The dream of a world without charging cables - where phones, headsets, and even industrial robots never need to be plugged in - is moving from science fiction to reality. AWL Electricity, often referred to by partners as All Electricity, is at the forefront of this shift by leveraging advanced semiconductor breakthroughs to deliver power wirelessly over distance. As the company prepares for COMPUTEX 2026 in Taipei this June, it aims to solidify its position as the global leader in mid-power, mid-range wireless charging.The Breakthrough: GaN and the Five-Foot RadiusThe foundation of AWL Electricity's technology lies in a scientific leap made in 2017 by the invention of CEO Emmanuel Glenn. While the concept of wireless power dates back to Nikola Tesla, traditional low-frequency methods were often unsafe or impractical due to the extreme power required at low frequencies. By utilizing Gallium Nitride (GaN) transistors, the company successfully increased operating frequencies while reducing electric field strength, making the technology safe and highly practical.Unlike standard charging pads that require direct contact, AWL-E's Resonant Capacitive Coupling technology focuses on a 1.5-meter (five-foot) radius. Francis Beauchamp-Verdon, Co-Founder and Chief Revenue Officer, explains that human moves around within a five-foot bubble, whether at a desk, in a car, or at a café. While the company remains "planet-centric" and advises that high-power stationary devices like coffee machines or electric vehicles should remain wired for maximum efficiency, wireless power is reserved for mobility and devices where cables create significant friction.Transforming Industry 4.0Beyond consumer electronics, AWL-E is targeting the "New Age of Physical AI" and smart manufacturing. Modern factory lines can require between 40,000 to 50,000 sensors, with an automotive leader noting that every single wire adds significant connection costs. AWL-E's solution eliminates the need for traditional cable management and drag chains into robotic cells. By powering humanoids and autonomous guided vehicles (AGVs) while they work, factories can eliminate 20% downtime typically lost when robots must sit next to a charging wall.Strategic Objectives for COMPUTEX 2026Taiwan holds a special place in the AWL-E story, as its semiconductor ecosystem enabled the company's initial breakthrough. During the COMPUTEX 2026 mission, the company seeks to collaborate with Taiwanese chip leaders to transition their technology into a dedicated Wireless Power Chip, which would make the solution smaller, cheaper, and more accessible. Additionally, the company hopes to help Taiwan improve its own chip-making tools, specifically in vacuum environments where wires are a "worst enemy," creating a symbiotic relationship where AWL-E powers the machines that build the chips.Beauchamp-Verdon will be carrying a portable demo unit to the event to prove that this innovation is ready for today's market. He believes that seeing technology in action is essential for the Taiwanese industry, where "seeing is believing" is a core mindset. AWL-E currently maintains flagship projects in consumer electronics, automotive, and factory automation across Asia and intends to use this visit to find the right partners for their next level of expansion.

As global manufacturing accelerates its smart-factory transition, computer vision is taking on an increasingly critical role in industrial quality inspection. Canadian AI startup DaoAI, on the strength of its innovative AI vision technology, has secured partnerships with international heavyweights including Siemens and BASF. Co-founder and CTO Xiaochuan Chen explains how DaoAI uses "Feature Cognition Inspection" to solve the high false-call rates and time-consuming programming pain points of traditional Automated Optical Inspection (AOI), and reveals plans to actively pursue deeper partnerships with Taiwanese equipment makers and distributors during COMPUTEX 2026.From Academic Research to Industrial Practice: Bringing AI to the Electronics Manufacturing FloorDaoAI CTO Xiaochuan Chen has been working in AI and vision research in Canada since 2014 - right at the inflection point of deep learning. In 2017, he co-founded DaoAI in Vancouver alongside a partner with a track record of successful entrepreneurship, leading a top-tier AI vision team drawn from University of British and University of Waterloo and focused squarely on industrial automation.Chen sees enormous potential for AI in manufacturing across both North American and Asian markets. DaoAI's technology not only lifts production yield but also protects enterprise data sovereignty through its on-premise data architecture. "We understand that in any digital transformation, the security and ownership of data is a core interest for manufacturers - and that's the foundation our technology is built on," Chen says.Solving the Long Programming Cycles and High False-Call Rates of Traditional AOITraditional AOI algorithms running on PCBA (printed circuit board assembly) inspection lines are notorious for high false-call rates. Chen explains that conventional algorithms rely heavily on color matching or pixel-level comparison - when, for example, a resistor and the board substrate are both black, traditional algorithms struggle to tell them apart.DaoAI's core technology is Feature Cognition Inspection. The model is pretrained on a dataset of more than one million images, abstracting what the AI sees into a specialized feature space. The advantages show up at two levels: 1. Multi-dimensional differentiation: the AI no longer compares colors - it precisely distinguishes whether a defect is present on a component within feature space. 2. Continuous learning: the system mirrors how humans learn. If the AI gets a call wrong on the first pass, the inspector's feedback is fed into its memory system, so the next time a similar component appears, the same mistake doesn't recur."We pretrain a PCBA-specific inspection model on real production-line data," Chen explains. "All the customer needs is a single 'reference board.' Without any CAD file or component library, the AI identifies the location of every component, automatically generates inspection regions, and automatically calculates thresholds. Programming can be done in seconds or minutes - the AI takes over the part of AOI that historically required the most human intervention."This kind of fast programming is especially well-suited to high-mix, low-volume production. It dissolves the bottleneck that NPI (new product introduction) phases used to hit, where modeling was slow and dependent on dedicated programming engineers.Solving the Compute-and-Sovereignty Trade-off Without Cloud DependenceFor data sovereignty and information security issues that customers care about deeply - DaoAI runs 100% on-premise. To deliver high performance within the limited compute budget of edge hardware, DaoAI takes a "pretraining + rapid fine-tuning" approach: customers run a pre-tuned, optimized specialty model locally while keeping their data fully secure.Cross-Border Partnerships and the COMPUTEX Strategy: Complementing Taiwan's Supply ChainDaoAI has already established deep partnerships with Siemens (electronics manufacturing and automation platform integration) and BASF (vision analysis applications in chemicals). Looking ahead, Chen is bullish on the Taiwan market and announced that DaoAI will participate in COMPUTEX for the first time this year.DaoAI positions itself as a vision-AI application company, Chen says, and the trip to Taiwan has two strategic objectives: 1. Hardware integration: partner with local Taiwanese equipment manufacturers to combine DaoAI's AI software algorithms with Taiwan's high-quality hardware, delivering customized solutions. 2. Distribution expansion: identify professional distributors and service partners in Taiwan to get closer to local electronics manufacturing customers.Beyond Surface Mount Technology line inspection, DaoAI is also strongly interested in semiconductor packaging and testing and is looking to co-develop new applications with Taiwanese probe and inspection equipment makers - pushing the boundaries of vision AI further still.

As Low Earth Orbit (LEO) satellite competition intensifies, satellite communication has evolved from a terrestrial supplement into a core infrastructure for AI and cloud services. Emtar Technologies, a Canadian chip design startup founded by Taiwanese-Canadian entrepreneur Alvis Huang, is emerging as a critical player in this shift. Leveraging his background as a Marconi Young Scholar, Huang has led Emtar to develop groundbreaking 6G Non-Terrestrial Network (NTN) chips that have already garnered support from TSMC and the Canadian government.Breakthrough Performance: The "Private Library" ArchitectureAt the recent TSMC North America Technology Symposium, Emtar conducted a Live Demo of its 6G NTN solutions, demonstrating high strategic value to the semiconductor supply chain. Emtar's chipset - comprising high-performance RF Front-End ICs and Intelligent Beamforming chips - acts as the system's "sensory organs and brain."Unlike traditional architectures where transceivers must "queue" to access shared memory (SRAM), Emtar utilizes a disruptive fully embedded memory design paired with proprietary algorithms. This gives each transceiver a "private library" for instantaneous data scheduling, resulting in: 1. 10x faster tracking and position prediction. 2. 2x higher reception sensitivity. 3. Significant power savings (dozens of watts), solving critical heat dissipation issues for satellite equipment.National Recognition and Global ExpansionEmtar's strategic importance is backed by high-level Canadian endorsement. Emtar participated in a Canadian trade mission to South Korea led by Minister Maninder Sidhu, where the company engaged with potential satellite industry partners. Additionally, Emtar was named "Startup of the Year" by Canada's Semiconductor Council (CSC), an organization featuring industry titans like AMD, Intel, and Qualcomm.The Future: Data Centers in SpaceHuang anticipates the LEO market will reach 2 billion users within seven years, driven by "Data Centers in Space." Cloud providers are eyeing orbital AI deployments to mitigate terrestrial geopolitical risks. This shift demands high-efficiency satellite access for everything from autonomous drones to maritime vessels - these are Emtar's primary target market.With products entering mass production by year-end, Emtar is currently engaging with Taiwanese ODMs and space agencies during COMPUTEX Taipei. As products head toward mass production by the end of the year, Emtar plans to launch its Series A funding round. Huang emphasized that he is looking for investors with Silicon Valley experience who can provide top-down strategic resources to help Emtar connect with tier-one global satellite operators. From a Canadian startup to an industry star, Emtar is poised to leave its mark on the 6G space race, blending Taiwanese entrepreneurial resilience with North American technical innovation.

As the global technology industry descends on Taipei for COMPUTEX 2026 this June, a Canadian startup is preparing to challenge the fundamental architecture of modern processing. Irreversible, a Montreal-based firm with deep roots in quantum computing, is unveiling a "physics-first" analog in-memory computing architecture that promises a staggering 1,000x reduction in power consumption compared to conventional digital processors.Unlike many silicon startups that originate in traditional chip design, Irreversible’s journey began in the highly constrained world of quantum physics. The core team originally specialized in quantum computing, where they were forced to solve computing problems within the extreme limitations of a dilution refrigerator - an environment where even the slightest heat or noise can destroy a fragile quantum state. Co-Founder Dominic Marchand explains that this background led them to become a "computing company that found its way to designing chips," rather than the reverse. This unique DNA pushed the team to strip away decades of architectural abstractions and return to the most basic laws of physics to find the most energy-efficient ways to process information.The current industry obsession with massive Large Language Models (LLMs) has created a significant energy crisis, particularly at the "extreme edge" where devices must operate on microwatt-class power. Irreversible addresses this by sidestepping the Von Neumann bottleneck, the energy-intensive movement of data back and forth between memory and the processor. By performing calculations directly in memory and maintaining a fully analog signal path, Irreversible also eliminates the power-hungry digital-to-analog conversions that often limit hybrid AI chips. This approach recognizes that while digital logic offers noise protection, the energy required to strictly maintain ones and zeros is a luxury that edge sensors can no longer afford.A critical point of differentiation is how Irreversible compares to other innovators in this space. Marchand notes that while he is proud of the Canadian leadership in analog in-memory compute, Irreversible maintains several distinct advantages. First, the company is memory-agnostic, meaning they are not tied to a single proprietary memory technology and can instead utilize various non-volatile memories and emerging RRAM roadmaps. Second, the company places extraordinary emphasis on its software and simulation tools, which allow their hardware and software teams to work in lockstep. Their proprietary hardware-aware training ensures that neural networks remain accurate by accounting for the inherent variability of analog circuits during the initial training phase.For their up-coming visit to Taipei, Irreversible has set clear strategic objectives to integrate with the world's leading semiconductor ecosystem. A primary goal is establishing high-level connections with semiconductor foundries to gain privileged access to specific memory cells, which are essential for their "physics-first" custom designs. Additionally, the company is actively seeking partnerships with OEMs and solution integrators. By bringing intelligence directly to the sensor site, Irreversible aims to enable "previously impossible" use cases, such as deploying sophisticated AI on small drones or always-on wearable devices that cannot support a traditional GPU. Ultimately, Irreversible arrives in Taipei not just to showcase a chip, but to advocate for a shift in how the world thinks about intelligence. By trading the rigid certainty of digital bits for the natural efficiency of physics, they are proving that the future of AI isn't just about more power - it's about more efficient computing.

Test Research, Inc. (TRI), the leading provider of Test and Inspection solutions for the electronics manufacturing industry, is proud to announce the launch of the TR7950Q SII Series. This highly modular platform is a dedicated solution for Back End Process and Advanced Packaging Inspection, ranging from patterning to wafer saw, and is engineered to set new benchmarks in wafer inspection and micro-measurement metrology.The AI-powered Wafer Metrology and Inspection Platform, TR7950Q SII, is built on a high-stability granite platform and the system supports 6" to 12" wafers. The platform features robust Automated Visual Inspection (AVI) for high-speed detection of surface defects, including particles, scratches, chipping, contamination, and foreign materials.The optional Short-Wave Infrared (SWIR) module allows the system to penetrate silicon to detect hidden inner cracks and subsurface defects invisible to standard sensors. For high-detail requirements, the platform offers 0.5 µm or 1 µm high-resolution imaging via the 3D DFF (Depth from Focus) module.The TR7950Q SII provides high-precision metrology for wafer thickness, top-side warpage, and complex surface topography, alongside high-speed sensing for Through-Silicon Via (TSV) depth, trench dimensions, thin film, and Chiplet metrology. Please visit the link to learn more about the TR7950Q SII.Credit: TRI

Global Unichip Corp. (GUC), the Advanced ASIC Leader, today announced a strategic technical collaboration with Wiwynn, an innovative cloud IT infrastructure provider for data centers. This collaboration integrates GUC's flagship SoC design and 2.5D/3D advanced packaging with Wiwynn's expertise in rack-scale system integration, liquid cooling and optical interconnect. Together, the collaboration enables hyperscale customers to transition more efficiently from silicon definition to deployment-ready AI infrastructure.AI clusters continue to scale in performance, bandwidth and power density, hyperscalers must increasingly evaluate silicon, packaging, interconnect, thermal and rack-level design choices much earlier in the development cycle. Through this collaboration, GUC and Wiwynn are aligning key technology pillars, including leading-edge ASIC implementation, 2.5D/3D advanced packaging, optical I/O, power delivery, thermal architecture, manufacturability, serviceability and rack-scale integration. By addressing these factors holistically at the outset, the collaboration partners aim to reduce integration complexity, improve development efficiency and accelerate the transition from silicon-ready innovation to system-ready AI infrastructure."As AI infrastructure evolves beyond chip-level optimization and scale-up networks push the limits of conventional electrical interconnects, close alignment across silicon to system architecture become critical," said Aditya Raina, Chief of Marketing of GUC. "By collaborating with Wiwynn, we are helping hyperscale customers evaluate critical system-level tradeoffs earlier, integrating optical I/O to deliver the bandwidth and power efficiency required for next generation AI systems. This partnership establishes a more practical, holistic path from flagship ASIC development to deployable, rack-scale AI infrastructure."With deep expertise across board-level innovation, rack-scale integration, and manufacturing, Wiwynn effectively bridges semiconductor innovation with data center deployment," said Tony Wen, Vice President at Wiwynn. "Together with GUC, we are enabling a comprehensive silicon-tosystem approach that delivers scalable, efficient and serviceable AI infrastructure tailored for nextgeneration hyperscale environments."For more information, please visit.

Cincoze has unveiled its all-new CV-200 Series slim-bezel industrial displays. The CV-200 Series features a minimalist profile, a narrow bezel, and industrial-grade reliability for industrial panel PCs and industrial touch monitors. Specifically engineered for modern factory HMI and process visualization, they carefully balance the durability required for harsh environments with seamless equipment integration and intuitive operation. The modular design of the CV-200 Series offers screen sizes from 10 to 21.5 inches for over 40 possible configurations. The first release is the 21.5" Full HD models with almost ten configuration options for various application needs.Ultra-Slim Bezel, High Visibility, and an Intuitive User ExperienceThe CV-200 Series offers clear visuals and smooth operation, and integrates easily into production line equipment. Its slim, die-cast aluminum alloy frame has a bezel less than 3mm wide, increasing the display area without changing existing equipment setup. The Full HD screen and 178° wide viewing angle ensure clear and crisp readability from any position. Every model features a projective capacitive (P-Cap) touchscreen with an anti-glare (AG) coating for the clearest images, even in high-brightness indoor lighting conditions. Touch response is fast and precise, making daily HMI operation smoother and more natural.Rugged and Durable for Industrial and Humid EnvironmentsThe CV-200 Series is built to handle harsh, humid industrial environments. It has an IP66-rated front panel and Wet Tracking technology, so the touchscreen works reliably even with wet fingers or splashes of water. The backlight lasts up to 50,000 hours, and a 7H hardness Glass-Glass (GG) panel adds durability. The CV-200 Series meets the IEC 61000-6-4 industrial EMC standard, ensuring stable, long-term operation and giving operators total peace of mind.Flexible Modular DesignCincoze's exclusive Convertible Display System (CDS) technology lets you pair the CV-200 Series with embedded computer modules (P2000/P1000 Series) or monitor modules (M1000 Series). Customers can configure the system as either an industrial panel PC or an industrial touch monitor, depending on display size, computing performance, and functional requirements. This plug-and-play design simplifies deployment and maintenance. If repairs are needed, only a single module needs to be replaced, cutting downtime, lowering maintenance costs, and streamlining future upgrades.

Chroma ATE Inc. successfully concluded the 3rd Chroma Paper Award on March 19, marking another milestone in the company's ongoing commitment to industry-academia collaboration. Organized in partnership with National Taiwan University of Science and Technology (Taiwan Tech), the Chroma Paper Award provides an exchange platform that accelerates the translation of research into real-world applications, fostering innovation and the cultivation of key talent.As high-performance computing (HPC) and AI applications continue to advance rapidly, demand for test and measurement technologies is rising across AI chips, HPC, and data centers. In this era of lightning-fast iteration, testing and validation have become critical enablers of system performance and reliability. With long-standing expertise in this field, Chroma has built comprehensive AI-related testing capabilities spanning the four core pillars of AI infrastructure: compute and data processing, cooling and thermal management, high-speed communications and data transmission, and power and energy management. Through its test and validation solutions, Chroma helps ensure the performance, stability, and reliability of AI systems, playing a vital enabling role across the AI value chain.Aligned with Chroma's core technology development priorities, this year's competition featured two main categories: Power Electronics-Related Technologies and Semiconductor Testing-Related Technologies. Each category included a Top Prize (NT$200,000), Excellence Prize (NT$100,000), and Merit Prize (NT$20,000), with total prize funding reaching nearly NT$1.5 million. A total of 101 papers were submitted. Following a multi-stage evaluation process comprising preliminary, secondary, and final reviews, the judging committee selected outstanding research projects distinguished by both technical innovation and strong potential for industrial application.In the Power Electronics-Related Technologies category, the Top Prize was awarded to a team from Taiwan Tech for the project "Development of a High Power Density Power Module for AI Server Applications." Supervised by Associate Professor Yu-Chen Liu and completed by student Yu-Jun Li, the project directly addresses the growing need for high-efficiency, high-power-density power systems in AI data centers.In the Semiconductor Testing-Related Technologies category, the Top Prize went to a team from National Taiwan University for the project "A Novel Full-Chip Afterpulsing Evaluation Technique for 116 x 160 Ge-on-Si SPAD Array." Supervised by Professor Chao-Hsin Wu and jointly completed by students Jia-Zhen Cai, Ren-Hong Zhang, and Qi'en Chen, the research presents innovative achievements in advanced sensing and semiconductor testing technologies.Following the award ceremony, Chroma invited finalist teams into its R&D labs and testing facilities to see firsthand how research outcomes are transformed into real systems and industrial applications. The visit further strengthened ties between academia and industry.As the AI era continues to evolve at speed, test and measurement serves not only as a gatekeeper of quality but also as a key engine of innovation. Looking ahead, Chroma will continue to deepen its engagement with the global academic community through the Chroma Paper Award and a range of industry-academia collaboration initiatives, building an open and impactful platform that advances key technologies and sustains innovation momentum across the industry.For the full list of award winners, please visit the official Chroma Paper Award website.President Jia-Yush Yen of National Taiwan University of Science and Technology delivers remarks. Credit: ChromaCredit: ChromaFinalist students pose for a group photo with Chroma Foundation Chairman Paul Ying. Credit: ChromaChroma ATE Chairman Leo Huang (left) poses with the Top Prize-winning student Yu-Jun Li. Credit: ChromaChroma ATE Chairman Leo Huang (left) poses with the Top Prize-winning student Jia-Zhen Cai. Credit: ChromaFinalist teams visit Chroma headquarters. Credit: ChromaGroup photo at the 3rd Chroma Paper Award ceremony and banquet. Credit: ChromaChroma ATE Chairman Leo Huang delivers remarks. Credit: ChromaChroma Foundation Chairman Paul Ying delivers remarks. Credit: Chroma

The rapid advancement of generative artificial intelligence (GenAI) has significantly enhanced the efficiency of content creation and dissemination. At the same time, it has accelerated the proliferation of misinformation, manipulated content, and digital fraud, posing increasing challenges to democratic governance, social stability, and the integrity of digital trust and information ecosystems. In this context, achieving a balance between technological innovation and risk governance, while strengthening a trusted information environment, has become a key priority for both government and industry in Taiwan.Concurrently, the global expansion of virtual asset investment has prompted jurisdictions worldwide to strengthen regulatory frameworks governing digital asset transactions. Despite these efforts, fraudulent activities involving virtual assets continue to evolve in both scale and complexity. Malicious actors frequently exploit nominee accounts to conduct layered money laundering schemes, resulting in delayed fraud detection and challenges in asset recovery. Conventional approaches -including static blacklists and rule-based controls-are increasingly insufficient to address these evolving threats. As a result, the development of highly interpretable, AI-enabled early warning mechanisms to support timely risk identification and mitigation has emerged as a critical focus for both policymakers and industry.Against this backdrop, Team Bibi Lab, comprising students from National Tsing Hua University (NTHU), was awarded top honors in the "Virtual Asset Transaction Security" category-sponsored by BitoPro, a cryptocurrency exchange under BitoGroup-at the "Agent for Truth: Disinformation Defense Hackathon." Their project, "AI Anti-Fraud Guardian for Virtual Currency Transactions," demonstrated a high degree of technical innovation and real-world applicability, earning strong recognition from the judging panel.Team Bibi Lab extracted 140 features across 18 categories from KYC, fiat currency, and cryptocurrency transaction data provided by BitoPro. At the core of their approach is an innovative "three-layer risk tracking mechanism," which analyzes shared wallets, shared IP addresses, and indirectly connected users to trace how risk propagates through the transaction network-forming one of the system's most critical signal sources.To ensure high interpretability and support compliance requirements, the team deliberately avoided complex ensemble models that could obscure decision logic. Instead, they adopted LightGBM combined with Focal Loss, enabling the model to focus on hard-to-detect minority cases and effectively address severe data imbalance.In addition, the team constructed a network graph of internal transfers, shared wallets, and common IP addresses using NetworkX. By applying algorithms such as PageRank and community detection, they identified critical relay nodes within fund flows, further strengthening the system's ability to uncover hidden fraud patterns.The competition was powered by Amazon Web Services (AWS), whose cloud infrastructure enabled Team Bibi Lab to build a comprehensive AI-driven anti-fraud system. Their solution features a four-layer interpretability architecture: "Continuous Risk Scoring and Tiering," which classifies users into four risk levels from low to extremely high; "Feature Deviation Analysis," which visualizes how user behavior diverges from baseline norms; "Rule-Based Interpretation," which generates automated textual explanations; and an "AI Risk Diagnosis Report," which leverages the Claude 3.5 Haiku on Amazon Bedrock to generate professional compliance analysis reports.The system is built on a robust AWS cloud stack. The solution is deployed on Amazon Elastic Compute Cloud (Amazon EC2), with raw data and feature matrices stored in Amazon Simple Storage Service (Amazon S3), and AWS Glue handling ETL and feature engineering. AWS Lambda supports batch risk scoring, while AWS Step Functions orchestrates the end-to-end workflow. For high-risk cases, Amazon Simple Notification Service (Amazon SNS) sends real-time alerts to compliance teams, and Amazon CloudWatch ensures system monitoring and alerting-demonstrating the breadth and scalability of AWS cloud services in supporting advanced AI application development.Team Bibi Lab noted that, despite their background in AI development, they had no prior experience with AWS cloud services. Prior to the competition, AWS organized a series of technical workshops-covering AI applications and enterprise data-enabling the team to quickly build proficiency with relevant tools and services.With guidance from BitoPro mentors and industry experts, the team deepened its understanding of cryptocurrency operations. They also incorporated key design principles-including "auditability for compliance personnel" and "automated risk alerting" -into their solution, ultimately delivering a practical, deployable anti-fraud system that contributes to a more resilient and trustworthy digital financial ecosystem.

SK hynix Inc. (or "the company", www.skhynix.com) announced today that it received the Corporate Innovation Award at the '2026 IEEE1 Honors Ceremony' held in New York on the 24th (local time).IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Established more than a century ago, the IEEE Awards Program recognizes individuals and teams whose innovations have advanced technology and improved the human condition.The IEEE Corporation Innovation Award, part of the Recognitions category, has been presented since 1986 to companies that have significantly contributed to the advancement of industry and society through innovative technology. This marks the first time SK hynix has received this honor.SK hynix attributed the honor to its contribution to the global AI computing ecosystem by ensuring the stable mass production of all High Bandwidth Memory (HBM) generations. Looking ahead, the company aims to solidify its position as a trusted partner in the global AI market by providing memory solutions that are critical to overcoming the performance limitations of AI platforms.The recognition highlights SK hynix's achievements in driving the expansion of AI computing through HBM innovation and application. Central to this success was the company's ability to preemptively offer innovative HBM solutions and respond timely to customer demands in the global AI market.Industry observers also credit this achievement to the strategic direction of SK Group Chairman Chey Tae-won, who has long emphasized securing long-term technological competitiveness. Under his leadership, the company has consistently expanded its AI infrastructure partnerships with global Big Tech firms in the United States.Ahn Hyun, President and Chief Development Officer (CDO), attended the ceremony as the company representative to accept the award."It is an honor to receive this award on behalf of our employees, who have tirelessly challenged the limits of technology," said Ahn. "By collaborating closely with our global customers and partners, we will stay ahead in creating the value the market demands and continue to be a premier company leading AI innovation."