Reports
AI-generated structured vendor updates
Intel Announces Leadership Appointment to Strengthen Customer Engagement and Accelerate Growth - Intel Newsroom
Intel Announces Leadership Appointment to Strengthen Customer Engagement and Accelerate Growth ...
AMD收购AI推理芯片公司Taalas 补强AI推理路线图
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Fortinet扩展FortiGate G系列 推出1200G与FortiSASE Outpost
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Anthropic确认组建内部芯片团队为Claude设计定制芯片
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Cisco Unveils 51.2Tbps Router for AI-Ready Data Centers
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Micron, MediaTek back ChipAgents as agentic AI startup extends series A to US$134 million
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MediaTek sees SerDes 448G as copper's final battleground
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MediaTek Advances CoWoS, EMIB-T and 3.5D Packaging Strategy
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Cloudflare Announces Second Quarter 2026 Financial Results | Cloudflare
Press release. August 6, 2026 Cloudflare Announces Second Quarter 2026 Financial Results Second quarter revenue totaled $696.1 million, representing an increase of 36% year-over-year GAAP lo...
MediaTek targets Google TPU v10 and Meta AI ASIC orders with 400G SerDes
MediaTek announces 400G/448Gbps SerDes ready by 2027, targeting Google TPU v10 and Meta AI ASIC orders. It has secured major TPU v9 orders and aims for 15-20% ASIC market share, leveraging 2nm process for data center AI chips.
MediaTek Adopts Dual Packaging: CoWoS and Intel EMIB-T for ASIC
MediaTek CEO confirms ASIC projects adopt Intel EMIB-T packaging alongside TSMC CoWoS. EMIB-T uses micro bridges for high-density interconnects, supporting HBM, achieving 8-10x reticle area at lower cost. Dual-track strategy highlights packaging as a key competitive dimension in AI chips.
MediaTek Approves $5B for AI Data Center ASICs, Shifts from Mobile Focus
MediaTek approves $5B discretionary budget to develop AI ASICs for data centers, with first AI accelerator ASIC entering production in Q4 2026 and second-gen in early 2028. The company targets 15-20% share of the $80B custom AI chip market by 2027, expecting over $2B revenue from AI data center chips in 2026.
英特尔与Fortinet共同开发SP6安全处理器，强化网络防火墙ASIC能力
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FortiBleed攻击全球暴露约75000台Fortinet防火墙设备
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Third-party cyber evaluations involving OpenAI models | OpenAI
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Google's Frozen v2 Chip Hardwires Gemini Architecture for 6-10x TPU Efficiency, Set for 2028
Google is developing Frozen v2, a dedicated AI chip that hardwires the Gemini model architecture into silicon for 6-10x energy efficiency per token over current TPUs. It is a new product line, planned for 2028, with weight update flexibility but a frozen architecture. This validates the industry shift from general-purpose GPUs to dedicated ASICs for AI inference.
Google DeepMind AlphaEvolve GA: AI Self-Evolution for Data Center and Algorithm Optimization
On July 19, 2026, Google DeepMind announced the GA of AlphaEvolve, a Gemini-based multi-agent evolution system for algorithmic discovery, mathematical discovery, and data center efficiency optimization, already used in Borg and Orca, aiming to reduce Capex in massive AI compute investments.
NVIDIA-Nokia Alliance Redefines RAN Ecosystem with GPU-Based AI Acceleration
NVIDIA and Nokia are jointly developing AI-powered RAN technology, using NVIDIA GPUs to accelerate baseband processing and AI algorithms for beamforming and spectrum optimization. Targeting commercial deployment by 2027 and 2x spectral efficiency by 2028, this partnership marks a fundamental shift from dedicated RAN hardware to GPU-based, software-defined AI networks.
Meta Iris Chip to Mass Produce in September: 6-Month Cadence Threatens NVIDIA GPU Hegemony
Reuters confirms Meta's Iris AI chip mass production in September, targeting 2.5GW by end-2026 and 14GW by 2027. Meta's 6-month MTIA generation cadence directly challenges NVIDIA's annual GPU cycle, signaling a hyperscaler shift from GPU dependency to custom ASIC sovereignty.
JCET's $1.4B AI Packaging Capex Reshapes Advanced Packaging Supply Chain
JCET announces $1.4B capex for AI advanced packaging in 2026, targeting Chiplet, HBM, 2.5D/3D. This marks Chinese OSAT's major entry into high-end packaging, complementing TSMC's CoWoS expansion and shifting AI packaging from Taiwan-centric to cross-strait division, supporting local hyperscalers' computing needs.