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.

In the past, due to high equipment costs and bulky sizes, thermal imaging technology was predominantly confined to specialized fields such as security surveillance, firefighting and rescue, military defense, and high-end industrial inspection. However, driven by declining sensor costs, maturing AI algorithms, and rapid advancements in module miniaturization, thermal imaging applications have expanded from specialized niches to a broader range of commercial and consumer markets. These include predictive maintenance, EV battery monitoring, and AI-automated inspection.The global thermal imaging market is projected to grow from USD 9.21 billion in 2026 to USD 14.51 billion by 2030, representing a compound annual growth rate (CAGR) of approximately 12%. To help Taiwanese industries capture this massive market potential, Suntek Global has partnered with Teledyne FLIR to establish a local thermal imaging ecosystem. Beyond offering a comprehensive product portfolio, Suntek delivers multifaceted technical support services, providing an all-in-one solution that accelerates deployment for local enterprises.Jason Ray, CEO & Managing Partner of Suntek Global, stated that Teledyne FLIR is the undisputed global leader in the commercial thermal imaging market, offering an exceptional range of sensors, focal plane arrays, and thermal calibration solutions recognized worldwide for their quality and diversity. Suntek focuses on localized integration and engineering deployment services, covering custom carrier boards, firmware development, AI model integration, IP-rated enclosure design, regulatory certification, module QA calibration, and localized technical support. The goal of this joint ecosystem is to provide Taiwanese industries with ready-to-mass-produce thermal imaging solutions. Backed by Teledyne FLIR's OEM resources, Suntek assists clients through reference design, thermal module integration, firmware development, and mass production deployment. Suntek's mission is to ensure that Taiwanese device makers do not have to become thermal experts to build thermal-enabled products — they can leverage Suntek's expertise, integrate, and go to market.AI and Cost Reduction Drive Thermal Imaging into Mass MarketsBenefiting from the continuous decline in thermal module costs, a wide range of new application scenarios has emerged. These include smart buildings, energy management, home security, robotics, automation equipment, and consumer electronics, driving thermal imaging from niche professional domains into mass markets. Notably, unlike traditional night-vision cameras, thermal imaging modules detect the thermal contours emitted by humans or objects. This uniquely satisfies the dual demand for advanced sensing and privacy protection in various settings. Consequently, these solutions are being widely adopted in smart buildings, long-term care facilities, public spaces, and smart city developments.Taiwan stands as a global hub for semiconductors and high-tech manufacturing. While many local OEMs and ODMs possess robust hardware manufacturing capabilities, integrating thermal imaging modules into products inevitably presents hurdles such as radiometric calibration, FFC (Flat Field Correction), and ISP tuning—tasks that typically require substantial time and talent investment. To address this, Suntek Global aims to lower the barrier to entry through localized support services, allowing companies to integrate thermal imaging into their product design cycles more efficiently. From knowledge sharing and training to reference designs, Suntek is fully committed to building Taiwan's thermal imaging ecosystem.A prime example is AiForce, a company specializing in thermal imaging sensors, optical components, and AI vision training integration, dedicated to creating high-performance, multi-scenario intelligent vision systems. With full technical backing from Suntek Global, AiForce successfully compressed its product development timeline, enabling it to launch its new solutions to the market in the shortest time possible.Ethen Zhong, CEO of AiForce, noted, "Teledyne FLIR's thermal imaging components are undoubtedly top-tier global products. However, because of this, it is challenging for the original manufacturer to provide immediate, localized support to every regional user, making a dependable distributor indispensable. Although we are highly proficient in AI and thermal imaging component integration, we still encountered various calibration and parameter adjustment challenges during development. This is where Suntek Global played a critical role. Suntek Global is no longer just a traditional distributor; they act as a vital bridge connecting original manufacturer technology, local engineering resources, and customer needs. By helping us resolve module integration, image tuning, software-hardware validation, and production introduction issues, they enabled AiForce to focus entirely on application innovation and accelerate our commercialization timeline."From Technical Support to Talent Cultivation: Building Taiwan's Thermal EcosystemAs global demand for thermal imaging surges, product competitiveness will no longer rely solely on hardware specifications. Instead, it will hinge on the integration capabilities across sensors, algorithms, AI inference, optics, and system platforms. To this end, Suntek Global is mapping out its ecosystem across four core pillars to help Taiwanese industries capture this massive market potential.Jason Ray pointed out that the first pillar is knowledge promotion, which begins with the launch of the "Thermal Tech" column to provide in-depth technical analysis and case studies. The second is talent training, offering courses that cover thermal integration, ISP tuning, and AI model deployment. The third is reference design and demonstration platforms to accelerate client development processes. Finally, the fourth pillar focuses on vertical industry application showcases, ensuring partners stay informed of the latest trends and practical use cases.From sensors and modules to AI vision integration, the thermal imaging market is rapidly entering a new growth cycle.  The thermal revolution is no longer on the horizon — it is already reshaping Taiwan's manufacturing landscape. Suntek Global, in partnership with Teledyne FLIR, intends to be the connective tissue that makes Taiwan's leadership in this space inevitable.Teledyne FLIR Boson thermal camera module. Credit: Suntek GlobalThermal imaging application for industrial monitoring. Credit: Suntek Global

The integration of artificial intelligence into the semiconductor industry is no longer merely a competitive advantage - it has become a core driver of modern engineering.The Industrial Development Administration (IDA) under Taiwan's Ministry of Economic Affairs is committed to building a comprehensive training and support ecosystem for international talents in Taiwan. The initiative covers key semiconductor technologies, cross-cultural communication, and local integration, while also leveraging online learning resources to connect talent across the Asia-Pacific region.Designed to help outstanding international students and professionals transition seamlessly into Taiwan's semiconductor industry, the program provides early exposure to the local industrial ecosystem, along with mentorship and tailored support services that strengthen long-term adaptation, professional growth, and career development in Taiwan. Through these efforts, Taiwan aims to cultivate a more inclusive and globally connected environment for international talent, further enhancing the global competitiveness of its semiconductor industry.Through specialized talent development programs in Taiwan, Wifal Inola from Indonesia and Earon John Mendoza from the Philippines are transforming their professional capabilities and expanding their roles in the global semiconductor ecosystem.By bridging the gap between theoretical AI knowledge and its practical application in high-tech manufacturing and research and development, these programs are cultivating a new generation of interdisciplinary talent prepared for the future of advanced technology industries.Advancing technical depth and specialized applicationThe training provided in Taiwan offers a significant shift in both technical depth and industrial focus compared with the educational experiences available in the engineers' home countries.Wifal Inola, a master's student in the Department of Semiconductor Technology at National Yang Ming Chiao Tung University (NYCU), observed that while AI training in Indonesia often focuses on supporting the digital economy through e-commerce and financial technology, Taiwan's curriculum is deeply rooted in advanced semiconductor applications and system integration. This includes specialized fields such as smart manufacturing, medical technology, and robotics.Similarly, Earon John Mendoza, a QW1612 Assistant Engineer at ASE and a post-baccalaureate student at I-Shou University, emphasized that AI-related training in Taiwan is far more structured and technically rigorous. He noted a clear contrast with his previous educational experience in the Philippines, where the focus was often placed on final output and task completion under pressure.In Taiwan, however, the emphasis is placed on understanding every step involved in building AI models - ensuring engineers understand not only how a process works, but why each stage is necessary. This foundational approach is especially critical in semiconductor manufacturing, where skipping steps in troubleshooting or equipment maintenance can lead to serious systemic failures.Enhancing efficiency through AI tools in R&D and manufacturingBoth engineers have successfully integrated AI tools into their daily workflows, reducing manual workloads and allowing greater focus on high-value technical decision-making.Wifal Inola, who secured both an internship and a future full-time position at Micron as a Process Engineer in Diffusion Process, uses AI to streamline the demanding research process required in semiconductor studies. He applies AI tools to significantly reduce the time spent on literature reviews, allowing him to quickly understand unfamiliar research topics.He also leverages AI for technical analysis tasks such as X-ray Photoelectron Spectroscopy (XPS) peak division and chemical bond identification. By delegating repetitive analytical work to AI, Wifal is able to focus more on designing better experiments and optimizing process parameters.In the industrial sector, Earon applies AI knowledge within ASE's preventive maintenance operations to ensure production lines remain stable and efficient. His work focuses on hardware-related systems such as sensors, controllers, and equipment monitoring.In an environment where every minute of machine downtime translates into significant production losses, AI becomes a critical tool for operational efficiency. Earon uses AI-assisted inspection systems and computer-based monitoring tools to track equipment failures and identify non-good (NG) parts with high precision.His background in mechatronics, combined with AI training, allows him to better understand how different hardware components interact - helping him identify faster and more effective solutions while improving productivity beyond standard performance targets.Localized AI development beyond manufacturingBeyond hardware and manufacturing applications, both Taiwan and other countries are also developing localized AI models to better serve their own linguistic and cultural environments.Wifal noted that Taiwan has developed TAIDE (Trustworthy AI Dialogue Engine), which focuses on traditional Chinese language applications and local cultural context. At the same time, Indonesia has introduced Sahabat AI, a model designed specifically for Bahasa Indonesia and regional dialects.This development highlights that AI training is not solely about meeting global technical standards - it is also about understanding how technology can be adapted to serve local populations more effectively.The future: from manual labor to strategic decision-makingBoth engineers believe AI will fundamentally reshape the semiconductor industry over the next five to ten years. Wifal believes AI will eventually take over most repetitive and manual tasks, shifting the role of engineers toward high-level decision-making based on AI-assisted analysis and predictive systems.This transformation will require a new type of professional - one who combines deep semiconductor expertise with strong capabilities in data analysis and AI fundamentals.Earon shares a similar view, expecting AI to become a key solution for reducing time-consuming and physically demanding tasks that engineers currently perform manually. This will allow professionals to focus more on solving complex technical challenges and driving innovation.As AI continues to automate repetitive work and redefine traditional engineering roles, the experience gained in Taiwan ensures these professionals remain at the forefront of industry transformation.Whether they return to their home countries or continue their careers at world-class companies such as Micron and ASE, they carry with them the technical depth, operational efficiency, and strategic mindset needed to lead AI-integrated engineering teams.Ultimately, this talent exchange creates a true win-win scenario: Southeast Asian engineers gain access to world-class career opportunities, while the global semiconductor industry benefits from a more resilient, technically sophisticated, and future-ready workforce.A new era of global synergyThe stories of Wifal Inola and Earon John Mendoza reflect a broader shift in the global semiconductor landscape - one where talent mobility and specialized AI training are becoming key drivers of innovation.By opening its doors to engineers from Indonesia and the Philippines, Taiwan is doing more than addressing talent shortages. It is fostering an advanced ecosystem of professionals who are fluent in both semiconductor engineering and artificial intelligence.For the engineers themselves, the journey is transformative - turning them into interdisciplinary leaders capable of navigating the growing complexity of modern manufacturing, process optimization, and R&D.As the semiconductor industry becomes increasingly AI-driven, these talent development programs are ensuring that the next generation of Southeast Asian engineers is not simply adapting to change - they are prepared to lead it.