Semiconductor Engineering rounds up this week's blogs: a Siemens team explores how CFETs and buried power rails can shrink chip area and improve energy efficiency to meet the needs of AI accelerators, data centers, and mobile processors; Synopsys and Cadence analyze the collaborative advantages of agentic AI in EDA; Arm introduces the AMBA C2C extension for chiplet connectivity.
Precisely aligning and fixing fiber array units—FAU coupling—has become a critical bottleneck in CPO manufacturing and testing. At SEMICON Taiwan 2026, TSMC unveiled an upgraded COUPE roadmap: per-chip bandwidth reaching 3.2 Tbps in 2026, doubling to 6.4 Tbps in 2027, with a long-term target exceeding 51.2 Tbps. Integrating optics on the substrate can deliver a 4X power-efficiency gain, with OOI reaching 10X.
AWS launched the ability to create and manage SageMaker Spaces on HyperPod EKS clusters directly from the SageMaker Studio UI, letting data scientists launch JupyterLab or Code Editor environments in a few clicks without command-line tools.
AMD has released video resources related to AMD Helios AI infrastructure, along with brand assets including AMD trademarks and logos for download. Before downloading, users must accept terms and conditions: these AMD Marks may only be used in promotional materials featuring products with AMD CPUs, GPUs, APUs or FPGAs, and AMD may terminate the license at any time.
On Friday, Amazon pledged more than $1 billion over the next five years to communities near its data centers, targeting education, workforce training, energy affordability, water and other areas. It also committed to not driving up electricity prices, to becoming "water positive" by 2030, and claimed 75% of its projects already meet that standard.
TrendForce released a monthly report based on its Data Center Tracker (covering nearly 2,000 facilities), with AWS adding the most MW this month, contributed largely by the Susquehanna campus accounting for nearly half; Google adjusted across three countries, led by 330 MW of new air permits in Omaha.
Lam Research has opened its largest US warehouse in Livermore, California—a 470,000-square-foot logistics and supply chain hub built to support semiconductor supply chain pressures driven by AI technology demand. A 40,000-square-foot automated storage and retrieval system with 15 robots cuts parts retrieval time from 6 minutes to under 30 seconds, 12 times faster than the existing system. The center is expected to support more than 200 jobs by 2027.
AMD announced a definitive agreement to acquire World Labs in an all-stock deal valued at approximately $8.2 billion, expected to close by the end of 2026, subject to regulatory approval and other customary closing conditions. Founded by Fei-Fei Li and headquartered in San Francisco, World Labs develops spatial intelligence models that generate, reconstruct, and simulate interactive 3D environments from text, image, and video inputs, as well as robot learning and simulation technology.
Why it matters: AMD's official announcement gives the deal amount, equity form, and timeline, helping readers understand its direction of integrating AI hardware with model research.
TrendForce has observed that some cloud service providers are adding QLC SSDs to SSD PODs, replacing the default TLC SSD plus HDD configuration. In AI inference, the Prefill and Decode stages repeatedly read and write KV Cache, and as context windows and batch sizes grow, KV Cache capacity needs multiply, prompting vendors to move caching from costly, capacity-limited HBM down to cheaper tiers.
Based on AI server shipments, TrendForce projects that global data center power demand capacity will reach 490.7GW by 2030, with the US at 272.4GW, while US grid deliverable capacity will be only 100.7GW, leaving a gap of more than 170GW, of which about 49GW stems from the grid being unable to deliver on schedule.
At the AI Infra Summit, AMD argued that the core of AI infrastructure design should not be chips or networking but a system's ability to adapt to changing demands. The piece notes that agentic AI turns a single request into a multi-step chain of retrieval, tool calls, code execution and sub-agent coordination, and should be measured by cost per completed task rather than cost per token, offering three auditable principles: adaptable, economical, and open.
During LEAP 2026, AMD announced that AI infrastructure built with Cisco and HUMAIN, based on AMD Instinct MI355X GPUs, EPYC CPUs and Cisco networking equipment, is now in production service, with plans to add up to 250 megawatts starting from 2027 and the joint venture on track to reach up to 1 gigawatt by 2030.
AI's demand for larger, more complex chip packaging is pushing the industry to explore panel-level packaging (PLP): replacing round wafers with rectangular panels to improve area utilization and scalability beyond traditional wafer-level packaging size limits. Lam Research is advancing the technology toward production readiness through tool innovation and infrastructure investments, including the Salzburg Panel Center of Excellence. The technology still faces challenges in uniformity control, yield management, and industry standards.
At the SPIE Photomask and EUV Lithography conference, Intel Foundry and ASML reported progress on High NA EUV volume readiness; the technology has already been used in production of some Core Ultra Series 3 (Panther Lake) processors on Intel's 18A process.
In its AI Ecosystem series, SK hynix notes that as AI shifts from pretraining to inference and agentic AI, the system bottleneck is moving from GPU compute to where data resides and how it flows. The memory wall proposed by Wulf and McKee in 1994 is becoming reality: AI accelerators now reach petaflops of compute, but memory read speeds cannot keep up, leaving many compute units idle waiting for data. The response is to increase memory bandwidth or move memory closer to the processor.
AMD claims that 14 EPYC 9965 servers can replace 100 dual-socket Intel Xeon Platinum 8280 servers aged 5-7 years, cutting server count by 86% while delivering the same total performance, reducing power consumption by 69% and three-year TCO by 41%.
TrendForce analyzes the data center expansion strategies of the five major CSPs—Amazon, Microsoft, Google, Meta, and Oracle—noting that their signed but not yet activated lease commitments total about $1.16 trillion.
AMD, Cisco and HUMAIN announced that AI infrastructure built on AMD Instinct MI355X GPUs, EPYC CPUs and Cisco Silicon One AI networking has officially gone live in Saudi Arabia, providing production-grade compute to HUMAIN customers, with plans to expand to 250 MW.
AMD announced that its Instinct GPUs and EPYC CPUs will provide the compute for Europe's next-generation LUMI-AI supercomputer. (The original article contains only AMD trademark download terms and provides no further technical details of the partnership.)
AMD, Cisco and HUMAIN announced that AI infrastructure based on AMD Instinct MI355X GPUs, AMD EPYC CPUs and Cisco Silicon One networking has gone live in Saudi Arabia, offering HUMAIN customers GPU-as-a-service from model training to inference, with plans to reach 1 GW by 2030.
Marvell reported fiscal 2027 second-quarter results with record net revenue of $2.739 billion, up 37% year over year and $39 million above the midpoint of the May 27 guidance. Data center revenue was $2.1715 billion, up 46% year over year and 79% of revenue; GAAP gross margin was 53.1%, non-GAAP gross margin 58.9%, and operating cash flow $605.5 million.
Why it matters: The earnings report shows accelerating data center revenue growth and raised guidance, helping readers gauge how AI demand is actually driving Marvell's business.
SK hynix, together with researchers from UVA, UIUC, NTU, MIT and Yonsei University, has published a co-packaged optics (CPO) technology roadmap in Nature Electronics. The corresponding authors are Seunghoon Hong, SK hynix AI Infra Team Lead, and UVA professor Kyusang Lee.
Mexico's Ministry of Science, Humanities, Technology and Innovation (Secihti) has signed a memorandum of understanding with AMD aimed at building a national innovation ecosystem spanning AI, high-performance computing and semiconductors. The two sides will coordinate academic activities, seminars and training programs to develop skilled talent. The partnership will also support projects such as the Coatlicue supercomputer and national HPC and AI clusters, strengthening Mexico's research infrastructure and technological sovereignty.
AMD announced that as of mid-2026 its AI energy efficiency improvement is estimated at 4x, exceeding the 3x expected for this phase, as it advances toward its 20x30 goal of a 20x improvement in rack-scale AI training and inference energy efficiency by 2030.
AMD released its 2025-26 Corporate Responsibility Report, reviewing progress on 2020-2025 goals and looking ahead to 2030. From 2020 to 2025, renewable electricity rose from 22% to 58%, operational greenhouse gas emissions fell 30%, AI training and high-performance computing node energy efficiency improved 38x, and AMD systems on the Green500 list grew from 11 to 194; new targets include a 20x improvement in rack-scale AI energy efficiency from 2024 to 2030.
TrendForce supply chain research shows that despite reports China may relax import restrictions on the NVIDIA H200, actual H200 entry into China remains highly uncertain. Under export controls on high-end GPUs, the Chinese government is actively promoting domestic AI chip adoption this year, and the local ecosystem is gradually maturing in advanced process nodes, advanced packaging, and thermal management. China's AI infrastructure is shifting from reliance on foreign GPUs toward a dual-track model of domestic GPUs plus in-house ASICs.
On August 6, AMD announced a definitive agreement to acquire Taalas, a Toronto-based company founded in 2023 focused on dedicated AI inference chips. Taalas' technology optimizes inference data flow to reduce the compute and memory bottlenecks of general-purpose architectures; AMD plans to integrate it into its accelerator roadmap, co-develop system-level solutions with AMD Instinct GPUs, and fold it into its full-stack AI platform spanning the Helios rack solution, EPYC CPUs, and ROCm software.
AMD reported Q2 2026 results with revenue of $11.5 billion, up 50% year over year, GAAP net income of $2.3 billion, and data center revenue of $6.7 billion, up 107% and accounting for 58% of total revenue.
Why it matters: The earnings report gives specific figures on doubled data center revenue, AI-related product deployments and next-quarter guidance, helping readers gauge the pace of AMD's AI business growth.
Arista Networks reported Q2 2026 revenue of $3.036 billion, up 12.1% sequentially and 37.7% year over year, its first quarter above $3 billion; non-GAAP diluted EPS was $1.02, up 40% year over year.
Why it matters: The report gives specific figures for quarterly revenue, profit, and Q3 guidance, helping readers assess the pace of Arista's growth in AI networking hardware.
Marvell will showcase its AI memory and storage portfolio at FMS 2026 on August 4-6 at Booth #805, featuring PCIe 6.0 enterprise SSD controllers, CXL near-memory acceleration and memory pooling switches, CXL memory expansion cards, Octeon DPUs, and Photonic Fabric technology for optical interconnect scaling.
TrendForce analysts explain three paths tech giants are taking to compress the KV Cache through architectural and algorithmic innovation, with Google and DeepSeek respectively reworking attention mechanisms via GQA and MLA.
At Advancing AI 2026 on July 23, AMD unveiled a full-stack AI and physical AI product portfolio, including its first rackscale solution, AMD Helios (72 Instinct MI455X GPUs plus 18 6th Gen EPYC "Venice" CPUs).
Why it matters: The official announcement consolidates Helios rack, MI400 series CPU/GPU spec figures, and major customer deployment plans, allowing readers to benchmark actual progress against competing solutions.
On July 23, 2026 at Advancing AI 2026, AMD and Cerebras announced a technical collaboration integrating AMD Helios rack-scale solutions with the Cerebras Wafer-Scale Engine into a single disaggregated inference workflow.
As test-time scaling rises, the AI industry's focus is shifting from training to inference, bringing structural changes to the memory hierarchy. In the first half of 2026, NVIDIA and Google respectively launched CMX, Rubin integrated Groq LPX, and the TPU v8i designed for inference (with 72 GB more HBM3e and 384 MB SRAM than the TPU v8t).
AMD announced an expanded long-term strategic partnership with Microsoft, which will deploy the AMD Helios Rackscale Solution at scale on Azure for frontier model inference, its own AI customers, and Azure AI services.
Why it matters: The official announcement specifies the concrete vehicle and product composition of the partnership, helping readers understand how the two companies divide roles in AI infrastructure and the pace of deployment.
TrendForce analysis indicates that large-scale AI data center (AIDC) deployments in 2026 are pushing energy storage from an optional add-on to critical infrastructure. North America urgently needs storage to secure 24/7 power given gas generation's 40-50% share and tight supply of large gas turbines; China has made compute-power coordination part of new infrastructure, making 4-8 hour long-duration storage standard for compute hubs. AIDC storage is deployed on both the data center side and the power generation side, and NVIDIA's 800V DC architecture white paper proposes facility-level and rack-level two-tier storage schemes.
On June 9, 2026, Arista Networks launched the 7060XE7 series of 1.6T network platforms, positioned as a rack-scale AI infrastructure foundation. Built on 224G SerDes, the platforms deliver 100 Tbps of bandwidth, and LPO optical modules can cut interconnect power consumption by about 60%.
Intel announced a series of AI innovations at Computex 2026, spanning from chips to system-level solutions. Intel is working with SambaNova and Foxconn to build rack-scale AI inference infrastructure based on Xeon processors and the SambaNova SN-50 RDU.
Arista Networks (NYSE: ANET) reported fourth-quarter and full-year 2025 results: Q4 revenue of $2.488 billion, up 7.8% quarter over quarter and 28.9% year over year; full-year revenue of $9.006 billion, up 28.6% year over year.
Why it matters: The report discloses quarterly and annual revenue, margins, and Q1 2026 guidance, letting readers gauge the growth pace of its AI networking business.