The manufacturing industry is facing major changes with the rapid development of artificial intelligence (AI) technology, which has made computing power and AI application services the “new oil” that fuels the competitiveness of enterprises. However, simply stacking hardware is not enough to run AI models, which are highly dependent on a stable and secure computing environment with low latency. The only way to ensure enterprise-level power, cooling, network bandwidth, and cybersecurity for the deployment of AI applications at scale is to set up the AI model in a professional Internet data center (IDC).
Founded in 2009, Global Instrument Technology (GIT) initially provided instrument rental and automation solutions. However, its business expanded along with the upgrading of Taiwan’s manufacturing industry, as it focused on optimizing networking, semiconductors, automotive electronics, and EMS production lines. It even expanded into surface defect detection for popular products, such as e-readers and Apple Watches. The company subsequently expanded to smart manufacturing solutions, such as the Industrial Internet of Things (IIoT) and early warning of anomalies, under Industry 4.0, expanding from single-point improvement to system-level optimization.
GIT saw that the clearest trend in the manufacturing industry in recent years has been the rapid adoption of AI by factories. Its application scenarios include image inspection and IIoT. However, in addition to software capabilities, the support of a stable and high performance computing environment and network architecture are also needed to actually run AI models in production lines.
To help customers in the manufacturing industry adopt AI more quickly, GIT partnered with Chunghwa Telecom to provide enterprises with an “AI application verification platform” and integration services in a secure and high performance professional IDC environment. This architecture allows enterprises to verify AI image inspection models and analyze the quality of AI models without increasing the burden of hardware, thus shortening the time from proof of concept to implementation.
Professional IDC has become the foundation for stably running AI models with cooling, power, network, and cybersecurity all in place
Tsai noted GIT chose a professional IDC to deliver stable AI services and trusted commitment. Credit:GIT
The biggest difference between AI servers and regular servers is their power consumption, heat generation, and bandwidth requirements. “It would be very hard to let corporate customers feel at ease if we kept our servers at the company and managed them ourselves.” Tsai Pei-Ying, IT Manager at the Head Office of GIT, got straight to the point: AI requires a trustworthy environment to ensure stable, high-performance, and secure processing.
Therefore, GIT set the goal to relocate into a professional IDC, and evaluated five key criteria: Is the power supply stable? Is the temperature under control? Is the bandwidth adequate and is the latency acceptable? Is cybersecurity good enough? Is the quality of professional services reliable? GIT evaluated numerous service providers, focusing on their ability to operate at full capacity for extended periods of time without interruption, as well as their scalability, so that new businesses would not be slowed down by infrastructure limitations once launched.
“From our perspective, IDC is not just a place to house servers, it is the foundation that enables AI applications to run stably,” said Tsai Pei-Ying. GIT delivers more than just AI, it delivers a comprehensive system integration service that encompasses equipment, data transmission, security, and maintenance, offering a total solution for AI implementation.
From cold aisles to high bandwidth, the guardian safeguarding the stability of AI servers
In the end, GIT chose Chunghwa Telecom’s IDC. “Chunghwa Telecom is able to fully meet all five of our requirements!” Tsai Pei-Ying pointed out that the instantaneous power consumption of a single AI server can reach up to 10 kW, so it has extremely high requirements on the stability of power supply.
Chunghwa Telecom’s IDC has a complete power and temperature control plan in place to ensure that servers can operate safely for extended periods of time. Using environmental control as an example, AI servers need to operate between 10 and 35 degrees Celsius, so Chunghwa Telecom specially designed “cold aisles” for faster heat dissipation and cooling to maintain optimal conditions for equipment.
AI applications impose equally astonishing demands not only on power and cooling, but also on bandwidth. Using AI image inspection as an example, the size of a high-resolution image can reach several hundred megabytes, so high network latency can greatly lower the efficiency of training and inference. Chunghwa Telecom’s IDC provides high bandwidth capable of instantly meeting massive data transmission demands, ensuring that customer services are not interrupted.
In terms of cybersecurity, Chunghwa Telecom has worked closely with GIT to tailor cybersecurity solutions. From hardware firewalls to “cybersecurity fleet” solutions, the comprehensive protection mechanisms not only allow GIT to provide AI services without any concerns, but also lay the foundation for future expansion.
“Chunghwa Telecom offers highly competitive one-stop services that have saved us great effort in resource integration.” Manager Tsai Pei-Ying was straightforward when explaining the main reason why the company made the decision: They have never had to worry about the quality of Chunghwa Telecom’s operation and maintenance. The value of providing one-stop services has been proven again and again in actual operations: All requests, no matter the scale, can be handled at a single window.
The top-tier quality of the IDC’s operation and maintenance has made GIT more confident in its future development
The services of Chunghwa Telecom’s IDC have gained the trust and confidence of GIT ever since it became a tenant. Stability is the top priority. In addition, the density of Chunghwa Telecom’s resources across multiple locations throughout Taiwan and its backbone network allows service nodes to be located closer to demand, achieving lower latency and greater stability.
GIT is currently focused on assisting the manufacturing industry in developing scenarios for implementing AI, such as image defect detection, automated quality monitoring, and digital twin systems. With the support of stable computing capacity provided by the IDC, these AI applications will be able to move on from proof of concept to become a part of routine operations, gradually becoming the new normal for smart manufacturing.
Trust is key: Let a professional IDC handle strategic infrastructure
Wang Sin-Siang, Vice General Manager of GIT (right), and Tsai Pei-Ying, IT Manager of GIT (left).Credit:GIT
From the perspective of GIT, the AI application verification platform is not a short-term project. It is a long-term strategic direction to be simultaneously carried out by the manufacturing industry. Stable, flexible, and secure infrastructure is the key to letting enterprises experiment with AI and not be priced out by the initial cost.
“Trust” is the key that makes all of this possible. As mentioned by Manager Tsai Pei-Ying, moving into a professional IDC is a necessary condition. Letting a team that understands data centers, networks, and operation and maintenance provide capital-intensive infrastructure is the only way AI will have a chance to move forward from technical projects to a stable part of routine operations. Chunghwa Telecom’s one-stop, single window is a catalyst for reducing friction and accelerating development. Stability, predictability, and scalability are what give customers peace of mind.
With the strong support of Chunghwa Telecom’s IDC, GIT is driving the rapid adoption of AI in the manufacturing industry. When AI is no longer an experiment and is fully embedded into production processes, Taiwan’s AI-enabled manufacturing industry will be able to move towards a replicable and sustainable future.