AMAZON RELEASES AN IMPRESSIVE NEW AI CHIP AND TEASES

AI Chip Components for Servers

AI Chip Components for Servers

Coverage across current and emerging chip types, including GPUs, CPUs, custom AI ASICs, and other AI chips, from over 40 chip designers, historic market data from 2022-2024, and market forecasts from 2025 to 2035. AI model training and inference workloads are forcing the industry to rethink not only how much compute fits in a rack, but how servers are architected from end to end — transforming computing infrastructure as we know it. 2 Hyperscalers are spending $380B+ on AI capex in 2025 while simultaneously building custom chips (TPU, Trainium, Maia, MTIA) that offer 40-65% TCO advantages over GPUs. 3 Broadcom and Marvell control ~95% of the custom ASIC co-design market — Google alone spends ~$8B/year with Broadcom on TPU. Within this hardware ecosystem, printed circuit boards (PCBs) play a critical role as the structural foundation for electronic components and the provider of electrical. Our new AI Chip Components explorer tracks how much advanced-node logic, memory, and advanced packaging capacity is consumed by leading AI chip designers. Artificial intelligence (AI) is being adopted across all industry sectors and the growing need to run AI (as well as machine learning, or ML) workloads is placing considerable demands on servers.

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Thailand Cloud AI Server

Thailand Cloud AI Server

This blog analyzes Thailand AI Servers and GPU Hardware industry including industry growth drivers, rising AI workloads, data center investments, adoption across cloud providers, enterprises and research institutions, key hardware segments, competitive landscape and future. Thailand's digital infrastructure landscape is experiencing a rapid transformation as demand for artificial intelligence (AI), cloud computing, and high-performance computing continues to rise. As of 2026, Thailand has emerged as one of Southeast Asia's fastest-growing data center markets. The Thailand Artificial Intelligence Data Center Market Report is Segmented by Data Center Type (Cloud Service Providers, Colocation Data Centers, and More), Component (Hardware, Software Technology, and Services), Tier Standard (Tier 3 and Tier 4), and End-User Industry (IT and ITES, Internet and. Offering over 100 cloud and AI services, this collaboration supports enterprises and government with hyperscale performance, local data compliance, and robust security—ideal for critical workloads. ulf Edge Company Limited ("Gulf Edge"), a fully-owned subsidiary of Gulf Energy Development Public Company Limited ("Gulf"), and Google Cloud today announced a multi-year agreement to deliver next-generation sovereign cloud services in Thailand that meet the country's most stringent data residency.

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AI Hyperconverged Server

AI Hyperconverged Server

HCI is converging with edge computing to reduce latency for AI, computer vision, and IoT workloads. Deploying HCI clusters at the edge brings enterprise-grade infrastructure capabilities to remote locations, supporting use cases like autonomous vehicles, smart manufacturing . Starting with as few as three nodes, users can easily scale out to match computing and storage resource needs. It's an integrated system of performance-optimized hardware, open software, ML frameworks, and flexible consumption models.

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Vietnam AI Server 100G

Vietnam AI Server 100G

On May 9, 2024, FPT imported Vietnam's first DGX H100 server system, marking the initiation of a strategic collaboration with NVIDIA to advance artificial intelligence (AI) development in the country. A Vietnamese retailer builds AI servers with RTX 5090s to leverage higher memory capacity for AI workloads. The GeForce RTX 5090 was launched at the end of January, and it has been over two months, and yet we don't have sufficient stocks of the GPU. The V100 GPU server (NVIDIA Tesla V100) is a powerful solution for Artificial Intelligence (AI), Deep Learning, and High-Performance Computing (HPC), suitable for systems requiring high computing performance and large-scale data processing. Once clustered together, they create large memory pools that can support various AI workloads, something that will always find a customer, and wealthy customers those are. Vietnam's digital economy has been expanding at one of the fastest rates in Southeast Asia, driven by strong internet penetration, rising e-commerce adoption, and a rapidly growing startup ecosystem. A Vietnamese PC known as Nguyencongpc, recently posted a picture of a custom rig with multiple units of the NVIDIA GeForce RTX 5090. While it may look like the rig would be deployed for cryptomining, it was actually built to facilitate a more.

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AI computing power server

AI computing power server

AI servers consume significantly more power than traditional IT equipment, primarily due to the use of GPUs and high-performance accelerators. Typical ranges include: • Traditional servers: 300–800 W per server • GPU servers: 2–10 kW per server • AI racks: 20–100+ kW per rackThe start-up SPAN wants to bundle AI computing power decentrally in private households. A piece of data center: The servers from SPAN are to be housed in a white box on the house wall, which – networked with other boxes – will. 2 AI data center racks draw 60+ kW each, compared to 5-10 kW for standard server racks. This 6-12x density difference is why AI facilities require entirely different power infrastructure, liquid cooling, and grid connections than conventional data centers. In collaboration with NVIDIA, Infineon will develop the next generation of power systems based on a new architecture with centralized power generation through 800V high-voltage direct current. Despite this, rack space and PSU form factors will remain unchanged, pressuring PSU vendors to achieve higher power density.

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