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Broadcom
Data center news, project activity, and monthly briefings for Broadcom.
Editor's picks
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What the OCI MSA Didn't Solve for AI Scaling
Scintil Photonics’ CEO Matt Crowley argues that the architecture for optical scale-up has been settled by the OCI MSA and that manufacturing — specifically heterogeneous integration — now determines who can scale beyond four wavelengths per fiber.
Main announcement/action: The article presents the argument that the Optical Compute Interconnect MSA (formed earlier this spring by AMD, Broadcom, Meta, Microsoft, NVIDIA, and OpenAI) settled on an NRZ modulation + wavelength multiplexing architecture (starting at four wavelengths per fiber), and that the remaining challenge to move to 8, 16+ wavelengths is industrial (manufacturing) rather than architectural. It identifies heterogeneous integration (bonding III-V gain material to silicon photonics wafers) as the manufacturing pattern that provides wavelength-scaling headroom and cites SHIP™ on Tower Semiconductor 200 mm lines and LEAF Light™ demonstrated in 8- and 16-wavelength configurations (with NVIDIA among Series B investors) as production proofs.
Background and details: The piece contrasts prior eras (discrete lasers; silicon photonics with off‑wafer lasers) with the current heterogeneous integration era, notes that discrete-laser assembly scales poorly for hyperscale (e.g., a 16-wavelength source multiplies lasers and alignments across fibers), and references OFC 2026 where multiple vendors requested SHIP™ extensions across device categories. It emphasizes adding wavelength-scaling headroom as a line item on supplier evaluation sheets and states that teams delaying this consideration will need to redesign across two generations.
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ST 10104 2026 ADD 2
The European Commission has published an Impact Assessment Report accompanying its Proposal for a Regulation establishing the Cloud and AI Development Act (CADA).
- Main announcement: The Commission proposes CADA to strengthen Europe’s cloud and AI ecosystem by (a) tripling EU data centre (DC) capacity by 2030 and setting a path to meet needs by 2035; (b) targeting 30% market share for European cloud and AI providers by 2035; (c) imposing a permitting target of <18 months for DC permits across the EU; and (d) introducing a four-tier sovereignty framework for cloud/AI services (Levels 1–4), plus EU R&D and deployment funding and measures on public procurement to promote sovereign services.
- Context and concrete measures: The assessment documents a 2025 EU DC supply/demand gap (central estimate ~19 GW by 2036), highlights geographic concentration (FLAPD hubs ~65% of market), energy and grid constraints (Ireland DCs = 22% of electricity demand in 2025; EU DC electricity ~99 TWh in 2025 projected higher), cites past investments (AWS/Microsoft/Google ~EUR 12 bn in EU infrastructure in 2020) and commercial pressures (examples: CIA USD 600 m contract to AWS in 2013). The Impact Assessment accompanies the Commission proposal and sets out policy packages (preferred: national fast-track facilitators, designated fast-track areas, EU R&D/deployment support, mandatory sovereignty risk assessments for public procurement, joint procurement and SME support).
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Choice is the New Enterprise Cloud Strategy
DataBank promoted a webinar arguing enterprises should adopt a choice-based cloud strategy to reduce risk, cost, and vendor lock-in.
- Webinar announcement & core proposal: DataBank’s cloud team released an on-demand webinar arguing that a choice-based cloud strategy (mixing Multi-Tenant Cloud, Private Cloud, Bare Metal, and FedRAMP Cloud) and mixing hypervisors (VMware, Nutanix, Proxmox) lets organizations place each workload where it performs best. The webinar included a concrete cost example where an energy company reduced monthly spend from $18,000 to $12,200 (~32% reduction) by migrating appropriate workloads from VMware to Proxmox while keeping ERP on VMware.
- Background & drivers: The piece cites Broadcom’s 2023 acquisition of VMware and the shift from perpetual licenses to a per-core subscription model as a root cause of sharp licensing increases, and reports hardware/equipment costs rose 3–4x over several months. A webinar audience poll ranked rising infrastructure costs, hypervisor licensing increases, and security and compliance as top cloud-related challenges. The webinar replay is available on-demand.
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VMware Cloud Foundation 9: Evolving Private Cloud In One Go
VMware has released VMware Cloud Foundation 9, and OVHcloud is developing a managed offering called Private VMware Cloud Foundation as-a-Service.
- Main announcement: VMware Cloud Foundation 9 introduces a unified platform with a single lifecycle engine (VCF Operations Console) and VCF Automation for unified cloud consumption; key technical features include Advanced NVMe Memory Tiering (default DRAM:NVMe ratio 1:1, customizable to 1:4), DRS and vMotion awareness, multi-device redundancy, encryption at VM/host level, and integrated chargeback/cost transparency. The article cites Broadcom/IDC/Broadcom-internal testing figures such as up to 40% TCO savings and 25–30% increased CPU utilization.
- OVHcloud managed offering and implementation details: OVHcloud will provide Private VMware Cloud Foundation as-a-Service with VCF license portability, enforced IAM policies, pre-configured vSAN hosts, and seamless maintenance window scheduling; roadmap includes 1-AZ and 3-AZ stretched cluster versions currently in Alpha for business-critical workloads. The article is an explanatory/announcing product marketing post (author: OVHcloud copywriter and product marketing lead) and references IDC/Broadcom studies and Broadcom internal test results as supporting evidence.
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Powering AI Centers with AI Spines
Arista has announced the 7800R4 as its Universal AI Spine platform for large-scale AI deployments.
- Main announcement: Arista unveils the 7800R4 AI Spine (part of the 7800-series) as an integrated alternative to disaggregated leaf–spine fabrics, offering predictable RDMA performance, centralized control-plane and management, and support for 400G/800G/1.6Tbps interfaces; the portfolio includes 20+ Etherlink switches and is positioned for AI clusters ranging from tens of thousands up to ~100k XPUs.
- Background and details: The platform leverages features such as Virtual Output Queuing (VOQ), large ingress buffers, hierarchical buffering, Arista EOS with real-time load balancing, and telemetry tools (AI Analyzer, Latency Analyzer); hardware resiliency includes redundant supervisors, fabric cards, and field-replaceable components, and the product is presented as interoperable with partners like AMD, Anthropic, Arm, Broadcom, Nvidia, OpenAI, Pure Storage and Vast Data.
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Arista Networks, Inc. Reports Fourth Quarter and Year End 2025 Financial Results
Arista Networks has announced its fourth quarter and full year 2025 financial results.
- Main announcement: Arista reported Q4 revenue of $2.488 billion and full year revenue of $9.006 billion, with GAAP net income of $955.8 million for Q4 and GAAP net income of $3.511 billion for the full year 2025; the company also disclosed non-GAAP net income of $1.047 billion for Q4 and $3.806 billion for the full year. The company provided Q1 2026 guidance of approximately $2.6 billion revenue, non-GAAP gross margin 62-63%, and non-GAAP operating margin ~46%.
- Background and additional details:Product and corporate actions include unveiling the R4 series for AI/data center networks, Arista AVA agentic AI enhancements, launch of cognitive campus and industrial-edge switches, and the acquisition of the VeloCloud® SD-WAN portfolio from Broadcom; prior-period non-GAAP adjustments of $19.5 million (Q4 2024) and $61.3 million (FY 2024) were disclosed and recast to conform to the current presentation.
Conference call (event):
- Date: February 12, 2026
- Time: 1:30 p.m. Pacific time
- Location/Access: Dial (888) 330-2502 (US) or +1 (240) 789-2713 (international); Conference ID 5655862; also available via live webcast on Arista investor relations website (https://investors.arista.com/).
Recent news
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FuriosaAI deploys its RNGD servers at Equinix data center in Lisbon, Portugal
FuriosaAI has announced a deployment of its RNGD servers at Equinix’s LS2 data center in Lisbon, Portugal, expanding its European footprint.
- The deployment uses FuriosaAI’s custom AI inference accelerators at Equinix’s LS2 facility, which launched in June 2025 and offers 2,050 sqm of colocation space across three floors with capacity for 625 racks.
- FuriosaAI said the partnership with Equinix creates an important new distribution channel in Europe and supports energy-efficient and sustainable inference; the company also noted its NXT RNGD server launched in September 2025.
- The article adds background that FuriosaAI was reportedly seeking $300 million to $500 million in a funding round ahead of a planned IPO, and had previously raised about $115 million across four rounds; in May 2026 it announced a partnership with Broadcom for its third-generation AI accelerator.
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Enter the Network Supercycle: Preparing Data Center Networks for AI’s Next Wave
This article is commentary and analysis about AI-driven data center networking demand; it does not announce a new project or deal.
- AI traffic growth is presented as a major challenge for data centers, with commentary that ChatGPT triggered the first wave and agentic AI will drive a further surge in workload and networking demand.
- The piece cites remarks from Cisco CEO Chuck Robbins, Cisco president Jeetu Patel, Dell’Oro Group’s Sameh Boujelbene, and StorageIO’s Greg Schulz on the need to rethink bandwidth, latency, congestion control, topology, optics, telemetry, and resilience.
- Cisco is mentioned as having recently rolled out networking, switching, and routing products designed for AI, alongside vendors Marvell, Arista Networks, Nvidia, and Broadcom.
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Marvell boosts custom silicon push with AMD engineering lead hire
Marvell Technology has hired former AMD engineering lead Jay Kirkland as SVP of custom silicon engineering.
- Kirkland joins Marvell after more than six years at AMD, where he led customer engineering, platform engineering, and AI enablement for hyperscale and AI customers.
- Marvell is also pursuing custom silicon, AI networking, and optical interconnects; the article cites a $2 billion Nvidia investment in Marvell and Marvell’s $3.25 billion acquisition of Celestial AI.
- The story also mentions Marvell’s Teralynx T100 switch for AI and cloud data center infrastructure, and its acquisitions of Polariton Technologies and Celestial AI.
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You can’t build sovereign infrastructure with Broadcom, says CISPE
CISPE has publicly criticised Broadcom’s VMware Cloud Foundation (VCF), saying it cannot deliver European sovereign cloud solutions.
- Main announcement: CISPE secretary-general Francisco Mingorance published a post on CISPE’s website asserting that VCF is a proprietary product with limited interoperability and substitutability, is controlled by a foreign vendor (Broadcom) that has “behaved like a bully”, and therefore would likely only achieve Level 1 under the EU’s proposed CADA sovereignty framework; CISPE specifically cites limited maintenance commitments, no source-code escrow, no substitution plan, and no Data Act certification as concrete shortcomings.
- Background and context: The post references the EU’s Cloud and AI Development Act (CADA) proposals (which would set conditions for European data centres, investment and an EU-wide assessment framework); CISPE also notes prior actions against Broadcom including urging the EU central court in December to overturn the Broadcom/VMware merger and publishing an open letter in March warning of US hyperscalers’ “sovereignty washing.”
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Will Co-Packaged Optics Transform Data Centers?
This article explains co-packaged optics and assesses practicality and adoption timelines.
- Explains CPO and current status: The piece describes Co-packaged optics (CPO) as the integration of optical transceivers with processors in very close proximity, and cites claimed benefits of up to 350% power-efficiency gains and up to 1,000% bandwidth increases. It notes that Broadcom has made CPO-capable switches available, hyperscalers like Meta have run experiments, and Nvidia is working on processor-integrated optics (technology still in development).
- Limitations and implementation details: The article highlights concrete constraints: limited CPO hardware availability, a shortage of lasers affecting production, thermal management challenges from higher power density, maintenance limitations due to integrated transceivers, and proprietary transceiver ecosystems that hinder third-party interchangeability. No firm industry-wide deployment timeline is announced; examples cited are vendor products and hyperscaler experiments.
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Alphabet’s $80B Fundraising Spotlights AI’s Soaring Capital Needs
Alphabet has announced a planned equity raise of approximately $80 billion to fund AI infrastructure and global compute capacity.
- Main announcement: Alphabet will raise ~$80 billion in equity to fund capital expenditures to scale AI infrastructure and global compute, including a $10 billion private placement with Berkshire Hathaway (Berkshire to buy $5 billion each of Class A and Class C shares).
- Background and details: The article cites analysts and industry observers noting dramatically increased data center capex (Google expected to double data center capex this year) and emphasizes that funds are intended for data centers, power delivery, networking, cooling, and AI accelerators; portions of proceeds may also cover employee equity and corporate finance rather than direct buildout.
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AI Capacity Is Being Pre-Sold at Gigawatt Scale
Google is reportedly negotiating to invest up to $40 billion in Anthropic and to supply reserved compute capacity tied to future performance, though the companies have not publicly confirmed the terms.
- Main announcement: Reported deal would provide an initial $10 billion investment with up to $30 billion contingent on performance, and Google would supply as much as 5 GW of computing power over five years to Anthropic; the companies have not publicly confirmed these terms.
- Background and structure: The arrangement pairs capital with pre-negotiated capacity (including TPU commitments) and builds on existing ties with Google and a separate Broadcom partnership for custom silicon; delivering ~5 GW would require multiple hyperscale campuses, years of land acquisition, permitting, and grid interconnection, and coordinated planning and financing.
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Google-Anthropic Deal: AI Capacity Now Pre-Sold at Gigawatt Scale
Google is understood to be in talks to invest up to $40 billion in Anthropic.
- Main terms: Reported initial $10 billion investment, with up to $30 billion contingent on performance targets (total potential $40 billion), plus up to 5 GW of computing power over five years supplied by Google; companies have not publicly confirmed these terms.
- Background and implementation details: Builds on prior Google investments and TPU commitments to Anthropic and a separate partnership with Broadcom; delivering 5 GW approaches utility scale and will require multi-year coordination on land acquisition, permitting, grid interconnection, and multiple hyperscale campuses.
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Hyperscalers will own two-thirds of data center capacity by 2031
Synergy Research Group reported that hyperscalers will account for 67% of all data center capacity by 2031.
- Main announcement: Synergy Research Group says hyperscalers (Google, Microsoft, AWS) will reach 67% of global data center capacity by 2031, with enterprise on-prem data centers dropping from 56% in 2018 to 19% by 2031; the report also notes almost 60% of hyperscale capacity is in own-built facilities and non-hyperscale colocation accounts for ~20%.
- Background & details: The article cites planned > $500 billion in capex by Google/Microsoft/AWS for AI infrastructure in fiscal year 2026, cites hyperscalers operating ~1,297 large data centers in Q3 2025 (1,360 by end-2025), references commitments such as the Ratepayer Protection Pledge (Google, Oracle, xAI, Meta, Microsoft, OpenAI, Amazon) and highlights electricity demand concerns (EIA: price hikes up to 79% in areas like Texas by 2027); it references expanded compute partnerships (Anthropic–Google/Broadcom; OpenAI–AMD) with multi-gigawatt capacity starting 2027.
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Aria Networks raises $125M and debuts its approach for AI-optimized networks
Aria Networks has launched the Deep Networking platform and disclosed $125 million in total funding.
- Main announcement: Aria Networks (founded January 2025 by Mansour Karam) has made Deep Networking generally available this week: a combined offering of purpose-built switching hardware, a hardened SONiC implementation, microsecond ASIC-level telemetry, and intelligent agents across the stack, plus an exposed MCP server and embedded FDE (forward deployed engineers) model; the company disclosed $125 million in total funding from Sutter Hill Ventures, Atreides Management, Valor Equity Partners and Eclipse Ventures.
- Background and specifics: The platform targets AI operational metrics Model FLOPS Utilization (MFU) and token efficiency (MFU typically 33–45% for training, <30% for inference); Aria models a 3% MFU improvement across a 10,000-XPU cluster as ~$49.8 million annual revenue gain (≈7.9% revenue improvement). Hardware portfolio details include Aria Switch 800G (64 x 800G, Broadcom Tomahawk 5), Aria Switch 1.6T High Radix (128 x 800G, TH6), and Aria Switch 1.6T (64 x 1.6T, air and full liquid cooling). Software update cadence targeted at weekly releases, and FDE feedback is engineered back into products.
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Anthropic Secures Multi-Gigawatt TPU Deal With Google, Broadcom
Anthropic has signed a deal with Google and Broadcom to secure multiple gigawatts of next-generation TPU capacity beginning in 2027.
- Deal details and timeline: The agreement will deliver multiple gigawatts of TPU-based compute capacity (Broadcom disclosed it will support roughly 3.5 gigawatts) beginning in 2027, with most capacity in the US; the move expands on Anthropic’s previously announced $50 billion investment in domestic computing infrastructure and is described as the company’s largest compute commitment to date.
- Background and context: Anthropic reported a reported revenue run rate surpassing $30 billion in 2026 (up from ~$9 billion at end-2025) and said more than 1,000 customers now spend over $1 million annually; the deal reflects a strategic shift toward long-term, utility-scale TPU commitments (vertical hardware/cloud alignment) while AWS remains their primary partner.
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Anthropic signs AI compute deal with Google & Broadcom as it surpasses OpenAI’s revenue
Anthropic has signed a new agreement with Google and Broadcom to secure multiple gigawatts of next‑generation AI compute capacity, expected to come online from 2027.
- Main announcement: Anthropic secured multiple gigawatts of next‑generation AI compute capacity from Google and Broadcom, with most capacity located in the United States and expected to be online from 2027; this expands Anthropic’s infrastructure aligned with its earlier $50 billion US investment commitment for AI infrastructure.
- Background and additional details: The company reported annualised revenue run rate (ARR) crossed $30 billion in 2026 (up from ~$9 billion at end‑2025) and said >1,000 enterprise customers now spend > $1 million annually (doubling in under two months); Anthropic uses a multi‑platform hardware strategy (AWS, Google TPUs, NVIDIA GPUs), with Amazon remaining its primary cloud and training partner (ongoing Project Rainier).
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Hyperscaler backlogs show growing demand for AI infrastructure
Dell’Oro Group reported that global data center capital expenditures grew 57% in 2025 to $726 billion and are forecast to grow more than 50% in 2026, pushing total capex to cross the $1 trillion mark.
- Main announcement: Dell’Oro Group: data center capex up 57% to $726 billion in 2025, with an estimated >50% growth in 2026 that will make data center capex surpass $1 trillion (earlier forecast for $1T was 2029). The report attributes the surge primarily to AI-driven demand from hyperscalers.
- Background and details:Hyperscalers drove the increase — Amazon, Google, Meta, Microsoft raised data center capex by 76% collectively; reported company figures include Amazon $131 billion capex in 2025 (mostly data centers) and Amazon expects ~$200 billion in capex in 2026, Google plans ~$180 billion in 2026; hyperscaler backlogs cited: Amazon backlog $244 billion, Google backlog $240 billion. Surveys (BCG) show companies plan to double AI spending (from 0.8% to 1.7% of revenues) in the year referenced.
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‘Inference Is Bigger Than Any One Chip’ – d-Matrix CEO on GigaIO Deal
d-Matrix has announced the acquisition of GigaIO’s data center business to internalize interconnect technology and accelerate delivery of rack-scale AI inference infrastructure.
- Business action: d-Matrix completed a business unit acquisition of GigaIO’s data center assets (ownership of the unit’s related assets transfers to d-Matrix); financial terms were not disclosed; the deal builds on a collaboration that began in 2025 and integrates GigaIO’s SuperNode and FabreX PCIe fabric into d-Matrix’s inference stack (which also includes Corsair inference accelerators, JetStream networking, Aviator software, and the SquadRack reference architecture developed with Broadcom and Arista).
- Background & implementation details: GigaIO will continue operating independently and refocus on edge computing; a team of systems engineers based in Carlsbad, California joins d-Matrix, establishing a new Southern California engineering presence; d-Matrix now operates six innovation hubs across North America, Europe, and Asia; target customers include hyperscalers, frontier AI labs, and enterprise deployments.