AI growth is increasingly becoming a manufacturing, packaging and deployment challenge — not just a computing one.
Updated
May 26, 2026 5:28 PM
Taipei 101 and Taipei Nan Shan Plaza, viewed from Elephant Mountain. PHOTO: UNSPLASH
As AI companies continue scaling larger models and data centers, the pressure is no longer falling only on chip design. Manufacturing capacity, advanced packaging and infrastructure deployment are becoming equally important parts of the AI race. AMD’s latest investment announcement reflects how quickly that shift is accelerating.
The US chipmaker announced plans to invest more than US$10 billion across Taiwan’s semiconductor and manufacturing ecosystem to support next-generation AI infrastructure. The investment focuses on expanding partnerships and increasing advanced packaging capacity needed for future AI systems.
The announcement highlights a growing reality across the AI industry. Building powerful AI chips is no longer enough on its own. Companies now also need the manufacturing networks, packaging technologies and supply chain coordination required to deploy AI infrastructure at global scale.
AMD’s investments center heavily around advanced chip packaging, an area becoming increasingly critical as AI systems demand higher performance and greater power efficiency. Traditional chip architectures are struggling to keep pace with the size and complexity of modern AI workloads. Advanced packaging helps connect processors, memory and computing systems more efficiently while managing power and cooling limitations inside large-scale AI environments.
The company said it is working with Taiwan-based partners including ASE, SPIL and PTI to develop next-generation packaging technologies for its upcoming 6th Gen AMD EPYC processors, codenamed “Venice.” AMD also said it had qualified what it described as the industry’s first 2.5D panel-based EFB interconnect technology alongside PTI.
At the center of the broader strategy is AMD Helios, the company’s rack-scale AI infrastructure platform scheduled for deployment beginning in the second half of 2026. The platform combines AMD Instinct MI450X GPUs, 6th Gen EPYC CPUs, networking systems and AMD’s ROCm software stack into integrated AI infrastructure systems designed for hyperscale deployment.
Rather than selling individual processors alone, companies are increasingly building complete AI infrastructure platforms that combine hardware, software, cooling systems and power management into unified deployments. That transition is reshaping how AI infrastructure is designed, manufactured and delivered.
Taiwan is also becoming more deeply embedded in that process. AMD’s investment spans not only semiconductor packaging companies but also manufacturing and system integration partners including Sanmina, Wiwynn, Wistron and Inventec. The partnerships reflect Taiwan’s growing role as one of the operational centers of the global AI infrastructure economy.
Dr. Lisa Su, Chair and CEO of AMD, said: “As AI adoption accelerates, our global customers are rapidly scaling AI infrastructure to meet growing compute demand. By combining AMD leadership in high-performance computing with the Taiwan ecosystem and our strategic global partners, we are enabling integrated, rack-scale AI infrastructure that helps customers accelerate deployment of next-generation AI systems”.
Power efficiency is becoming another major challenge shaping AI infrastructure decisions. As AI workloads consume more electricity and generate more heat, infrastructure providers are increasingly being forced to rethink cooling systems, interconnect technologies and deployment economics.
AMD’s announcement signals how the AI competition is evolving beyond model development and raw computing power. The next stage may depend just as heavily on who can manufacture, package and deploy AI infrastructure fast enough to support global demand.
Keep Reading
Structured AI interviews and human judgment combine to address the global talent shortage
Updated
April 1, 2026 8:56 AM
ManpowerGroup World Headquarters in Milwaukee. PHOTO: ADOBE STOCK
As hiring pressures mount across global markets, ManpowerGroup is turning to technology to strengthen how it connects people to work. The workforce solutions major has announced a global partnership with Hubert, a startup focused on AI-driven structured interviews. The aim is simple: make hiring faster and fairer, without removing the human touch.
ManpowerGroup has spent decades operating at the center of the global labor market. The company works with employers across industries to fill roles, manage workforce planning and build talent pipelines. With millions of placements each year, it has a clear view of how strained hiring has become. A large share of employers today report difficulty finding skilled talent. At the same time, candidates expect more transparency, quicker feedback and flexibility in how they engage with employers.
Hubert enters this picture as a specialist in structured digital interviewing. The startup has built tools that allow candidates to complete interviews online, at any time, while being assessed against consistent criteria. Instead of relying on informal screening calls or resume filters, its system focuses on standardized questions tied directly to job requirements. The idea is to bring more consistency to early-stage hiring.
The partnership brings these capabilities into ManpowerGroup’s global operations. AI-powered interviews will now support the first stage of screening, helping recruiters identify qualified candidates earlier in the process. This does not replace recruiters. Final decisions and contextual judgment remain with experienced hiring professionals. What changes is the speed and structure of the initial assessment.
For employers, this could mean earlier visibility into job-ready talent and less time spent on manual screening. For candidates, it offers more flexibility. A significant portion of interviews on Hubert’s platform are completed outside regular office hours, allowing applicants to engage when it suits them. That flexibility can make a difference in competitive labor markets where timing matters.
The collaboration is also positioned as a step toward reducing bias. By evaluating each candidate against the same transparent standards, the process becomes more consistent. While no system can remove bias entirely, structured assessments can reduce the variability that often comes with unstructured interviews.
At its core, the partnership addresses a gap many large organizations are facing. They need scale and speed, but they cannot afford to lose the human judgment that good hiring depends on. Manual processes are too slow. Fully automated systems can feel impersonal and risky. ManpowerGroup’s approach suggests a middle path, where technology handles repetition and structure and recruiters focus on potential and fit.
The move also reflects a broader shift in the workforce industry. AI is no longer being tested on the sidelines. It is being built into the foundation of hiring operations. For established players like ManpowerGroup, the challenge is not whether to adopt AI, but how to do so responsibly and at scale.
By working with Hubert, the company is signaling that the future of recruitment will likely blend structured digital tools with human expertise. In a market defined by talent shortages and rising expectations, that balance may prove critical.