Taipei, December 11, 2025: Dimerco Express Group ("Dimerco") has announced that it is strengthening its integrated, Asia-focused logistics solutions to help customers capture growth from AI and "Taiwan+, China+" manufacturing while managing risks from congestion, regulatory changes and shifting capacity

At COMPUTEX 2025, ASUS showcased its comprehensive AI infrastructure solutions, targeting the computing needs of data centers, edge computing, and a wide range of intelligent applications. With a robust product portfolio, ASUS brings to life the NVIDIA AI Factory vision, illustrating how AI will be deeply embedded into enterprise IT infrastructure. This evolution continues to drive forward applications and services that shape the future of AI and high-performance computing

Technology news, product launches and show highlights from the event attendees available for download (PDF).

Bitcoin's core infrastructure is continually being re-engineered with each Bitcoin blockchain upgrade. Consequently, these upgrades alter how Bitcoin is traded and how it moves throughout the market. Recent changes to the Bitcoin protocols have brought about shifts in the costs, speeds, and security of transactions, prompting market actors to reassess and reposition. The blockchain of Bitcoin is always in a state of refinement, and its underlying technology continues to strive for scalability, efficiency, and sustainability. But these upgrades entail much more than an optimization of code, as they can result in real-market reactions, influence trading volumes, and shift investor sentiment. This year, with improvements in the protocol, technical aspects have become a core factor that drives market dynamics. This article will examine recent blockchain developments, how updates on the network influence trading activity, why markets may react in a particular way, and what wider adoption trends indicate about Bitcoin's future. Recent developments in blockchain technologyThe Bitcoin network has undergone a number of key upgrades aimed at improving transaction throughput, reducing fees, and offering greater flexibility for future scaling. Perhaps the most salient consequence of these enhancements pertains to how they affect trading-most notably when market participants check the bitcoin price today. By utilizing publicly available APIs and exchange data, traders can track real？time price, volume, and volatility to better gauge how protocol changes feed into market conditions. In a similar vein, upgrades such as Taproot or further layer？2 enhancements will continue to drive faster validation and more efficient block propagation. These changes significantly enhance the network's value proposition and can have a measurable effect on the way users interact with Bitcoin.How network upgrades influence Bitcoin tradingUpgrades create short-term volatility from how developers propose upgrades and how it influence different market actors. For example, do block efficiency upgrades lower confirmation times and fee costs, and thus, encourage traders to reassess their positions?According to the Cambridge Centre for Alternative Finance, the Bitcoin network's efficiency continues to be a problem for market participants assessing the cost structure of transactions. Through modeling, the Centre explains the relationships, thus the reason trading volumes increase after an upgrade, as traders reposition from the expected upside.Upgrades also factor into liquidity; a set of upgrades to a protocol usually incites a spell of high trading activity across the markets; however, as the network's performance becomes more predictable, liquidity provision from the participants improves. Institutions expand their tranche sizes, retail users of the network adjust their trading sizes, and these change the order imbalance, order book depth, and spread.Market responses to protocol changesThe market response of Bitcoin to protocol changes may be nuanced, fusing technical optimism with risk awareness. Whenever there is an announcement or deployment of a major upgrade, it generates speculative trading whereby some actors buy in anticipation of long-term gains, while others hedge for possible delays or unintended issues. This has traditionally led to increased volumes and higher volatility as participants test whether the upgrade provides the touted benefits.After an initial disruption, markets settle down, but not always uniformly across all exchanges. Differences in technology adoption and node infrastructure often create divergence in how different exchanges price Bitcoin-especially when some platforms support new features sooner rather than later. With time, however, upgrades add to the resilience of the network and reinforce confidence in the development path taken by the blockchain. Trends in cryptocurrency adoption and investmentAdoption of Bitcoin and, more broadly, cryptocurrency is continuing to grow. According to global data from CoinLedger from mid？2025, approximately 562 million people globally now hold some form of crypto, which is roughly 6.8？per cent of the global population. This growth reflects not only increased retail interest but also broader institutional participation.Investment strategies increasingly reflect the technical trajectory of the network: As upgrades to the blockchain offer greater scalability and efficiency, investors signal demand for digital assets built on sustainable and performant protocols. On the exchange side, platforms are continuing to deploy tools-real？time analytics, risk？management dashboards and more responsive execution systems-to help traders gauge how technical changes might impact their portfolios.Institutional interest also responds to environmental and sustainability themes. Energy usage, consensus efficiency, and mining footprint have become increasingly linked to blockchain upgrades and investment sentiment. Ongoing research into electricity consumption and mining emissions continues to impact the way some investors value Bitcoin in the context of long？term ESG objectives. Future implications for Bitcoin trading and innovationThe pace of protocol development at Bitcoin suggests that upgrades will continue to play a leading role in its market story. The more efficiently the network can scale, the more transaction costs can shrink, and open up space for more entrants, both retail and institutional. Technical change will continue to drive market actors' responses, but over time, improvements in capacity and sustainability could stabilise the asset's financial profile. This upgrade is not limited to short-term trading effects only. Modifications made in technology transform one's viewpoint regarding Bitcoin as a digital unit: more expandable, effective, and better aligned with anticipated infrastructural priorities in the future.Knowledgeable changes in a protocol and their impact on trade and adoption trends, as the participants in the market comprehend them better, clarify Bitcoin's position in the rapidly changing world of crypto.

Seoul, December 18, 2025 – SK hynix Inc. (or "the company", www.skhynix.com) announced today that it has become the first in the industry to complete the Intel Data Center Certified process to apply 256GB DDR5 RDIMM1 - a high capacity server module based on 32Gb fifth-generation 10nm-class (1b) DRAM - to Intel Xeon 6 platform.As an Intel Data Center Certified system/platform, 256GB DDR5 RDIMM has completed extensive testing and rigorous validation by Intel's Advanced Data Center Development Laboratory, and is now the industry's first server module verified to provide reliable performance, compatibility and quality when combined with Intel Xeon processors. SK hynix has previously obtained similar validation in January this year for its 16Gb fourth-generation 10nm-class (1a) die-based 256GB product.By becoming the first in the industry to validate compatibility with Intel's latest server platform, SK hynix is demonstrating technological leadership in high-capacity DDR5 modules. Based on this, the company will expand cooperation with major global data center operators and continue to lead the next-generation memory market in response to rapidly increasing demand from server customers.In this new AI-driven infrastructure environment, memory has emerged as a critical determinant of performance. As AI inference models evolve beyond generating simple response to performing complex logical processes, the volume of data that must be processed in real time is growing exponentially. To manage these massive data sets swiftly and reliably, high-capacity and high-performance memory has become indispensable - driving a sharp increase in market demand.The company anticipates its latest product to be the ideal solution to meet this growing demand. Servers equipped with the new module deliver up to 16% higher inference performance compared with those using 32Gb die-based 128GB products. In addition, by utilizing 32Gb DRAM chips, the design achieves up to approximately 18% lower power consumption than previous 256GB products based on 16Gb 1a DRAM. With this improved power efficiency and outstanding performance per watt, the company expects strong interest from data center customers."We are now able to respond more swiftly to customer needs, solidifying our leadership in the server DDR5 DRAM market. As a full-stack AI memory creator, we will actively address the growing demand for high-performance, low-power, and high-capacity memory solutions to further enhance customer satisfaction." said Sangkwon Lee, head of DRAM Product Planning & Enablement at SK hynix."This achievement represents the culmination of collaborative engineering efforts across Intel and SK hynix and demonstrates our shared commitment to advancing memory technology. The high-capacity module addresses the increasingly demanding requirements of capacity-hungry workloads of AI applications, enabling our customers to unlock new levels of performance and efficiency in their data center operations," said Dr. Dimitrios Ziakas, VP of Platform Architecture, Intel Data Center Group.

Taipei As generative AI, software-defined vehicles, and intelligent automation accelerate in parallel, semiconductors are shifting from component suppliers to a critical foundation for intelligent systems in the physical world. At the recent 2025 NXP Technology Summit held in Taipei, NXP had focused on three major application pillars, AI, IIoT, and automotive electronics, working closely with Taiwan industry partners to bring smart technologies into real-world deployments.NXP as a System Platform Enabler Building a New Foundation for Smart Applications with AI × Edge × SDVRobert Li, Executive Vice President and General Manager of BL Greater China for NXP Semiconductors, noted in his keynote that the semiconductor industry follows a ten-year growth cycle, from PCs and smartphones to the current wave driven by automation, cloud computing, and Edge AI.By 2030, the market is expected to reach USD1.3 trillion. As data generated by edge devices continues to surge, sending everything back to the cloud would create bottlenecks in bandwidth, energy consumption, and latency, making real-time decision-making difficult. As a result, AI must move from the cloud to the edge.He further pointed out that AI is evolving from perceptual and generative stages toward a new era of Agentic AI and Physical AI, with applications in factories, autonomous driving, robotics, and energy systems at scale. To address this shift, NXP has transformed from a chip supplier into a system-level platform and ecosystem provider, integrating compute, connectivity, power, and security architectures. Through key acquisitions such as TTTech Auto, Aviva Link, and Kinara, NXP has strengthened its SDV(software-defined vehicles) and Edge AI capabilities while deepening Taiwan's strategic role in global R&D and application deployment.Stefan Poledna, CEO and CTO of TTTech Auto, stated that after joining NXP, TTTech Auto can more efficiently drive SDVs from concept to production-ready, system-level implementation. With more than a decade of experience in automotive software, system integration, and functional safety, the company has built a team of nearly one thousand engineers. Its software has been deployed in over five million vehicles, with more than sixteen million project instances under ongoing development, serving major automakers across Europe and Asia.Its capabilities span SDV core software, functional safety and cybersecurity services, as well as hardware reference designs supporting heterogeneous multi-chip architectures. These are deeply integrated with NXP automotive platforms to enhance overall system scalability. Based on this architectural approach, TTTech Auto has contributed its technical strengths to the NXP CoreRide system-level platform.As generative AI, intelligent automation, and vehicle electrification continue to advance, global computing is shifting from the cloud back toward edge nodes closer to real-world environments, driving devices from being merely connected toward becoming autonomous. Luca Difalco, Senior Vice President of Global Channel Sales and Industrial Solutions at NXP Semiconductors, noted that the industry is moving from smart devices to autonomous intelligent edge systems with sensing, reasoning, and action capabilities. Where early devices relied on cloud-based decision-making, today's systems can perform AI inference at the edge under low power conditions and respond in real time, enabling truly deployable intelligent applications.In this context, he explained that NXP's core mission is not to expand cloud computing power, but to build Intelligent Nodes that can be deployed at scale, allowing AI to be realized in vehicles, factories, buildings, and healthcare environments. The value of AI lies not in model size, but in whether edge systems can perform timely inference and take the right actions. However, Edge AI involves sensing, power, security, connectivity, and data management, making integration far more complex than traditional embedded design.To address this, NXP adopts a modular, stackable architecture to simplify complexity and has established a tiered hardware platform spanning MCX and S32K MCUs to i.MX MPUs, gateways, zonal, and central compute, combined with Kinara NPUs for smooth scalability based on performance needs. On the software side, NXP provides a unified development workflow through eIQ and Time Series Studio, enabling even non-AI specialists to deploy models quickly, while building trusted AI foundations with Root of Trust, Secure OTA, post-quantum cryptography, and AI bias detection.Industrial IoT and Smart Mobility Tracks Reveal the Complete Path to AI DeploymentBeyond the keynotes, the summit featured two major tracks, Smart Industrial and IoT and Smart Mobility, led by NXP technical experts. These sessions comprehensively showcased NXP's technology roadmap across edge computing, connectivity, security, and AI, linking industrial, IoT, and automotive applications and illustrating the full evolution of future intelligent systems from perception to inference and action.The Smart Industrial and IoT track began by outlining how the industrial market is rapidly shifting from automation toward software-defined systems. Equipment now requires real-time computing, reliable connectivity, and higher energy efficiency to support the long-term evolution of smart factories and intelligent infrastructure. The NXP team further analyzed its MCU, MPU, connectivity, and AI NPU portfolio, demonstrating how scalable modular architectures reduce integration complexity and enable developers to move from design to deployment in shorter timeframes.In AI applications, NXP showcased practical deployments of generative and autonomous AI in industrial control equipment and IoT nodes, enabling devices to collect data, perform inference, and make on-site decisions without relying on the cloud. Experts also introduced next-generation intelligent power solutions that improve system efficiency and operational reliability, along with NXP's latest wireless connectivity technologies that ensure stable communication in high-noise, large-scale industrial networks. Applications span medical devices, smart buildings, humanoid robots, and industrial automation, all centered on edge computing, sensor fusion, and high-reliability connectivity.Finally, the team presented a comprehensive Edge Lock security strategy, providing protection from system boot to data exchange, covering OTA updates, helping enterprises maintain long-term trusted security foundations while scaling IoT deployments.In the Smart Mobility track, NXP brought together experts in automotive electronics, connectivity, and AI to provide an in-depth analysis of smart mobility trends and system architectures. The session began with market insights into the acceleration of vehicle electrification, electronics integration, and software-defined vehicles, followed by NXP's holistic solutions across sensing, control, connectivity, and security.New-generation automotive platforms such as S32K5 and CoreRide were then introduced, highlighting how scalable architectures, functional safety, and software reusability support rapid SDV iteration. As AI continues to penetrate in-vehicle edge nodes, experts demonstrated edge inference applications in driver monitoring, environmental perception, and behavioral decision-making, and explained how i.MX processors combined with wireless connectivity are advancing in-vehicle infotainment and intelligent cockpits.To address vehicle connectivity and high-speed data exchange demands, the session also explored the latest automotive Ethernet roadmaps and the high bandwidth and low latency advantages enabled by NXP's 10Gbps Ethernet switches. On electrification, X-in-1 integration solutions and 48V power conversion technologies were presented, underscoring the importance of efficient power management in future EV architectures. Overall, the track covered computing, connectivity, AI, security, and power architectures in a comprehensive manner, defining NXP's core position and forward-looking vision within the smart mobility ecosystem.In addition to keynote and technical sessions, the summit featured more than seventy technology showcases from NXP, ecosystem partners, and sponsors, helping customers understand market trends while gaining deeper insight into how NXP enables the real-world deployment of advanced technologies.In summary, NXP demonstrated how edge intelligence moves from concept to large-scale deployment through comprehensive computing platforms, trusted security architectures, and cross-industry application examples. Whether in industrial IoT, smart mobility, or emerging autonomous systems, the key lies in bringing AI into real-world environments with higher efficiency, lower power consumption, and greater predictability. As Taiwan's influence across technology and ecosystem value chains continues to grow, NXP will keep working closely with local partners to drive the next phase of global edge intelligence adoption.Credit: NXP