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Tuesday 6 January 2026
MSI Unveils Full Lineup of AI Products at CES 2026
MSI, a world leader in gaming and high-performance AI computing, today announced its commanding presence at the 2026 Consumer Electronics Show (CES), centered around the theme of "Innovate Beyond.
Friday 9 January 2026
Taiwan III launches national team to deliver DCBBS computer cabinet
Generative AI is fueling accelerated growth in worldwide computing power requirements, yet the industry encounters significant challenges. Although the product cycle for GPUs and AI servers has been condensed to approximately 18 months, the conventional data center construction process remains at two to three years, resulting in a structural gap where the deployment of computing capacity lags behind technology advancements.Supermicro, Easy Field Corporation (EFC), and Chicony Power have jointly introduced the world's first DCBBS containerized data center solution. This solution is designed to expedite engineering delivery timelines and offers an alternative approach to the construction of AI infrastructure.In this DCBBS solution, Taiwan's Institute for Information Industry (III) acts as a coordinator for industry integration, connecting resources from IT, infrastructure, engineering consulting, and manufacturing to ensure that all stakeholders comply with a unified delivery timeline.Wang Rui-min (transliterated from Chinese), Senior Strategy Director of the Market Intelligence & Consulting Institute (MIC) at III, explained that AI computing power initiatives involve various components and parts, such as servers, networking devices, power supplies, cooling infrastructure, structural engineering, testing procedures, and international certifications. Historically, inadequate coordination methods often led to asynchronous delivery within these categories.Simon Hsu, COO of Taiwan's National Applied Research Laboratories (NARLabs), observed that traditional data center construction methodologies are inadequate in accommodating the progress of AI technology. Computing power has become a crucial resource for scientific research and industrial development, with the speed of deployment significantly impacting the evolution of both research and applications. In this context, modular and rapidly replicable computing power supply models are garnering attention.The DCBBS solution, collaboratively developed by Supermicro and several Taiwanese manufacturers, utilizes a methodical design approach. It first develops the overall data center architecture, then deconstructs tasks such as power supply, cooling, networking, fire safety, and administration into modular components.Huang Shih-chin (transliterated from Chinese), Product Manager for Supermicro's Rack Solutions, stated that this solution explicitly demonstrates computing power density in its technical specifications, addressing the requirements of various GPU generations, and introduces the notion of "Container Scale," enabling the expansion of computing power on a container-by-container basis. The engineering design prioritizes uninterrupted water, electricity, and network connectivity.The generator, transformer, chiller, and UPS are arranged in a containerized configuration, equipped with wireless environmental control and remote monitoring systems, facilitating mobility and rapid deployment of the computing units. The container is designed according to weight, stress absorption, external circumstances, and transportation certification standards, rather than conventional container specifications. The test line construction and burn-in verification have been completed, and the DCBBS system has entered the final acceptance and shipment phase.In the DCBBS project, EFC used an engineering methodology to complete system integration tasks for computing resource deployments. Chairman Paul Luo stated that, while AI servers are expensive, the primary elements determining computing power competitiveness are deployment timeframes and engineering dependability; delays or system failures result in expenditures that much surpass hardware expenses. Thus, EFC used a modular approach to organize the structural design, vibration mitigation, transportation, and certification requirements for the outdoor installation of large, high-density equipment in atypical environments, before transferring these components to the factory for assembly and verification. Luo indicated that, moving forward, computing containers will primarily be deployed in areas rich in energy resources.Consequently, what is truly finite is not electricity itself, but the ability to swiftly replicate and maintain the level of engineering execution. EFC, possessing extensive expertise in the production of large-scale structures and high-reliability systems, ensures that its computer cabinets are thoroughly prepared for acceptance and delivery before shipment. They are considered the fundamental framework and structure of the entire computing center, enabling future expansion within a managed and foreseeable technical timeline.In terms of work division, Supermicro is in charge of coordinating the full rapid delivery process, drawing on its significant experience with high-density computing clients. In recent years, the company has obtained AI processing power contracts, including those from Tesla, gaining engineering experience in high-density configurations and fast delivery, which has become a critical basis for minimizing deployment delays. Chicony Power oversees the wireless environmental control system, employing sensors, digital twins, and remote-control technology to mitigate the effects of conventional extensive cabling on deployment efficiency, hence facilitating expedited scheduling and replication of computing cabinets.EFC monitors the structural engineering design and, using its expertise in ship door manufacture, has ensured the structural integrity, vibration mitigation, and marine certification compliance for large, high-density equipment employed in outdoor settings. The modular power interface unit (PIU) designed for the Taiwan Busway (TBC) project allows for flexible power configuration extension. Sinotech Engineering Consultants assisted with the full planning of JBL's trillion-dollar computing center in Indonesia. DCBBS has started the practical project implementation phase.Hsieh Chieh-shou (transliterated from Chinese), a director on Viscor Computing's board, stated that the DCBBS project is not intended as a conceptual demonstration but as an engineering solution based on the principles of deliverability and replicability.Unlike other teams that are still engaged in architectural design and strategic planning, the DCBBS project, led by Supermicro, EFC, and Chicony Power, has completed the setup of operational test lines, which include physical equipment integration, power configuration, and burn-in verification, and is ready to advance to the replication and delivery phase. As this model evolves, the team has been emulating the collaborative strategy of "national second-tier teams," thereby broadening the participation of Taiwanese firms possessing engineering and manufacturing expertise. This enables the metal and electromechanical sectors, which have faced challenges due to shifts in the global industrial landscape in recent years, to venture into computing infrastructure and pursue an additional transformation opportunity.Wang noted that the delivery approach of the DCBBS project offers significant advantages for implementing enterprises in both financial and engineering aspects. In engineering, factory modularization and pre-integration—including wiring, labeling, performance verification, and burn-in testing—conducted prior to shipment can substantially diminish the uncertainty and risk associated with repeated modifications during onsite construction abroad. Financially, acceptance and payment can come quickly after testing, shortening the project payback period and reducing foreign deployment and travel costs. He stated that this design allows computing power efforts to evolve into a business model with predictable delivery and cash flow patterns, rather than long-term investment ventures with low returns.DCBBS has shifted from a monolithic computing cabinet to a sustainably scalable modular system architecture. The team will subsequently release modules pertaining to generators, transformers, UPS, chiller units, control rooms, and coatings, while including a new 800V DC power architecture and cooling-in-rack design to improve the overall system's integrity and adaptability. Essential technical tasks, such wiring, labeling, integration, and testing, are consistently performed in Taiwan, thereby mitigating the unpredictability of international construction and expediting acceptance and payment processes. Wang emphasized that DCBBS's fundamental value is enhancing engineering and financial efficiency while maintaining the majority of high-value-added integration and verification operations in Taiwan, thereby establishing a sustainable platform for industrial competitiveness in the AI era.Credit: Easy Field Corporation
Thursday 8 January 2026
MICROIP Leads Edge AI Deployment at CES 2026
At CES 2026, the world's leading consumer and enterprise technology event, MICROIP Inc. (Emerging Stock Board: 7796), a Taiwan-based provider of ASIC design services and AI software solutions, is showcasing its latest advancements at the AI Applications Pavilion. The company is presenting its CAPS (Cross-Platform AI Powered Solutions) architecture and highlighting AIVO (AI Vision Operation), a flagship Edge AI platform that has already entered commercial deployment.Through a software-defined approach, MICROIP demonstrates how AI applications can be deployed across global environments with lower barriers to entry and higher operational efficiency - bridging the gap between proof-of-concept and real-world deployment.From Technology Demonstration to Operational AIDr. James Yang, Chairman of MICROIP, stated: "CES is not just a venue for showcasing technology—it is where AI must prove its real-world value. AIVO was not designed to maximize model benchmarks or raw hardware performance, but to address real deployment constraints in transportation security, smart agriculture, and autonomous systems, including heterogeneous network conditions, limited edge compute resources, and long-term operational costs.By starting from these real-world constraints, MICROIP has built AIVO as an Edge AI platform that can be deployed, operated, and maintained over time - allowing AI to become part of daily operations rather than remaining at the proof-of-concept stage."CES 2026 Focus: Turning Edge AI into Operational CapabilityCAPS is MICROIP's  cross-platform AI software design framework, developed to help customers define AI systems that are deployable and maintainable in production environments. At CES 2026, MICROIP presents AIVO as a reference implementation of CAPS, demonstrating how Edge AI evolves from pilot projects into scalable, operational systems.Positioned as the deployment-focused pillar within the CAPS architecture, AIVO addresses two of the most persistent challenges in Edge AI: bandwidth constraints and multi-task processing at the edge.Distributed Master–Client Architecture for Large-Scale Edge DeploymentTo support geographically distributed and large-scale deployments, AIVO adopts a master–client distributed architecture. Real-time inference is performed locally on edge devices, while system management and decision logic are centralized at the host level.Instead of streaming raw video data, edge nodes transmit only structured inference results and metadata. This design significantly reduces bandwidth requirements and allows the system to maintain centralized oversight and real-time responsiveness - even in 4G/5G or unstable network environments.Real-Time Heterogeneous Multi-Tasking at the EdgeAIVO integrates a dynamic resource scheduling mechanism that enables multiple AI models to run concurrently on a single hardware platform. In security scenarios, object detection, behavior analysis, and environmental sensing models can operate in parallel, with compute resources allocated dynamically based on task priority.This ensures that mission-critical events are processed and responded to in real time, even under constrained edge compute conditions.Proven Edge AI Applications Across Transportation, Agriculture, and Autonomous SystemsLeveraging its system architecture, AIVO has completed multiple international field validations and is now focused on high-reliability application domains worldwide:Transportation Security: AIVO is being rolled out across metro systems, railways, buses, commercial aviation, and airport environments. Edge-based AI enables real-time detection of anomalous behavior, with alerts integrated into control centers or government security systems—enhancing response capability without increasing manpower requirements.Smart Agriculture: Addressing labor shortages and an aging workforce in U.S. agriculture, AIVO uses computer vision to monitor livestock health and environmental conditions. Expert knowledge from experienced farmers is encoded into AI models, while optimized system design ensures stable operation under low-power and limited-network farm environments.AI Drones and Robotics: For infrastructure inspection and disaster response, AIVO strengthens on-device autonomy. Even in GPS-denied or connectivity-limited conditions, drones and robots can perform real-time object tracking and dynamic obstacle avoidance, expanding the use of autonomous systems in high-risk scenarios.CAPS Ecosystem: Software-Driven Hardware Through Global PartnershipsDr. Yang emphasized that CAPS represents MICROIP's holistic vision for AI software design services:"Through vertical integration of AIVO as the deployment platform, XEdgAI as the system development platform, and CATS as our custom ASIC service, we establish a core advantage where software defines hardware specifications and real-world applications validate design direction."To accelerate global adoption of this model, MICROIP announced at CES 2026 strategic partnerships with Axelera AI (Europe), Axiomtek, Lex System, and U.S.-based Physical AI and robotics integration startup Universal AI Services, forming an international Edge AI alliance.Through CAPS' cross-platform compatibility, MICROIP has integrated mainstream AI chip platforms with industrial-grade hardware to deliver end-to-end, software-defined hardware Edge AI solutions. This strengthens MICROIP's technical leadership within the Edge AI ecosystem and enables customers worldwide to deploy high-performance, low-power AI systems across transportation, agriculture, and robotics applications.CES 2026 Exhibition Information – Next-Generation Edge AI Solutions,Dates: January 6–9, 2026;Location: Las Vegas, USA; Hall: North Hall;Booth: #9277.For more information on MICROIP, please visit MICROIP website.
Thursday 8 January 2026
EDOM Unveils NVIDIA Jetson T4000, Powering Lightweight and Stable Edge AI
EDOM Technology (TWSE: 3048), Asia’s best solutions provider, today announces the introduction of NVIDIA Jetson T4000 edge AI module, addressing the growing demand from system integrators, equipment manufacturers, and enterprise customers for balanced performance, power efficiency, and deployment flexibility. With powerful inference capability and a lightweight design, NVIDIA Jetson T4000 enables faster implementation of practical physical AI applications.Powered by NVIDIA Blackwell architecture, NVIDIA Jetson T4000 supports Transformer Engine and Multi-Instance GPU (MIG) technologies. The module integrates a 12-core Arm Neoverse-V3AE CPU, three 25GbE network interfaces, and a wide range of I/O options, making it well suited for low-latency, multi-sensor, and real-time computing requirements. In addition, Jetson T4000 features a third-generation programmable vision accelerator (PVA), dual encoders and decoders, and an optical flow accelerator. These dedicated hardware engines allow stable AI inference even under constrained compute and power budgets, making the platform particularly suitable for mid-range models and real-time edge applications.For system integrators (SIs), the modular architecture of Jetson T4000, combined with NVIDIA's mature software ecosystem, enables rapid integration of vision, sensing, and control systems. This significantly shortens development and validation cycles while improving project delivery efficiency especially for multi-site and scalable edge AI deployments.For equipment manufacturers, Jetson T4000's compact form factor and low-power design allow flexible integration into a wide range of end devices, including advanced robotics, industrial equipment, smart terminals, machine vision systems, and edge controllers. These capabilities help manufacturers bring stable AI inference into products with limited space and power budgets, accelerating intelligent product upgrades.Enterprise users can deploy Jetson T4000 across diverse scenarios such as smart factories, smart retail, security, and edge sensor data processing. By performing inference and data pre-processing at the edge, organizations can reduce system latency, lower cloud workloads, and improve overall operational efficiency - while maintaining system stability and deployment flexibility.In robotics and automation applications, Jetson T4000 features low power consumption, high speed I/O and compact footprint make it an ideal platform for small mobile robots, educational robots, and autonomous inspection systems, delivering efficient and reliable AI computing for a wide range of automation use cases.NVIDIA Jetson product lineup spans from lightweight to high-performance modules, including Jetson T4000 and T5000, addressing diverse requirements ranging from compact edge devices and industrial control systems to higher-performance inference applications. With NVIDIA's comprehensive AI development tools and SDKs, developers can rapidly port models, optimize inference performance, and seamlessly integrate AI capabilities into existing system architectures.Beyond supplying Jetson T4000 modules, EDOM Technology leverages its extensive ecosystem of partners across chips, modules, system integration, and application development. Based on the specific development stages and requirements of system integrators, equipment manufacturers, and enterprise customers, EDOM provides end-to-end support - from early-stage planning and technical consulting to ecosystem enablement. By sharing ecosystem expertise and practical experience, EDOM helps both existing customers and new entrants to the edge AI domain quickly build application capabilities and deploy edge AI solutions tailored to real-world scenarios.For more information on NVIDIA Jetson T4000, please visit website.