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Data center news, project activity, and monthly briefings for AMD.
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Editor's picks
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AWANI Talk Series: Friends to All, Enemy to None | Can Malaysia stay neutral in a polarised world?
Astro AWANI hosted a panel discussion on Malaysia’s foreign policy approach of “active non-alignment” and whether the country can remain neutral in a more polarized world.
- The discussion focused on Malaysia’s neutrality, trade and investment attraction, human rights, and ASEAN centrality, with panelists debating whether Malaysia can stay “friends to all, enemy to none” under rising geopolitical tensions.
- Speakers referenced China-US trade tensions, South China Sea, Myanmar, Cambodia-Thailand, Gaza, Ukraine, and Malaysia’s national action plan on business and human rights; they also argued that ASEAN is constrained by national interests, a weak Secretariat, and rotating chairmanship.
- This appears to be an analysis/opinion panel, not a first-time policy announcement, although it cites Prime Minister Anwar Ibrahim’s term “active non-alignment” and discusses recent government positions and reforms.
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AT&T and Microsoft scale trillion-token workloads with Microsoft Foundry and AMD
AT&T has announced that it used Microsoft Foundry Managed Compute to build and scale its OTel2.0 telecom-focused AI models.
- AT&T used approximately 530 GPUs through Microsoft Foundry Managed Compute, including 430 AMD Instinct™ MI300X GPUs, to support OTel2.0 development across multiple GPU architectures.
- The company processed about 1T tokens for OTel2.0 and says using open-source models like Phi-4 for synthetic data generation saved tens of millions of dollars versus frontier models; Microsoft also said deployment could happen in days rather than weeks.
- AT&T deployed models including Phi-4, OSS-120B, and Gemma-4 for synthetic data generation, data preparation, reasoning workloads, and broader model development.
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Edge AI Platforms
AMAX has announced its Edge AI platform portfolio and supporting services for moving edge AI systems from prototype to production.
- The portfolio includes 1U and 2U edge servers for low-latency inference, industrial compute, medical imaging, smart vision, and distributed enterprise workloads.
- Named products include ServMax X-110, ServMax X-114, ServMax A-1112T, ServMax X-216, and AceleMax AXG-2164IB, with the latter supporting up to four PCIe GPUs.
- AMAX also describes services covering product engineering, GPU system design, OEM customization, thermal & power validation, factory testing, manufacturing & QA, global deployment support, and lifecycle management.
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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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Economic Consequences of Section 232 Tariffs on Semiconductor Imports
The Trump administration issued an executive order in January 2026 imposing a 25 percent Section 232 tariff on certain advanced semiconductors.
- Main action: The January 14, 2026 executive order imposed an immediate 25 percent ad valorem duty on a narrow category of advanced computing chips and signaled a possible broader phase 2 at a “rate of duty that is significant.” ITIF models that a sustained 25% tariff would produce a cumulative $1.6 trillion loss in U.S. GDP (3.9%) over 10 years, reduce ICT consumption by $12.5 billion, and lower GDP per capita by $170 in year 1 and $4,825 cumulatively by year 10. The United States imported $48.1 billion of semiconductors in 2025 (baseline used in analysis).
- Background and recommendations: ITIF recommends removing blanket semiconductor tariffs, extending the investment tax credit (ITC) — now 35% — through 2030 and expanding it to semiconductor research and design, and requiring future Section 232 tariffs to include annual reviews and automatic expiration. The report also urges that tariff offsets under phase 2 be made available to firms engaged in semiconductor R&D and AI/data-center investment. The ITC is noted as scheduled to expire at the end of 2026.
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Liz Kendall's speech to London Tech Week
Liz Kendall, Secretary of State for Science, Innovation and Technology, announced expanded UK AI industrial policy at London Tech Week, including Sovereign AI (SovAI) details and a new AI Hardware Plan.
- Main announcement: SovAI (launched in April) will invest £500m in British AI companies to start up, scale up and win globally; the government is also mobilising fully funded access to the UK’s largest super computers, super-priority visa decisions and free visas for R&D, and working with the British Business Bank (which runs a £2bn annual investment programme) to back companies. The government also published an AI Hardware Plan that
Recent news
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Core Scientific Doubles AI Capacity to 1.1 GW in $14B AMD Deal
Core Scientific has announced a 15-year infrastructure agreement with AMD to expand its leased AI data center capacity to approximately 1.1 GW.
- The agreement covers 530 MW across five campuses and represents more than $14 billion in potential base contracted revenue; it begins in 2027 and gives AMD exclusive rights to reserve up to an additional 2 GW of future capacity.
- Core Scientific said the broader contracted AI portfolio now totals approximately 1.1 GW and more than $24 billion in potential contracted revenue; deliveries will begin at the Pecos, Texas campus in the first half of 2027, with development also advancing in Hunt, Texas; Muskogee, Oklahoma; Auburn, Alabama; and Dalton, Georgia through 2028.
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Intel Layoffs Show Data Center Workers Aren’t Immune to Corporate Job Cuts
Intel has announced it is preparing another round of layoffs in its data center group while saying product commitments and roadmaps will not change.
- First reported by The Oregonian, Intel notified employees in its data center group about planned cuts; the company did not disclose the number of positions or whether Oregon employees would be affected.
- Intel said the reorganization is part of a broader strategy to become a more focused and efficient company and to ensure the group has the right roles and skills for long-term success; Intel also reported Q1 2026 data center and AI revenue of $5.1 billion, up 22% year over year.
- The article also notes broader industry layoffs at Oracle and Microsoft amid heavy investment in AI data center expansion, and includes analyst commentary from IDC about AI being used as a pretext for job cuts.
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AMD Fires Back at Nvidia with Helios AI System, Epyc CPUs
AMD has announced its Helios rack-scale AI system and sixth-generation Epyc CPUs at its Advancing AI conference in San Francisco.
- Helios is in full production, with shipments from hardware partners scheduled to begin by the end of Q3 2026; the system combines Epyc processors, Instinct MI455X GPUs, Pensando networking, and ROCm software.
- AMD also launched the Epyc 9006 Series CPUs and ROCm.ai; the company said future products include Instinct MI500 in 2027, MI600 in 2028, and next-gen CPUs planned for 2028 and 2030.
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Quantum Meets the Data Center: Hybrid Systems Take Off
The article explains a shift in quantum computing toward hybrid quantum-classical infrastructure and cites policy support, vendor roadmaps, and conference remarks rather than a single standalone company announcement.
- The U.S. Department of Commerce announced more than $2 billion in incentives in May 2026 to accelerate quantum commercialization, including quantum manufacturing and utility-scale, fault-tolerant systems; the White House followed with a June 2026 Executive Order on the Next Frontier of Quantum Innovation.
- The piece also cites vendor and industry developments: IBM outlined quantum-centric supercomputing in March 2026; Nvidia launched NVQLink at GTC 2026; HPE said in June 2026 it is working with multiple partners on hybrid quantum configurations; and AMD said it is working with OQC and JPMorgan Chase on quantum, AI, and HPC workloads.
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FLOPS vs Megawatts: Who’s Winning in 2026 Supercomputing?
The article provides analysis and commentary on 2026 supercomputing buildouts, contrasting public exascale systems with hyperscaler AI campuses. It is not a first-time announcement by one entity, but a roundup of recent developments and milestones.
- The piece compares public TOP500 systems and private hyperscaler AI campuses, highlighting that private builds are measured in hundreds of megawatts to gigawatts rather than HPL scores.
- It cites several recent milestones, including Microsoft’s Wisconsin Fairwater campus, xAI’s Colossus 2, OpenAI and Oracle’s Stargate, and Meta’s Prometheus nuclear power agreements.
- It also notes Alice Recoque installation in France under a €354.8 million EuroHPC JU contract with Eviden and mentions the next TOP500 list at SC26 in November.
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China $16 Billion AI GPU (Graphics Processing Unit) Startup Hong Kong-Listed Shanghai Iluvatar CoreX Semiconductor Raised $902 Million in Share Sale at 15% Discount to Closing Price (9/7/26), Share Price +234% Since IPO in 2026 January (8/1/26), Founded in 2015 by ex-Oracle R&D Director Li Yunpeng
Shanghai Iluvatar CoreX Semiconductor has announced a $902 million share sale at a 15% discount to the closing price, following its Hong Kong listing and earlier IPO fundraising.
- The company said it raised $902 million in a share sale on 9 July 2026, priced at a 15% discount to the closing price.
- The article also says Shanghai Iluvatar CoreX Semiconductor had its Hong Kong IPO in January 2026, raising $446 million at an IPO price of HKD 144.6 and closing at HKD 156.8 on day one; it was described as a $16 billion AI GPU startup founded in 2015 by Li Yunpeng.
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Pittsburgh Supercomputing Center awarded $10m by NSF for Bridges-3 supercomputer
The National Science Foundation has awarded the Pittsburgh Supercomputing Center $10 million for Bridges-3, the next generation of its flagship supercomputer.
- NSF funding: PSC said the award will support Bridges-3, built by HPE with Nvidia B200 GPUs, high-core-count AMD CPU nodes, an all-flash Lustre file system, and Nvidia InfiniBand networking.
- Timeline and context: Construction is expected to begin at PSC’s new data center in early 2027, with the system slated to come online in the summer of 2027; PSC said it will expand on Bridges-2 and serve a range of scientific workloads including modeling, simulation, data analytics, and AI.
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NSF’s $20M Quantum Push: What It Could Mean for Future Data Centers
The US National Science Foundation (NSF) has announced $20 million in additional funding for five quantum research teams as part of its National Quantum Virtual Laboratory program.
- NSF selected five additional teams to join the National Quantum Virtual Laboratory, with each team receiving $4 million over two years to refine development plans for fault-tolerant computing, quantum networking, and next-generation sensing.
- The program expands to nine design projects total, involves researchers across 20 US states and partners including NASA, NIST, Department of Energy national laboratories, and industry participants such as Nvidia, Honeywell, IonQ, and Quantinuum; it also supports the White House executive order on quantum innovation.
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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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HPE Discover: Neri outlines an AI architecture built for agents
HPE announced at HPE Discover 2026 in Las Vegas new AI-focused product and platform updates across networking, compute, storage and cloud.
- Main announcement: HPE detailed cross-portfolio AI updates including new networking hardware (QFX switches, PTX 12,000 with 800G routing, SRX 4700 quantum-safe firewall at 1.44 Tbps, MX 301 edge router), compute (ProLiant DL 394 Gen 12; Private Cloud AI scaling to 256 GPUs with multi-node inference and a three-tier AI Factory), storage (Alletra MPX 10,000 as the Private Cloud AI storage layer with native MCP and Nvidia Certified Storage validation), and cloud/management (HPE CloudOps consolidation and Unleash AI program covering 60+ validated partners).
- Background and specifics: Announcements include agentic governance (zero-code agent registration, three-tier identity model, Nvidia Open Shell, NeMo Cloud workflows, Zerto rollback), performance claims (AI training with one-quarter the GPUs vs prior Blackwell-generation platform; inference at one-tenth the cost per million tokens; 7 to 12x faster time to value vs custom environments), and an energy warning citing a projected 19 gigawatt U.S. power gap by 2028 and data centers accounting for nearly half of U.S. electricity demand through 2031.
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Data Center Hardware Highlights: June 2026
Blackstone and Google have launched a $5B TPU infrastructure venture.
- $5B TPU venture: Blackstone and Google announced a $5 billion partnership to build TPU-focused AI infrastructure, signaling a move toward vertically integrated AI compute financed by private capital. The announcement is the central deal highlighted in May’s coverage.
- Broader May highlights: Data Center Knowledge reports shifts across the stack in May: AI server vendors moving from silicon to services; Nvidia expanding spending beyond GPUs (including networking, cooling, power) and engaging with Iris Energy’s 5 GW pipeline; AMD posted 57% data center growth tied to accelerators; GPU rental pricing shows early compression; battery storage gains traction as diesel alternatives; and geopolitical risk (notably Iran) threatens PCB supply chains.
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AI Server Market Update: Vendors Shift from Silicon to Services
Data Center Knowledge reports that server vendors are shifting toward software, professional services, and AIOps to win enterprise AI customers.
- Main announcement: Vendors including Dell, HPE, Lenovo, and Supermicro are emphasizing software management, professional services, AIOps, and liquid-cooling/packaged rack solutions to capture enterprise AI demand; IDC projects AI infrastructure spending to reach $487 billion in 2026 and surpass $1 trillion by 2029, while suppliers report large backlogs (e.g., Dell $43 billion AI backlog, HPE $5 billion AI systems backlog, Lenovo $15.5 billion AI server pipeline).
- Background & details: The article is an industry analysis citing interviews and earnings: IDC reported the global server market at $444 billion (2025); vendors report specific results such as Dell $9 billion AI-optimized server revenue (Q4 FY2027) and Supermicro $10.2 billion sales (FYQ3 FY2026); it highlights enterprise skill gaps, GPU/memory supply constraints, and differentiation via integration, delivery speed, power & cooling, and services.
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What Next Gen Chips Might Mean for Data Centers
Data Center Knowledge presents analysis of semiconductor innovations for data centers.
- Main finding: The article argues that semiconductor-level innovation (AI-optimized chips, energy-optimized and heat-tolerant designs, advanced packaging such as chiplets and 2D/3D, and offload silicon like DPUs/IPUs/SmartNICs) could reshape how data centers are built, powered, cooled, and secured; current adoption is constrained by x86 inertia and software compatibility challenges.
- Background/details: The piece surveys existing technologies (GPUs, ASICs, FPGAs, ARM-based servers), highlights materials research (graphene, carbon nanotubes) as early-stage, and notes concrete operational benefits including reduced power draw and lower cooling/water use, but it does not announce specific commercial deployments or timelines.
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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.