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.  

LITEON Technology is actively capitalizing on the AI boom by restructuring its data center infrastructure around megawatt-scale power, rack and liquid cooling. The company has developed high-density 800 VDC power architectures and advanced cooling systems to support massive, next-generation AI accelerators.At COMPUTEX 2026, LITEON hosted the "AI Summit Panel" on the opening day, themed "Powering the AI-driven Future: Scaling AI Across Architecture, Systems, and Infrastructure." Moderated by Colley Hwang, Chairman of DIGITIMES, the Panel brought together industry leaders from NVIDIA, Infineon and GIGABYTE to examine how AI is reshaping the technology landscape. The discussion highlighted how rapid AI adoption is driving structural changes brought across the ecosystem, particularly in data center infrastructure and power demand. As AI scales, power availability and efficiency are becoming central considerations, with AI factories emerging as a defining paradigm in the next phase of industry development.Hwang opened by noting that AI has become a key driver of global productivity growth and is expected to generate trillions of dollars in economic value. As a result, infrastructure and deployment models are being fundamentally reshaped, with data centers rapidly evolving into AI factories. In this transition, the availability and reliability of energy have emerged as critical enablers of large-scale deployment, elevating power and cooling from supporting functions to core elements of system architecture.More than just chips, AI revolution requires huge energyNVIDIA Senior Director, HPC and AI Hyperscale infrastructure Solutions, Dion Harris spoke first. He referenced NVIDIA CEO Jensen Huang's speech in the NVIDIA GTC Taipei held in the previous day, addressing the "five-layer cake" analogy to illustrate AI from being just a software tool into a vast, vertically integrated industrial system. At the very bottom of the cake is "energy". Before the AI can showcase real-time intelligence, the systems fundamentally rely on efficient and stable power supply."Building AI factories goes beyond compute-you have to power them, cool them, and run them reliably to truly monetize AI," said Dion Harris at NVIDIA. "Infrastructure and energy play a critical role in determining token cost and performance per watt. As Jensen Huang's‘five-layer cake’ illustrates, without strong foundational layers, higher-level innovation cannot scale. This is why ecosystem collaboration is essential."Harris further mentioned NVIDIA DSX platform as a blueprint for AI factory development, defining how next-generation infrastructure is designed, built and operated. Under this framework, AI factories are evolving to support rapidly growing token demand driven by today's AI applications. He emphasized that achieving optimal token cost and performance per watt ultimately relies on strong ecosystem collaboration, noting that partners like LITEON play a critical role in delivering the power, cooling, and operational capabilities required to support frontier and open-source AI workloads at scale.Dr. Sergio Rossi, Vice President of Application Marketing at AI and Power division of Infineon Technologies, noted that AI adoption accelerates, the key competitive bottleneck is shifting from compute to energy, especially in regions such as Europe where electricity availability has become increasingly constrained. That's the reasons why LITEON, NVIDIA, GIGABYTE and Infineon engage in collaboration to have several steps forward to make sure the design is using the right technology, architecture and solutions for securing AI development to use energy in the most efficient manner."Just improving energy efficiency by a few percentage points can translate into saving power at the scale of an entire city, highlighting how critical efficiency has become in AI data center development," said Dr. Serio Rossi.Rossi further highlighted that the AI ecosystem is facing three key complexities, including acceleration, with development cycles shortening from 30 months to 6 months; increasing architectural complexity driven by the adoption of 800 VDC in next-generation data centers; and rapid innovation in power technologies such as SiCs and GaNs to enhance energy efficiency. To address these challenges, he emphasized the importance of close ecosystem collaboration, where infrastructure stakeholders work together to anticipate future demand and align on technology roadmaps with partners such as Infineon at an early stage. This enables faster development cycles and accelerates innovation in power and infrastructure solutions for evolving AI requirements.Leo Wang, EMEA regional Product & Marketing Lead at Giga Computing, talked about how the company collaborates with industry leaders to advance AI performance through hardware innovation and liquid-cooled server solutions optimized for AI workloads. He noted that as AI infrastructure evolves, the focus is extending beyond server performance to broader data center challenges, particularly in power and thermal management.Wang added that maximizing the value generated from available energy is becoming a key industry priority, making close ecosystem collaboration essential. Leveraging Taiwan's strong supply chain and close engagement with global partners, this collaboration is helping to establish scalable deployment models and best practices for global AI adoption."We are now dealing with increasingly heterogeneous machines, from training systems to different AI applications, so power and space both need to be carefully managed, as all of these resources are limited," said Leo Wang at Giga Computing, "Everything comes down to how we build a proper data center and a proper environment to serve the server in a consistent way. It is no longer just about building servers, but about optimizing at the data center level to ensure power is allocated and utilized in an effective and efficient way."From Power to Infrastructure: Enabling the Next Phase of AI ScalingIn response to the energy and infrastructure challenges highlighted in the panel, LITEON showcased its integrated capabilities across power, mechanical, and thermal systems to support next-generation AI infrastructure at COMPUTEX 2026. LITEON debuts 800 VDC liquid-cooled power rack, alongside a comprehensive portfolio of solutions, including the 110kW power shelf for NVIDIA Vera Rubin NVL72 platforms and the 280kW in-rack CDU. Together, these offerings address the growing demand for high-density and energy-efficient AI infrastructure, demonstrating LITEON's ability to integrate power delivery, thermal management, and system design to support scalable AI deployment, and reinforcing its role as a key enabler in the evolution toward megawatt-scale AI data centers.

Clientron, a premier global provider of smart endpoint solutions, today announced a strategic partnership with Parallels, a global leader in cross-platform and virtualization solutions. Through this collaboration, Clientron will bring Parallels Workspace solutions including Parallels RAS (Remote Application Server), Parallels Browser Isolation and Parallels DaaS to organizations across Southeast Asia, offering a simple, flexible, and secure alternative for businesses looking to modernize digital workspaces and reduce IT cost and complexity.In today's hybrid work era, IT teams across Southeast Asia are increasingly burdened by "Legacy VDI Platforms" and are increasingly looking for ways to simplify digital workspace management, reduce operational overhead, and improve cost efficiency. Parallels Workspace solutions address these challenges with streamlined deployment, flexible infrastructure support, and cost-effective application and desktop delivery across hybrid and multi-cloud environments."Businesses want to stop using old and costly systems," said Vivienne Weng, Vice President at Clientron. "Parallels is a great way to reduce the work for IT teams. With Clientron's high-performance hardware, we help IT managers in Asia move away from expensive setups to a smarter and easier way to manage their workspaces.""Many organizations across Southeast Asia are currently seeking solutions to modernize their digital workspace strategies," said Asif Khan, Country Sales Manager at Parallels. "As a strong mid-market enabler, Parallels helps organizations simplify application and desktop delivery with secure, flexible solutions designed for hybrid and multi-cloud environments - backed by competitive and cost-effective pricing. Together with Clientron, we're expanding access to these modern workspace solutions across the region."Key Advantages of Clientron x Parallels:1. Cost-Effective Seamless Access: Smoothly run critical apps on Mac, Windows, or Linux platforms while cutting Total Cost of Ownership (TCO); 2. Deployment Without Complexity: Parallels Workspace Solutions can be deployed in hours with minimal specialized training; 3. Ultimate IT Flexibility: Support workloads across hybrid, multi-cloud, and on-premises environments, protecting enterprises from vendor lock-in; 4. Stronger Security: Modern encryption and login technology to keep your data safe with high-class protection while staying fast and smooth; and 5. Localized Southeast Asia Support: Dedicated focus on key Southeast Asian markets including Malaysia, Thailand, the Philippines, Taiwan, Vietnam, and Indonesia, helping customers and partners access localized expertise, deployment support, and faster regional engagement.Moving forward, Clientron will continue to expand its footprint in Asia, working closely with channel partners to promote Parallels solutions and help enterprises build 'Smart Secure Workspaces' for the future.Deliver secure apps and desktops via Parallels RAS with simple VDI and seamless remote access.Credit: Clientron