China's domestic server and chipmakers are entering a 'super cycle' as local governments invest heavily in computing infrastructure for AI development. The AI Computing Power Concept Index, which includes 54 component stocks, reached a record high, increasing by 166% over the past year. DeepSeek AI has hinted at changing its data format to support domestic AI chips, contributing to the market excitement. Read more: https://lnkd.in/e9qZCKef 📰 Subscribe to the weekly Silicon Brief Newsletter: https://lnkd.in/ejfzg92J #ai #artificialintelligence #ainews #aichips #datacenters

Futurum has released two comprehensive market models predicting the data center semiconductor market will exceed $500 billion by 2029. The market is expected to grow from $265 billion in 2025 to $583 billion in 2029, with a 21.6% compound annual growth rate. NVIDIA holds over 90% of the GPU market, while Broadcom leads the XPU market with an 80% share. Ray Wang from Futurum said global investment in AI compute and data centers is accelerating due to increased AI demand and sovereign AI initiatives. Read more: https://lnkd.in/eC9eEbkS 📰 Subscribe to the weekly Silicon Brief Newsletter: https://lnkd.in/ejfzg92J #ai #artificialintelligence #ainews #aichips #datacenters

Huawei has introduced three AI-specific SSDs—the OceanDisk EX 560, SP 560, and LC 560—designed to break through storage and speed limitations in AI data centres. Highlights include: ⦿ OceanDisk EX 560: Ultra-high performance for AI training, enabling model fine-tuning at six times the scale per machine. ⦿ OceanDisk SP 560: Balances performance and cost, offering up to 2.5× faster inference with 75% lower latency on inference initiation. ⦿ OceanDisk LC 560: Record-breaking 245 TB capacity—the industry’s largest—offering 6.6× greater data processing efficiency while reducing physical storage footprint by 85%. These AI SSDs directly respond to growing AI workloads and global high-bandwidth memory (HBM) shortages, reinforcing Huawei’s push for self-reliance amid supply-chain pressures. #Huawei #AIHardware #DataCenter #StorageInnovation #AIInfrastructure

As AI models grow larger, the hidden challenge isn’t just computing power, it’s cooling. LG Electronics just won a major contract to supply cooling systems for U.S. hyperscale AI data centres, highlighting how infrastructure choices can shape the future of AI. Is cooling technology now as critical as chips in driving AI forward? Let us know your thoughts in the comments. #ArtificialIntelligence #DataCenters #ElectronicsIndustry #SustainableTech #FutureOfAI #Innovation

Ayar Labs has partnered with AIchip to develop AI infrastructure using co-packaged optics technology. The collaboration involves combining Ayar Labs' optical technology with AIchip's packaging expertise and TSMC's advanced process technology. Mark Wade from Ayar Labs said their technology removes limitations of copper interconnects, aiming for power-efficient AI systems. Johnny Shen from Alchip highlighted the need for innovative packaging design to meet AI workload demands. Read more: https://lnkd.in/ezFDKGWY 📰 Subscribe to the weekly Silicon Brief Newsletter: https://lnkd.in/ejfzg92J #ai #artificialintelligence #ainews #aichips #datacenters

Ayar Labs and Alchip to Scale AI Infrastructure With Co-Packaged Optics Ayar Labs Alchip Technologies Mark Wade Johnny Shen #AIChipsNews #AI #Chips #Semiconductor #AIChip #AIChipsMarket https://lnkd.in/dBXqhSTq

While everyone's getting excited about Huawei's new Ascend chips promising the world's most powerful clusters, I'm watching our clients struggle with much more basic realities. After deploying AI systems across 50+ companies this year, the bottleneck is never compute power. Three months ago we helped a manufacturing client save $2.3M annually with a simple Claude integration that processes quality reports. Total compute cost? Under $400 monthly. Yet they had been shopping for expensive GPU clusters because their previous consultant convinced them they needed cutting edge hardware. The uncomfortable truth most AI consultancies won't admit is that 90% of business AI applications run perfectly fine on standard cloud infrastructure. Companies are burning millions on unnecessary hardware while their actual workflows remain unautomated. We've seen Fortune 500s deploy massive compute clusters that sit at 12% utilization because nobody built the practical integrations. The real constraint isn't chip architecture or cluster performance. It's having operators who can ship working systems that integrate with existing business processes. DeepSeek R1 and advanced chips are fascinating from a research perspective, but most businesses need someone who can connect their CRM to intelligent document processing next week, not theoretical compute breakthroughs. What's the biggest gap you're seeing between AI marketing promises and actual deployment needs? #AIImplementation #BusinessAutomation #PracticalAI https://lnkd.in/epdEx7Ec

OpenAI Announces First Dedicated AI Chip for 2026 OpenAI’s partnership with Broadcom to develop its inaugural AI‑specific processor marks a pivotal shift in the industry, promising faster inference, lower latency, and more energy‑efficient workloads. This move signals a maturing AI ecosystem where custom silicon becomes essential for scaling large models, reducing operational costs, and unlocking new use‑cases in real‑time analytics and edge computing. Professionals in AI research, product development, and cloud infrastructure should watch how this hardware rollout may reshape model deployment strategies, competitive dynamics, and the broader push toward sustainable AI. resource: https://lnkd.in/gpZ793cc #AI #OpenAI #Hardware #Innovation #Tech

AI is no longer just software-driven — it’s becoming a hardware story. The demand for advanced chips is reshaping the global technology landscape, and the companies that can deliver secure, energy-efficient, and high-performance compute will define the next decade. From GPUs powering deep learning to specialized AI accelerators and next-gen data center infrastructure, the chip industry is at the center of an unprecedented transformation. Supply chains are evolving, competition for resources is intensifying, and the focus is shifting from “more compute” to “smarter, more efficient compute.” At Dozier Holdings Group, we see this as a pivotal moment — not only to meet the demands of AI today, but to build long-term, resilient solutions that support innovation across every industry tomorrow. The future belongs to those who can bridge AI + Infrastructure + Energy Efficiency — and we’re committed to being at that intersection. #AI #Chips #Semiconductors #DataCenters #FutureOfCompute #DozierHoldingsGroup

AI campuses are exploding in size. Without new rules, they look like liabilities to already-strained ISO/RTO systems. But what if the very same NVIDIA networking stack (Spectrum-X, MagnumIO, NCCL) could become a reliability asset? Our new paper, Incentivizing AI-Optimized Networking for Grid-Aligned Data Centers, shows how: NVIDIA’s tech already provides it - deterministic traffic patterns, sub-µs telemetry, and topology-aware schedulability. These features are exactly what ISOs need to accredit flexible load. The missing link is incentives — by embedding these digital load properties into the Unified Energy Valuation Framework (UEVF) / ASCDE, we can pay AI campuses not just for MW consumed, but for MW avoided when it matters most. Reliability, in the same units as capacity...  EUE x VOLL → monetized outage risk (today’s adequacy currency) Flexible AI networking → accredited like a demand response product Valuation results: 8–15% savings in adequacy procurement, 20%+ avoided transmission upgrade spend when AI load elasticity is priced alongside capacity/storage. The hardware is already in the racks. Spectrum-X and MagnumIO make these data centers predictable, controllable, and measurable. All that’s left is for ISOs to adopt the right incentive framework so that hyperscale growth strengthens the grid instead of stressing it. #AI #AIGrid #GridPolicy #UEVF