivity and returns and risking a market crash. However, he would rather “misspend a couple hundred billion dollars” on AI development than be late to the technology.
- Morgan Stanley Wealth Management’s chief investment officer, Lisa Shalett, warned that the AI stock boom was showing “cracks” and was likely closer to its end than its beginning. The firm cited concerns over negative free cash flow growth among major AI players and increasing speculative investment. Shalett highlighted that free cash flow growth for the major cloud providers, or “hyperscalers,” has turned negative. This is viewed as a key signal of the AI capital expenditure cycle’s maturity. Some analysts estimate this growth could shrink by about 16% over the next year.
Bezos’s remarks come as some analysts express growing fears of an impending AI market crash.
- Underlying technology is real: Unlike purely speculative bubbles, the AI boom is driven by a fundamental technology shift with real-world applications that will survive any market correction.
- Historical context: Some analysts believe the current AI bubble is on a much larger scale than the dot-com bubble due to the massive influx of investment.
- Significant spending: The level of business spending on AI is already at historic levels and is fueling economic growth, which could cause a broader economic slowdown if it were to crash.
- Potential for disruption: The AI industry faces risks such as diminishing returns for costly advanced models, increased competition, and infrastructure limitations related to power consumption.
Ian Harnett argues, the current bubble may be approaching its “endgame.” He wrote in the Financial Times:
“The dramatic rise in AI capital expenditure by so-called hyperscalers of the technology and the stock concentration in US equities are classic peak bubble signals. But history shows that a bust triggered by this over-investment may hold the key to the positive long-run potential of AI.
Until recently, the missing ingredient was the rapid build-out of physical capital. This is now firmly in place, echoing the capex boom seen in the late-1990s bubble in telecommunications, media and technology stocks. That scaling of the internet and mobile telephony was central to sustaining ‘blue sky’ earnings expectations and extreme valuations, but it also led to the TMT bust.”
Today’s AI capital expenditure (capex) is increasingly being funded by debt, marking a notable shift from previous reliance on cash reserves. While tech giants initially used their substantial cash flows for AI infrastructure, their massive and escalating spending has led them to increasingly rely on external financing to cover costs.
This is especially true of Oracle, which will have to increase its capex by almost $100 billion over the next two years for their deal to build out AI data centers for OpenAI. That’s an annualized growth rate of some 47%, even though Oracle’s free cash flow has already fallen into negative territory for the first time since 1990. According to a recent note from KeyBanc Capital Markets, Oracle may need to borrow $25 billion annually over the next four years. This comes at a time when Oracle is already carrying substantial debt and is highly leveraged. As of the end of August, the company had around $82 billion in long-term debt, with a debt-to-equity ratio of roughly 450%. By comparison, Alphabet—the parent company of Google—reported a ratio of 11.5%, while Microsoft’s stood at about 33%. In July, Moody’s revised Oracle’s credit outlook to negative from, while affirming its Baa2 senior unsecured rating. This negative outlook reflects the risks associated with Oracle’s significant expansion into AI infrastructure, which is expected to lead to elevated leverage and negative free cash flow due to high capital expenditures. Caveat Emptor!
References:
https://fortune.com/2025/10/04/jeff-bezos-amazon-openai-sam-altman-ai-bubble-tech-stocks-investing/
https://www.ft.com/content/c7b9453e-f528-4fc3-9bbd-3dbd369041be
Can the debt fueling the new wave of AI infrastructure buildouts ever be repaid?
AI Data Center Boom Carries Huge Default and Demand Risks
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Gartner: AI spending >$2 trillion in 2026 driven by hyperscalers data center investments
Will the wave of AI generated user-to/from-network traffic increase spectacularly as Cisco and Nokia predict?
Analysis: Cisco, HPE/Juniper, and Nvidia network equipment for AI data centers
RtBrick survey: Telco leaders warn AI and streaming traffic to “crack networks” by 2030
https://fortune.com/2025/09/19/zuckerberg-ai-bubble-definitely-possibility-sam-altman-collapse/
https://finance.yahoo.com/news/why-fears-trillion-dollar-ai-130008034.html
