Pursuing a PhD might have been the most lucrative decision that Tomasz Matusiak has ever taken.Whilst studying at the Wroclaw University of Science and Technology in Poland's third-largest city, he developed chemical sensors made from ceramic materials based on microplasma generators, and electrical components made from a paste of glass and graphite. Now, Matusiak is using this research to solve a bottleneck that plagues the cutting edge of AI development: moving data between where it is stored in memory and where it is handled in the processing unit (for example, the central processing unit [CPU], which handles arithmetic and logical operations; or more specialised graphics processing units [GPUs], which handle computer graphics and digital images) wastes both time and (electrical) power. This limits the extent to which AI models can be scaled up and, of course, harms the environment.What if one could perform all of the computational tasks right where the data are stored? Matusiak thinks his material can do this, and he has started a company, SemiQa, and produced a system inspired by the human brain, the Analog Neural Network (ANN). Unlike conventional chips, which can reach 80°C and require a cooling system, his ANN system only reaches a maximum of 40°C. SemiQa's goal since its inception at the start of 2025 has been to conquer the universe of data centres, replacing their graphic cards (and the GPUs that power these graphic cards) with ANNs.Matusiak wants to bring back analog processing for its computational advantages. He uses the analogy of a train ride through the countryside. One might look outside the window and see a forest pass one by, followed by a short section alongside a river, before heading back into the forest again. A human brain – the analog system – would see a forest and then not think about it again until it sees a change in the environment (the river), and then once again not actively register the river again until the river has been replaced by the forest. It only processes the changes.But a digital system would constantly process what is outside the window. Analog processing thus saves on energy as it doesn’t process when there hasn't been any change.Likewise, digital processing might allocate a large number of bits to a small integer – for example, even though the number 5 can be expressed in binary with just three bits (101), it might be stored in an 8-bit or a 16-bit structure, where most of the surplus bits are zeroes. Many of the operations performed on these small integers will also result in small integers, so most of the leading zeroes will not change. A lot of memory is wasted.Analog processing can get around this problem by simply storing the 5 in a memory cell as a 5 instead of in eight memory cells as 00000101. (Analog memory cells, unlike digital memory cells, can take on more values than just 0 and 1.)The neural approach is based on a special electrical component called a memristor (short for memory resistor). A traditional resistor follows Ohm's Law, which states that the current (the rate at which electric charge flows) through a conductor is proportional to the difference in voltage (or the difference in electric potential energy, or the work it would take to move a unit of charge provided by, for instance, a battery) across that conductor. Mathematically, Ohm's law is V= IR, where V stands for the voltage, I for the current, and R for the resistance of the conductor, a proportionality constant that indicates how difficult it is for charge to move. The higher the resistance, the lower the current (for a given level of voltage).In a traditional resistor, the resistance doesn't vary with current (or voltage). In a memristor, though, the resistance depends not just on the current (or voltage) but also on the past levels of current running through it (or voltage controlling it). In other words, if the voltage goes up and then goes back down to its earlier level, the current and resistance might not return to their original levels. This ability to take on a range of values of resistance also mean that the memristor can be analog – in other words, that it can represent a range of values and not just a 0 or a 1.In addition to its superior thermal properties, SemiQa's ANN1000 is more power-efficient than other chips, being able to carry out more than 30 TOPS (or 30 trillion operations per second) per Watt of power; standard GPUs or NPUs (neural processing units, which are specialised for AI applications) can only carry out 1-2 TOPS per Watt. (The chip consumes 2.5 Watts of power, and so can carry out roughly 75 TOPS.)It is also naturally faster – ANN1000's latency (the time delay between when the processor requests something from memory to when the processor retrieves it) is 50 times shorter than that of a conventional GPU or NPU.The next step is, of course, commercial-scale production of their chips. They already demonstrated a proof-of-concept of their memristive technology at last year's SEMICON Taiwan, an annual trade show and Asia's largest semiconductor event. They will now create a neural network on silicon and hope to have a product-ready chip tailored to specific applications by the end of 2027. The memristive material, a mixture of organic and inorganic parts, is compatible with CMOS (complementary metal-oxide-semiconductor) technology, which is commonly used in foundries to fabricate chips. Matusiak envisions SemiQa's chips in mission-critical applications where efficient power consumption and processing is highly advantageous. These include autonomous systems, such as drones to be used in war and marine robots. Electric cars can also benefit: GPUs currently account for roughly half the cost of driverless vehicles, and replacing conventional GPUs with SemiQa's chips could reduce the price for consumers whilst maintaining manufacturers' margins. SemiQa also plans to add B2B applications such as data centres to the aforementioned B2C applications. They will tackle this through the ANN2000, a matrix of a thousand smaller ANN1000s.The prize money from the Best AI Awards pales in comparison to the 3 million EUR in pre-seed funding that SemiQa has already raised in Europe. But Matusiak is most grateful for the recognition that the judges have given his company's achievements since they started it just a little more than a year ago. This will also facilitate their collaboration with potential partners – in fact, they are already in talks with two local foundries to deepen their co-operation and scale up production of their chips."If you want something special, you need to work with the special forces," says Matusiak. "Everyone knows that Taiwan is the best in the world."SemiQa also plans to set up a branch office in Taiwan and will potentially hire two business developers in the country in the short term. They also know that they will need more funding, and are looking into perhaps raising money from Taiwanese investors. SemiQa already has a strong relationship with Taiwan, being a member of the Taiwan-Poland Chamber of Commerce and having signed memoranda of understanding with several Taiwanese businesses.The Best AI Awards celebrate global excellence in artificial intelligence and IC design, welcoming submissions from innovative companies and brilliant student teams. Following the success of the 2026 edition—advised by the MOEA, organized by DoIT, and executed by TCA—the prestigious competition is officially transitioning into an annual tradition.Offering substantial grand prizes and unmatched industry exposure, the countdown to Best AI Awards 2027 has already begun. Details on the next submission cycle, prize tiers, and eligibility rules will be released soon. Connect with us on LinkedIn for the latest official updates and application alerts. 

By now, it's common knowledge that artificial intelligence has sped up coding and is now replacing junior software engineers. But can you really trust the code that AI produces?The answer is a clear no. Programmers are still needed to review the code for bugs of all sorts. Maybe the code hallucinates, meaning that it has the right syntax and looks plausible but attempts to, for example, import a library that doesn't exist. Maybe there are functional bugs, where the code simply produces the wrong result because of a faulty algorithm and these are just the simple errors.Moreover, companies are naturally hesitant to release sensitive or proprietary information, such as customer data, to an AI coding tool.Inferara wants to solve these problems. It wants to give you code on which you can rely, free from any vulnerabilities, and it does this by reformulating the code into mathematical notation. This is all done on the user's own computing infrastructure, so that no code or data is ever shared externally.Georgii Plotnikov is the CEO and CTO of Inferara. Originally from Russia, Plotnikov had been working as a software developer for a decade after graduating from university. Roughly five years ago, he started learning more about static code analysis, which can be likened to a real-time spell-checker for code: it is, essentially, early detection for any bugs or security vulnerabilities in the code.He started developing an idea for a new way to turn static code analysis into a mathematics problem at the end of 2023. Around the same time, he started to explore where he could settle down and legally incorporate his company. Plotnikov decided on Japan, sent his business plan and other documents to the country,s government, and after being awarded a startup visa, moved there in the summer of 2024. (Inferara is a relatively young company, incorporated only in October 2024.)Unlike many AI companies, which focus on their product and want to get them out to market as quickly as possible, Inferara is proud to call itself a research-first company. Its main product is not the code checker but rather Inference, which he describes as "a programming language that uses mathematics to ensure code works exactly as intended".This is also known as formal verification, and being formally verified gives programmers and users an additional layer of assurance that, for instance, cryptographic protocols will keep data secure, or that compilers for programming languages will not make mistakes. It's also important for mission-critical processes, such as those in automated (driver-less) driving systems, financial systems, energy plant controls, and medical devices.In a nutshell, formal verification examines all possible states that the (usually finite number of) variables or parameters can take, in order to ensure that the logic is sound. In contrast, simply testing the system with common values that the variables might take might not reach all possible states, especially as the number of variables increases, and it will definitely not reach all possible states when there are an infinite number of variables (or values that the variables can take).Mathematical proofs can group variables together and reduce the total number of states that need to be explored. They can even use mathematical induction to verify an infinitely large number of states.Traditionally, programmers have needed a sophisticated understanding of mathematical logic to manually perform formal verification. Inferara's Inference programming language performs formal verification as one codes (or as AI codes) and makes it possible for even those with no understanding of mathematical logic to guarantee their code's fidelity. Inference's diagnostics are also developed so that both humans and AI coding agents can interpret them and, thus, use them to improve the code's reliability.Inference builds upon and improves the user experience of using Rocq, a piece of software that can assist in mathematical proofs. Plotnikov says that Inference sets itself apart by working what appears to be slowly. Instead of writing code as quickly as possible, it continually checks the code's correctness as it is being generated. This takes more time but, in the end, is more cost-effective, since it requires fewer calls to AI later on. Plotnikov likens this to the slower, more rational and conscious system of thinking described in Daniel Kahneman's bestselling book Thinking, Fast and Slow.Inferara has now taken the next step beyond Inference: It has created Vibe Checker, an operating system that can encapsulate the entire AI-led code-development process. In addition to its own desktop AI agent, Vibe Checker is compatible with the existing, widely-used coding agents of Claude Code, Gemini, and Codex.Most companies currently using AI-assisted coding typically do so via the cloud (i.e., off-premises). Although the code and data is stored under the programmer's domain, all that information traverses multiple external barriers when being run. Vibe Checker provides its own gateway, comprising its own server and the user’s own cloud computing security model (also known as bring-your-own-encryption, bring-your-own-key, or BYOK). Vibe Checker's most data-secure services will host everything on users' own infrastructure, and is appropriate for those users who have the resources to buy their own hardware. There is total data sovereignty: no data ever leaves the user's infrastructure, nothing is ever uploaded to Inferara's servers, and everything can be run even without internet access. An audit trail also logs every action taken by a coding agent.Vibe Checker does more than just check code. It's a multifunctional checker, or task-agnostic, and can audit any AI-generated system for functional errors and security vulnerabilities. Law firms can use it to summarise case files and contracts; researchers and policy analysts can use it to verify their database queries; finance departments can check their tax filings; hospital clinicians can manage their patient records; and banks and insurers can double-check their regulatory submissions.Privacy is essential in all of these aforementioned applications, and Vibe Checker enables on-premise analysis with links and citations referring back to the original source of the information – in other words, no hallucinations.Plotnikov says that Inferara will clearly benefit from the 500,000 NTD prize money from the Best AI Awards. However, the most important reward is the valuable feedback from those working in the industry, telling them that what they are doing makes sense and has commercial value. The award will also help Inferara get its name out and allow them to approach and demonstrate their technology to potential partners; in fact, Inferara is currently in discussions with several companies in Taiwan. In particular, they are interested in working with Taiwan's semiconductor and chip industry, which can provide the hardware supply chain for their product.In the next few months, they plan to deploy Vibe Checker to several companies who will serve as beta-testers, including several Taiwanese companies. They also intend to establish a legal entity in Taiwan, and have plans to work with the Centre of Industry Accelerator and Patent Strategy (IAPS) at the National Yang Ming Chiao Tung University.The Best AI Awards celebrate global excellence in artificial intelligence and IC design, welcoming submissions from innovative companies and brilliant student teams. Following the success of the 2026 edition—advised by the MOEA, organized by DoIT, and executed by TCA—the prestigious competition is officially transitioning into an annual tradition.Offering substantial grand prizes and unmatched industry exposure, the countdown to Best AI Awards 2027 has already begun. Details on the next submission cycle, prize tiers, and eligibility rules will be released soon. Connect with us on LinkedIn for the latest official updates and application alerts.

As artificial intelligence (AI), high-performance computing (HPC), high-speed networking, and edge computing applications continue to expand rapidly, global demand for custom ASIC solutions is rising at an unprecedented pace. Faced with the escalating design complexity and development costs associated with advanced process nodes at 6/5/4/3nm, balancing time-to-market, cost efficiency, and production quality has become a critical challenge for IC design companies and system vendors worldwide.PGC (TPEx: 8227), with over 35 years of expertise in ASIC design services, is a member of the TSMC Design Center Alliance (DCA) and a Synopsys IP OEM Partner. With a track record of more than 1,500 tape-out projects and over 100 tape-outs completed annually, PGC delivers comprehensive capabilities spanning advanced-node design, APR (Automatic Place and Route), back-end design services and tape-out foundry services, and volume production ramp. In response to growing market demand for advanced-node ASIC development, PGC announces the further enhancement of its Customer-Owned Tooling (COT) business model, integrating ASIC design services, IP resources, and semiconductor supply chain ecosystems to help customers shorten chip development cycles, accelerate tape-out, and rapidly secure engineering samples and production capacity.COT Business Model: Balancing Design Ownership with Development EfficiencyThe COT business model enables customers to retain ownership of critical design assets — including IP, EDA tool licenses, and design data — preserving their core intellectual property and technical autonomy while leveraging PGC's professional ASIC design team and proven design flows to jointly complete chip development. Compared to traditional turnkey models, COT effectively reduces long-term NRE (Non-Recurring Engineering) investment, eliminates vendor lock-in, and enhances flexibility for product iteration, multi-project development, and cross-generation platform continuity.In practice, customers adopting the COT model have achieved development cycle reductions of over one month, along with long-term NRE cost savings of more than 10%, giving them greater autonomy and strategic flexibility in product planning and technology roadmap execution.Synopsys IP OEM Partnership: Lowering IP Licensing Barriers and Accelerating DevelopmentAs a Synopsys IP OEM Partner, PGC provides customers with comprehensive Synopsys IP licensing and integration services. Customers can flexibly incorporate market-proven, high-quality IP based on project requirements, simplifying licensing processes, lowering upfront investment thresholds, and accelerating IP integration and verification through PGC's expertise — further shortening ASIC development cycles and time-to-market.ASE Packaging and Test Integration: Bridging Design to Volume ProductionIn the area of packaging and test, PGC has established a close collaboration with ASE Group, integrating advanced packaging and test resources to provide customers with comprehensive production support from wafer to finished product. This collaboration covers BGA, Flip Chip, and Wire Bond packaging and full test services, helping customers accelerate production ramp while ensuring shipping quality and reliability.One-Stop Solution: End-to-End Support from Design to Mass ProductionBeyond ASIC design services, PGC offers a diverse range of prototyping options, including TSMC CyberShuttle (suited for early-stage design verification, leveraging multi-project wafer sharing to reduce prototyping costs) and VIS (Vanguard International Semiconductor) MPW (suited for specialty process or mature node requirements), enabling customers to complete engineering sample verification with maximum flexibility.PGC delivers a comprehensive one-stop solution encompassing ASIC design, IP integration, APR, DFT, tape-out, prototype verification, packaging and test (OSAT), and volume production ramp，complemented by professional back-end design services  and complete tape-out foundry services, helping customers rapidly obtain engineering samples, complete product validation, and seamlessly transition to mass production, significantly compressing time-to-market.PGC CEO Fred Lai stated: "In a market environment where AI and HPC applications continue to drive demand for advanced-node solutions, customers need more than a design service provider — they need a comprehensive partner capable of integrating IP, design, prototyping, and volume production. By enhancing our COT business model and deepening our three-way ecosystem collaboration with TSMC, Synopsys, and ASE, our goal is to help customers reduce their ASIC development cycles by more than 10%, bringing innovative products to market faster."Looking ahead, as demand for AI inference chips, HPC accelerators, and high-speed networking ASICs continues to grow, PGC will continue to expand its advanced-node service capabilities and further extend its customer reach into the US market, empowering global customers to seize opportunities in the advanced-node semiconductor landscape.PGC Boosts COT Model, Integrates TSMC Ecosystem for ASIC Growth. Credit: PGC

The data center industry is undergoing its largest structural transformation in the past decade due to the rapid development of generative AI. As AI models drive growing demand for GPUs, high-speed connectivity, and high-density computing, data center requirements are evolving beyond traditional colocation services to encompass comprehensive upgrades in power supply, cooling, networking, and overall infrastructure architecture. At the recent DIGITIMES 2026 Enterprise Data Center Forum, Chunghwa Telecom Senior Engineer Hsueh Jen-Hao presented "Meeting the AI Challenge: The Evolution of Data Center Requirements and Infrastructure Upgrade Strategies," outlining Chunghwa Telecom's key strategies for responding to the AIDC (AI Data Center) trend and helping enterprises plan their AI computing capacity. Hsueh Jen-Hao noted that power demand per rack has surged from the traditional 2 kW to 5 kW range to 100 kW and even 200 kW. This underscores that the AI era is driving not merely an upgrade of data center equipment, but a paradigm shift across data center design, cooling architecture, energy management, and cross-border network connectivity. AI Servers Drive Higher AIDC Service StandardsHsueh Jen-Hao described AIDC as a "five-star hotel," illustrating the fundamental transformation in the nature of data center services. As AI servers are high-value, power-intensive, and highly sensitive to environmental conditions, data centers must not only operate around the clock without interruption, but also maintain stable temperature and humidity levels, power supply, and network quality, while adjusting environmental conditions in accordance with customers' SLA requirements.To meet the operating environment required by AI servers, Chunghwa Telecom is also upgrading the infrastructure of its data centers. Hsueh Jen-Hao noted that with a single rack often weighing more than 1,250 kilograms, data center floor loading requirements have increased significantly from 500 kg/m2 to 2,000-2,500 kg/m2. Structural specifications are now approaching those of heavy industrial facilities, redefining the conventional concept of an IT data center. Furthermore, the rapid rise in rack power consumption has pushed cooling requirements beyond the limits of traditional air-cooling systems. From Air to Liquid Cooling: Chunghwa Telecom Delivers Customized SolutionsAI computing has driven a dramatic increase in rack power density, from 30 kW-132 kW for NVIDIA H100 clusters to 140 kW per rack for the liquid-cooled GB200 NVL72 architecture. In response to this trend, traditional downflow air-conditioning systems and fan-wall cooling systems, which can support only up to approximately 20 kW, are gradually becoming unable to meet the cooling requirements of next-generation servers.To address the surge in cooling demand driven by AI computing, Chunghwa Telecom is actively introducing liquid-cooling technologies and tailoring solutions to individual customer requirements. From facility planning and design to project management, Chunghwa Telecom offers one-stop services to deliver the essential infrastructure needed for high-density AI computing, including cooling systems, power distribution, and power backup mechanisms. Through flexible modular designs, the data centers can be expanded alongside customers' business growth, satisfying the requirements for large-scale computing and data processing. Hsueh Jen-Hao noted that driven by both the thermal demands of AI servers and international regulations incorporating data center energy performance, liquid cooling solutions are gradually becoming a standard configuration for AIDCs. AIDC Ecosystem Expansion: Green Energy, All-Photonics Networks, and Submarine CablesIn response to the AI wave and the growing adoption of innovative applications, Chunghwa Telecom is not only enhancing cooling technologies within its data centers, but is also pursuing a comprehensive strategy spanning energy, networking, and submarine cable infrastructure. First, Chunghwa Telecom launched its Green Energy AIDC initiative in 2020. As of 2025, approximately 40% of the electricity consumed by its data centers came from renewable energy sources. The company aims to achieve its sustainability goal of powering data centers with 100% renewable electricity by 2030. Second, as cross-regional collaboration and data exchange continue to expand rapidly, high-bandwidth, low-latency connectivity has evolved from a competitive advantage into a fundamental requirement for data centers. To support the development and advancement of internet technologies, Chunghwa Telecom is promoting reference architectures, frameworks, and specifications for next-generation ICT infrastructure centered on all-photonics networks (APN), meeting the increasingly stringent requirements of innovative applications and AI computing for power efficiency, bandwidth, and latency. In addition, Chunghwa Telecom is Taiwan's first and currently only telecommunications operator to serve as a board member of the IOWN Global Forum.Hsueh Jen-Hao noted that the attractiveness of a data center location is directly proportional to the availability of local submarine cable resources. The continued growth of data centers in Hong Kong and Singapore, for example, is largely attributable to their roles as major international submarine cable hubs in Asia. To this end, Chunghwa Telecom has continued to invest in Taiwan's submarine cable infrastructure. On the international front, in addition to the completed SJC2 submarine cable system, the APRICOT system is also scheduled for completion in 2027. To enhance domestic network resilience, the Taiwan-Penghu-Kinmen-Matsu No. 4 submarine cable is expected to be completed in 2026. As these submarine cable projects come online, they will not only significantly strengthen Taiwan's international connectivity, but also provide a solid infrastructure foundation for cross-border AI computing and the deployment of international data centers.From floor loading capacity and liquid-cooling technologies to renewable energy initiatives, all-photonics networks, and submarine cables, Chunghwa Telecom's data center investments in recent years may appear to span different domains. However, they are all guided by the same strategic objective: systematically strengthening data center infrastructure to support enterprise AI adoption, ensure uninterrupted operations, and enhance Taiwan's competitiveness in the AI era. 

Smiths Interconnect, a Molex company, announces its top performing distributors in 2025. The Distribution Awards program honors distributors which have made a meaningful impact on the growth of Smiths Interconnect across its three key regions: the Americas, EMEA, and Asia.Award recipients in each region are selected based on their outstanding performance compared to the previous fiscal year and on outstanding local service and support. This year, the strong commitment and dedication shown by distributors worldwide have resulted in a larger group of recognized companies. Seven distributors in total have been distinguished for their exceptional achievements.In the Americas, FDH Electronic Products Group, LLC. has been named Distributor of the Year for the second consecutive year. This recognition reflects FDH's outstanding performance, strong partnership, and unwavering commitment to delivering exceptional service and support to its customers.Over the past year, FDH achieved impressive sales growth, demonstrating not only market strength but also a deep dedication to driving their mutual success. Their ability to navigate challenges, adapt quickly, and maintain focus on execution has been instrumental in delivering consistent results and strengthening the partnership.The second distributor recognized in the Americas as Highly Commended Distributor for Business Growth 2025 is Arrow Electronics.Through a focused and strategic customer approach, Arrow has delivered impressive business growth, reinforcing their position in driving market expansion and customer engagement.Arrow's commitment to collaboration, responsiveness, and execution has played an important role in achieving these results. Their team has consistently demonstrated the ability to identify opportunities, adapt to evolving customer needs, and deliver value across joint initiatives.In the EMEA region, Smiths Interconnect has recognized two distinct distributors for their outstanding growth throughout the year.RFMW Ltd is recognised for delivering the strongest growth in 2025 across the company's RF component product lines, reflecting exceptional commercial execution and deep customer engagement. Their results in key South European territories were achieved through a close, collaborative partnership that enabled both organisations to navigate a highly competitive landscape effectively.RFMW consistently converted design activity into revenue while expanding presence in target markets, demonstrating a shared commitment to technical excellence, partnership, and sustained value creation.For the Connectors product line, the top performing distributor was Heilind Electronics GmbH, which supported sales growth with a strong focus on the DAC countries.This success was also driven by well-managed inventory levels, enabling fast deliveries and reliable local support for customers.Last but not least, Asia was one of the most active areas from a distribution standpoint. Three key distributors were appointed: Fusoh Shoji Co., Ltd, Bizmile Co. Ltd, and Conn-Tek Electronics Inc.First, Fusoh Shoji Co., Ltd was named Distributor of the Year 2025 for the Fiber Optic and Components product lines. The company has demonstrated outstanding performance in expanding these product lines in Japan, playing a key role in strengthening its market presence and supporting a solid foundation for future growth.Meanwhile, in the Connectors product line, Korea's Bizmile Co. Ltd secured the Distributor of the Year 2025 title. Awarded for its outstanding contribution to business growth, design-in excellence, and value delivery, Bizmile demonstrated exceptional support to key accounts by driving significant growth through strong inventory commitment and strategic project support. The company also excelled in design-in activities, successfully contributing to major defense programs while consistently delivering measurable value to customers. Its strength in commercial execution, strategic account development, and an ecosystem-driven approach has enabled sustained growth, improved profitability, and strong future demand visibility.Rounding out the region's success, Conn-Tek Electronics Inc was named Distributor of the Year 2025 for the Semiconductor Test product line for the second consecutive year. This award recognizes Conn-Tek's exceptional performance across business growth, design-in excellence, and strategic market development. The company achieved remarkable revenue growth in both China and international markets while demonstrating strong leadership in design-in activities with key customers. Furthermore, Conn-Tek experienced significant expansion in high-value product segments—particularly with the DaVinci coaxial test socket—and successfully penetrated new customer markets. Its design-led, partnership-driven approach has delivered sustained growth, improved profitability, and enhanced strategic value across the Asia region.

Artificial intelligence (AI) is moving beyond a tool that simply answers questions and into the era of "agentic AI"—systems that make their own judgments and carry out tasks. A major event offering a comprehensive view of the latest currents in the global AI industry is once again coming to Seoul.DMK Global, COEX, and the Korea International Trade Association (KITA) announced that they will host "AI Summit Seoul & EXPO 2026" (AISE 2026) over three days, from August 19 (Wed) to 21 (Fri), at COEX in Seoul. The conference will take place in the Grand Ballroom, while a large-scale exhibition (EXPO) runs concurrently in Hall B. Since its inaugural edition in 2018, the industrial-AI-focused event—now in its ninth year—has established itself as an annual global AI event held in Seoul.The central theme this year is putting AI to real work, beyond mere adoption. As AI technology advances rapidly, companies now face a new challenge that goes beyond "whether to adopt AI" to "what authority to grant AI, and how to trust the results it produces." Generative AI has proven its value in producing answers and content; more recently, attention has turned to agent-based AI that independently makes decisions and takes action within enterprise workflows.Reflecting this shift, AISE 2026 has set its theme as "The Transformation Era: Beyond Adoption – Rise of Enterprise Agents." Rather than simply introducing technology, the event focuses on how AI agents are being applied in real business settings and how they are reshaping organizations and business models.The two-day conference, held in the COEX Grand Ballroom beginning August 19, is organized around six core themes: "AI Mega Trends," surveying fast-moving technology and market shifts; "AI Transformation," addressing changes to organizations and business models; "AI & Data," covering foundational challenges such as data labeling and MLOps; "Vertical Industry Use Cases," presenting real-world applications by sector; "AI + Robotics," exploring the convergence of AI and robotics; and the year's most talked-about theme, "Agent & Agentic AI."The global speaker lineup also stands out. Speakers include Steve Chien, a researcher at NASA's Jet Propulsion Laboratory (JPL) who studies autonomous AI capable of independent decision-making in space; Larry Heck, a Georgia Tech professor and leading authority on conversational AI; Maxim Afanasyev of Google Cloud; Hoifung Poon, a researcher at Microsoft Research focused on AI-driven scientific discovery; and Maxime Labonne, a researcher at Liquid AI and an expert in frontier small models.In addition, representatives from leading global technology and industry companies—including Genspark, Google DeepMind, Hyundai, DHL, Notion, IDEO, Mercedes-Benz, Seagate, Adobe, and ClickHouse—will take part to share proven use cases and technical insights across industries.Running alongside the conference, the exhibition (EXPO) takes place in COEX Hall B over three days, from August 19 to 21. Roughly double the size of last year's edition, it will feature more than 100 exhibiting companies and over 30 speech and workshop sessions. A key highlight is the opportunity to survey the entire AI value chain under one roof—from LLMs and generative AI to AI hardware and infrastructure (GPUs, NPUs, and more), robotics and autonomous technologies, and industry-specific solutions. Visitors can experience live demonstrations of products and solutions already in operation at exhibitor booths, across categories including Industry AI, Enterprise AI, generative AI, AI platforms and infrastructure, and physical AI and robotics.Exhibiting companies will run demos and consultations for decision-makers from Korea and abroad, and the program includes 1:1 business matching and networking parties connecting executives, developers, investors, and researchers. EXPO visitor registration is free until July 31 (Super Early Bird); from August 1 it moves to Early Bird pricing of KRW 10,000, and to a standard rate of KRW 20,000 thereafter.Supporting programs have also been strengthened. During the event, offerings include hands-on workshops for in-depth, practical learning with leading AI technologies and solutions from Korea and abroad; investment matching connecting startups with investors; and an AI experience zone. Beyond simple viewing, the event is designed to serve as a venue for experiencing technology firsthand and connecting AI companies with industry, investors, and talent.As AI spreads beyond individual services and solutions into every facet of enterprise operations, the event is expected to offer a chance to survey the latest trends at a glance and to gauge the potential for real-world adoption and commercialization.

EDOM Technology(TWSE: 3048), Asia's best solutions provider, celebrates its 30th anniversary this year. Since its establishment in 1996, EDOM has worked with global partners to lead innovative technologies and witnessed the growth trajectory of the electronics industry along the way. Faced with the booming trend of diversified AI applications, EDOM will focus on four major innovation areas including power technologies, cybersecurity, optical communications, and biomedicine. Through complete technical support and supply chain services, EDOM will help customers accelerate the implementation of AI, smart networking, and edge computing applications, and jointly promote the development of smart manufacturing, smart medical care, and next-generation digital infrastructure.1996 is a critical year in the history of science and technology. This year, the Internet began to fully enter public life, and the core technology, software, and hardware that laid the foundation for modern digital life were born at this time. The company encountered the Asian financial crisis in 1997 when it was first established, but the rise of the Internet from 1996 to 2000 also brought excellent development opportunities. In its early days, EDOM was optimistic about the emerging 3D graphics chips, modem chips, and radio frequency components. Using this as a starting point, EDOM gradually established a foothold in the electronic circuit market and wrote important milestones along with the changes in the industry.Since its listing in 2002, EDOM has continued to deeply explore the Asia-Pacific market. Following the trend of the Asia-Pacific region becoming an important manufacturing base for the global information industry, EDOM has actively expanded its service base and strengthened its supply chain support capabilities. With the rapid development of the technology industry, EDOM has experienced steady growth: in 2010, driven by the popularity of smartphones and tablets, annual revenue exceeded US$1 billion for the first time; in 2014, it seized the opportunity of the rise of mobile communications, with the Internet of Things and mobile payment, annual revenue exceeded US$2 billion; in 2019, benefiting from the growth in market demand for wearable devices and network communications, annual revenue exceeded the milestone of US$3 billion. Facing a new wave of industrial changes driven by AI, EDOM achieved annual revenue of US$3.7 billion in 2025, ranking among the top ten electronic component distributors in the world, and continues to move towards the revenue target of US$4 billion.Over the past thirty years, EDOM has witnessed the birth of epoch-making applications such as PCs, mobile phones, tablets, electric vehicles, data centers, robots, smart manufacturing and industrial control, and autonomous vehicles. Every new application can be transformed from concept to practice, relying on the efforts of innovators and the support and collaboration of a complete supply chain system. Today, artificial intelligence technology has once again brought new development opportunities. AI has moved from the layout of cloud giants to the enterprise and industrial manufacturing fields, and has penetrated into daily life. Under this trend, EDOM is optimistic about four major areas:Power and cooling technologies: With the rapid growth of AI computing requirements, high-efficiency power management and cooling technology will become an important foundation to support the operation of future electronic products and data centers.Cybersecurity: In the era of digitalization and the Internet of Everything, the importance of information security protection continues to increase, and cybersecurity will become an indispensable part of the stable operation of enterprises.Optical communication: Optical communication and co-packaged optics (CPO) technology are regarded as important keys to breaking through the bottleneck of AI computing transmission. They will not only improve the operational efficiency of data centers, but also accelerate the development of edge computing and high-speed transmission applications.Integration of semiconductor technology and biomedicine: By combining technology and biomedicine, the automation of testing in medical institutions and laboratories can be further promoted, the process of precision medicine can be accelerated, and key breakthroughs can be brought to life sciences.Wayne Tseng, Chairman of EDOM Technology, said: "In the torrent of technological change, our vision of making the world a better place through innovation has remained steadfast. We are deeply honored to witness and participate in the development and evolution of the electronics industry. We sincerely thank the vendors, customers, and partners who have worked side by side with us over the past thirty years, and we look forward to continuing to work together in leading the next generation of technological innovation in the future."With thirty years of evolution, EDOM resonates with the pulse of the global electronics industry. Facing the ever-changing technological wave, we always keep abreast of the latest trends, enrich the electronics industry ecosystem, and open chapters of innovation with global partners.

As the AI computing race accelerates and semiconductor manufacturing capacity is increasingly redirected toward advanced memory, the memory industry is shifting from price-driven competition to a battle over resource allocation and supply security. The rapid expansion of high-bandwidth memory (HBM) production continues to consume advanced fabrication capacity, constraining the supply of conventional memory products and creating persistent shortages across the market. This concentration of high-end production has widened the supply-demand gap, driving the average selling prices of certain premium memory products to levels eight to ten times higher than previous norms.Against this backdrop, TEAMGROUP General Manager Gerry Chen warned that the industry could face a period of unprecedented scarcity by 2027. He described the situation as one where "even customers willing to accept higher prices may still face supply risks," potentially echoing the severe chip shortages seen during 2021–2022. Chen noted that even buyers willing to pay premium prices could face significant procurement challenges if they lack long-term strategic relationships with original chip manufacturers, leaving them highly vulnerable to supply disruptions.In response, TEAMGROUP initiated a strategic transformation in 2025, redirecting 80% of its resources from the consumer segment toward long-lifecycle, high-reliability applications. The company is now focused on mission-critical sectors, including industrial automation, enterprise infrastructure, defense, and healthcare, while also expanding into military-grade storage and high-density computing applications. Leveraging three decades of partnerships with leading global suppliers and its extensive experience in IPC design-in collaboration, TEAMGROUP has strengthened supply-chain resilience and enhanced supply assurance amid ongoing market volatility, positioning itself as a trusted enabler of secure and reliable AI infrastructure.Building supply chain resilience amid persistent memory shortageChen emphasized that the exponential growth of AI-driven demand is outpacing semiconductor capacity expansion, a process that typically requires three to three-and-a-half years to complete. As a result, supply constraints in DRAM and SSD markets are becoming a structural challenge rather than a cyclical phenomenon. In this environment, competitive advantage will increasingly depend on supply assurance, allocation capabilities, and long-term supplier relationships rather than price alone.Leveraging decades-long partnerships with leading memory manufacturers and extensive IPC expertise, TEAMGROUP has established a stable supply framework for industrial PCs and other long-lifecycle applications requiring seven to ten years of product availability. The company works closely with customers to identify alternative component sources, optimize system configurations, and mitigate demand distortion and bullwhip effects across the supply chain. These capabilities have strengthened resilience for customers in mission-critical industries such as automotive, healthcare, and defense.T-CREATE EXPERT P35S & TEAMGROUP INDUSTRIAL P250Q secure data in defense & finance. Credit:TEAMGROUPTEAMGROUP's portfolio spans commercial-grade storage solutions for general confidential data protection, as well as industrial-grade products engineered for deployment in aircraft, naval vessels, unmanned systems, and other high-reliability platforms. The company has showcased these solutions at major industry events, including Embedded World and Japan IT Week.Physical destruction technology enables one-click data destructionThe T-CREATE EXPERT P35S, recipient of the 2026 COMPUTEX Best Choice Award, exemplifies TEAMGROUP's philosophy that "physical destruction is the ultimate safeguard." According to Chen, true data security lies in the complete physical destruction of storage media rather than relying solely on software-based deletion methods.When activated, the SSD's built-in boost chip instantly releases a high-voltage current that physically breaks down the insulation layer of the NAND flash ICs, permanently destroying the storage medium within 2.4 seconds and making data recovery extremely difficult. For everyday protection, AES-256 encryption provides a first line of defense, creating a comprehensive security framework that integrates both hardware- and software-based safeguards.The design is engineered to eliminate any possibility of residual data. Its proprietary circuit architecture uses a zoned sequential-conduction mechanism, enabling high-voltage current to destroy memory chips in a controlled chain reaction. TEAMGROUP's patented "power-resume destruction" technology further ensures destruction integrity by automatically completing the process when power is restored if an interruption occurs during the destruction sequence.To prevent accidental activation, the device incorporates a two-stage fail-safe button requiring deliberate user action. The technology also supports remote activation through 4G/5G networks, radio communications, or SMS commands, allowing data destruction to be triggered from several kilometers away. This capability helps prevent sensitive information from being compromised even if a device is lost, stolen, or captured.The patented technology is currently available in two products: the T-CREATE EXPERT P35S, a portable secure storage device, and the industrial-grade TEAMGROUP INDUSTRIAL P250Q-M80 M.2 high-speed SSD, designed for classified computing environments, financial institutions, and defense applications. Together, they provide a robust cybersecurity safeguard for the defense, finance, and R&D sectors.TEAMGROUP showcases a variety of enterprise-grade SSDs at COMPUTEX. Credit: TEAMGROUPAdvanced specs pave the way for agentic AILooking ahead to the convergence of AI and physical robotics, Chen noted that technology ultimately serves human needs. As AI systems continue to collect and process vast amounts of behavioral, operational, and contextual data, demand for on-premises storage is expected to grow significantly.TEAMGROUP keeps data stable in harsh settings & inspires young teams to innovate. Credit: TEAMGROUPOne example is the emerging long-term care robotics market. These systems must not only deliver healthcare-related capabilities but also retain medical records and behavioral data over extended periods. Such requirements place stringent demands on SSD endurance, reliability, and long-term stability, underscoring the importance of local data storage. Similarly, enterprises are increasingly reluctant to move highly sensitive information—including financial data, proprietary business models, and operational intelligence—to the cloud. As a result, agentic AI systems capable of autonomous decision-making within on-premises environments are gaining strategic importance.To support next-generation AI applications, TEAMGROUP has become one of the industry's early innovators in LPCAMM2 and SOCAMM2 memory technologies. LPCAMM2 enables LPDDR memory, traditionally soldered directly onto notebook motherboards, to become modular and upgradeable, while SOCAMM2 introduces a compact, low-power architecture designed for AI servers and advanced computing platforms, offering an alternative to conventional RDIMM. Together, these technologies offer greater flexibility, serviceability, and power efficiency for future AI systems.Beyond supplying low-power memory components, TEAMGROUP has evolved into a comprehensive solution provider, helping customers maintain data integrity and system stability in demanding operating environments characterized by vibration, thermal challenges, and continuous workloads. At the same time, the company encourages its young talent to pursue bold innovation while investing in next-generation DDR6 R&D, laying the groundwork for future AI infrastructure and intelligent edge computing applications.Amid the ongoing memory supercycle, TEAMGROUP has demonstrated strategic resilience and innovation beyond the role of a traditional module manufacturer. By combining supply-chain expertise, advanced physical-level security technologies, and next-generation memory architectures, the company aims to help customers safeguard critical digital assets while preparing for the next phase of AI-driven transformation.For more information, please visit.

On the opening day of COMPUTEX 2026, AIC Inc. hosted a high-level strategic panel session at its booth, focusing on overcoming the "memory wall" challenge. Industry giants and key strategic partners, including NVIDIA and VAST Data, joined AIC for a presentation on their latest platforms designed to eliminate bottlenecks in Large Language Model (LLM) inference and intensive AI workloads, marking a critical evolution in active AI storage driven by Agentic AI in 2026.In his opening remarks, Michael Liang, CEO and President of AIC, outlined the new challenges facing AI infrastructure as AI applications enter the "Long Context" era. The transition to long-context and Agentic AI has completely shifted the primary AI infrastructure bottleneck from raw computational speed to massive data movement and memory bandwidth constraints—a hurdle commonly known as the "Memory Wall."Liang emphasized that the shift toward autonomous AI agents executing task decomposition and multi-step APIs is fundamentally transforming data center demands and reshaping underlying AI infrastructure. Consequently, AIC is actively collaborating with NVIDIA and VAST Data to develop advanced, AI-native storage solutions. By integrating the NVIDIA Vera BlueField-4 STX Storage Processor into its hardware platforms, AIC is building the essential infrastructure required to eliminate bottlenecks and accelerate workloads for Agentic AI applications.NVIDIA Ecosystem Scales Agentic AI Adoption WorldwideJason Hardy, NVIDIA's Vice President of Storage Technology, highlighted the significance of "Agentic Inferencing", a key theme from the NVIDIA GTC Taipei keynote during COMPUTEX 2026. Agentic AI requires more than faster compute; it demands fast, secure access to context memory so agents can reason across long sessions, large datasets, and complex workflows.NVIDIA Vera BlueField-4 STX addresses this paradigm shift. It enables a new class of AI-native storage infrastructure for context memory, built with Vera-based BlueField-4, NVIDIA Spectrum-X Ethernet, NVIDIA DOCA, NVIDIA Dynamo, and NVIDIA AI Enterprise. This foundation provides NVIDIA's storage partners, such as AIC, with the essential building blocks to keep agent context and inference data close to the compute path, significantly improving throughput, responsiveness, and infrastructure efficiency.NVIDIA is actively building a robust partner ecosystem around the NVIDIA Vera BlueField-4 STX architecture, spanning storage, systems, cloud infrastructure, and security sectors. Key partners like AIC are collaborating closely with NVIDIA to integrate, validate, and bring this next-generation infrastructure to market. Hardy emphasized that these close alliances will help customers optimize resource utilization, reduce costs, accelerate response times, and enhance security during large-scale deployments, thereby ushering in the era of Agentic Inferencing.VAST Data and AIC Hard-Soft Integration Optimizes AI InfrastructureEchoing the new design of NVIDIA Vera BlueField-4 STX, VAST Data CTO Andy Pernsteiner emphasized that Agentic AI requires sophisticated mechanisms for managing and optimizing massive-scale KV caching to persistent memory. This avoids redundant, expensive prefill computations across multi-turn, long-context sessions, while providing new storage platforms that support confidential computing and data protection for highly sensitive information. VAST Data integrates seamlessly with NVIDIA's BlueField-4 DPU architectures and Dynamo routing frameworks to offload, share, and reuse KV cache context across wide GPU clusters.The strategic hardware-software partnership between VAST Data and AIC pairs AIC's advanced server hardware with VAST's software intelligence to build next-generation AI infrastructure and context memory storage platforms. Integrating NVIDIA Context Memory Storage (CMX) platform, featuring the NVIDIA Vera BlueField-4 STX storage processor, effectively resolves GPU KV cache bottlenecks. By utilizing fast NVMe arrays as a shared, high-bandwidth context tier, the solution significantly increases tokens-per-second throughput and energy efficiency for long-context, multi-turn AI inferencing.AIC Embraces NVIDIA Vera BlueField-4 STX for Agentic AIAs Liang stated in a post-event interview with DIGITIMES, the company has successfully built its storage server business since 2014. By continuously reinvesting 15% of its annual revenue every year into R&D and early-stage development of new architectures, AIC has positioned itself as a key player in developing next-generation, Agentic AI-native storage infrastructure.Today, AIC is established as a Solution Advisor in the NVIDIA Partner Network (NPN). AIC also is building upon a strategic partnership with VAST Data that began seven and a half years ago. To meet the surging demand for AI data centers, AIC's strategic expansion in Yangmei, Taiwan, and Haiphong, Vietnam, directly targets the skyrocketing global demand for artificial intelligence data centers. These state-of-the-art manufacturing footprints allow the company to scale production of AI servers and high-density storage while seamlessly integrating computing, networking, and security into unified infrastructure platforms.The new facilities anchor AIC's global supply chain and position the company to meet the intense deployment needs of cloud service providers and enterprise customers. This empowers customers to maintain a competitive lead and achieve greater success amidst the AI wave.

The megatrend in electronic design today is end-to-end collaboration across ICs, packaging, PCBs, systems, data centers, and physical applications, with rapidly evolving artificial intelligence playing an increasingly critical role.In early June, Graser Technology held its annual technology forum, Graser TECHTALKS 2026, under the theme "AI in Sync: Intelligent Design, Accelerated Manufacturing." The event focused on how AI connects design, analysis, and manufacturing workflows. It brought together industry speakers, in-house engineering experts, and customer representatives to share professional insights and real-world experience, outlining a new paradigm for electronic design workflows and industrial applications in the AI era.In her opening remarks, Graser Chairwoman Lillian Pan said the company has, for more than 30 years, upheld the principles of fast response, professional service, and long-term partnership, helping customers turn ideas into products faster. She added that Graser will continue promoting the leverage of AI across engineering workflows, introducing advanced design tools, and supporting Taiwan's semiconductor and electronics industries in remaining globally competitive.AI as a Design Workflow CollaboratorIn the first keynote, "Paradigm Shift of System Design in the AI Era," Michael Shih, Corporate Vice President for APAC and Japan at Cadence, said electronic design is facing a new level of complexity as Moore's Law becomes harder to sustain and the cost of advanced process technologies and system integration continues to rise.He noted that the challenge is no longer limited to designing a single chip. Instead, engineering teams must increasingly solve complex issues across chips, advanced packaging, PCBs, system-level design, and multiple physical domains. Against this backdrop, Cadence has been expanding its focus from IC design into packaging, PCB design, multiphysics simulation, data centers, and system analysis, evolving from a traditional EDA tool provider into an Intelligent System Design platform company.Shih explained that Cadence's Intelligent System Design platform brings together AI, EDA and IP, system design and analysis, and computational software. This enables engineering teams to perform simulation, analysis, optimization, and design verification at the system level. Within this framework, Cadence is pursuing AI in two directions: Design for AI, which helps customers build AI infrastructure, and AI for Design, which embeds AI directly into design solutions. In other words, AI is not only an application enabled by advanced ICs and systems; it is also becoming a core collaborative capability within the electronic design process.A major part of this shift is the introduction of agentic AI into design workflows. Shih said Cadence is bringing AI agents into front-end design and verification, digital implementation, and custom and analog design processes.These AI agents can help engineers understand design goals, break down tasks, execute workflows, and accelerate iterative design cycles. Their value goes beyond labor savings: by automating repetitive and time-consuming work, AI agents allow design teams to explore feasible options faster, shorten development cycles, and reduce the time and cost pressures created by rising complexity of designs.Shih noted that, for example, many companies must complete large numbers of board designs every year, involving repetitive yet expertise-intensive tasks such as placement, routing, layout, and design checks. By introducing AI into these workflows, engineers can spend more time on system architecture, reliability, and innovation. This suggests that design automation in the AI era is moving beyond point-tool acceleration toward broader efficiency gains across ICs, packaging, PCBs, and system-level simulation.AI Deployment Through System IntegrationFocusing on system integration design trends in the AI era, Eric Kao, Business Development Director at Giga Computing, shared his perspective from the data center infrastructure side. He noted that as enterprises adopt AI agents and generative AI applications, inference workloads are growing rapidly, pushing data center architectures originally optimized for AI training to shift.This shift is also redefining the role of the CPU. Because AI agent workflows involve task decomposition, step-by-step planning, API calls, tool invocations, and other logic-heavy and I/O-intensive operations, the CPU is no longer just a supporting component next to GPUs or accelerators. Instead, it is becoming the control and orchestration hub inside the AI data center.Kao pointed out that future AI infrastructure will move toward more refined heterogeneous computing configurations. Effectively managing different platforms and resources—and matching the right hardware to the right models and workloads—will become a critical system design challenge.Giga Computing's own technology roadmap also reflects this transition. According to Kao, the company has expanded from server motherboards and system development into HPC, OCP, GPU servers, liquid cooling, heterogeneous computing platforms, and broader AI infrastructure services. This shows that competition in AI data centers is shifting from standalone server specifications to integrated capabilities across racks, cooling, networking, software, POD design, and system-level simulation.Po-Ting Lin, Professor in the Department of Mechanical Engineering and Director of the Center for Intelligent Robotics (CIR) at National Taiwan University of Science and Technology (NTUST), approached AI from the perspective of physical system applications. He shared his team's experience applying AI to obstacle-avoiding path planning for robotics.Lin explained that when a robot encounters nearby people or obstacles during operation, it must quickly determine a safe trajectory to avoid collisions. Traditional optimization methods can be used to search for safe paths, but they often require significant computation time. By incorporating AI models, the system has the potential to greatly shorten response time.Lin emphasized that robot obstacle avoidance is not about taking the longest possible detour. The goal is to find a path that avoids obstacles just enough while maintaining task efficiency. NTUST's robotics research covers human-robot collaborative robotic arms, UAV inspection, and dual-arm robotic systems, with a common focus on balancing safety and operational efficiency.Through the insights shared by these two speakers, it is evident that bringing AI into real-world applications depends not only on a single chip or algorithm but also on the integration of computing, software, sensing, simulation, and physical systems.Intelligent Tools and Simulation Integration Across the Design FlowThe afternoon sessions of Graser TECHTALKS 2026 focused on two major tracks: electronic system design automation and multiphysics simulation. Graser's engineering team highlighted the latest advances in Cadence Allegro/OrCAD X 25.1 and Allegro X AI, demonstrating how automation and AI-assisted design can improve PCB development workflows.The program also featured technical experts from AIC, Supermicro, and Cadence, who shared practical insights into power integrity, electrothermal co-simulation, AI server system design, and multiphysics optimization, spanning packaging to system-level design, using Cadence Sigrity, Clarity, Celsius 3D, Sigrity HPC, and Aurora.Graser also presented updates to its in-house software portfolio, including GraserWARE, GIMS, and CAMPro, addressing requirements such as circuit reliability checks, component and BOM management, and manufacturing data validation.Building on features introduced last year, the company added several practical tools to GraserWARE MSAPack, including simulation schedule management, stackup format conversion, S-parameter port-naming optimization, temperature-dependent material parameter fitting, and automatic Power Tree generation. These capabilities help streamline SI/PI simulation workflows while improving analysis efficiency and data consistency.The key takeaway from Graser TECHTALKS 2026 is that in the AI era, design competitiveness goes beyond upgrading individual tools—it depends on how effectively organizations can synchronize design, analysis, verification, and manufacturing data to enable faster, more agile system-level development.