AI’s expansion into the physical world is reshaping what investors choose to back
Updated
February 12, 2026 1:21 PM
Exterior view of the Exchange Square in Central, Hong Kong. PHOTO: UNSPLASH
Artificial intelligence is often discussed in terms of large models trained in distant data centres. Less visible, but increasingly consequential, is the layer of computing that enables machines to interpret and respond to the physical world in real-time. As AI systems move from abstract software into vehicles, cameras and factory equipment, the chips that power on-device decision-making are becoming strategic assets in their own right.
It is within this shift that Axera, a Shanghai-based semiconductor company, began trading on the Hong Kong Stock Exchange on February 10 under the ticker symbol 00600.HK. The company priced its shares at HK$28.2, debuting with a market capitalization of approximately HK$16.6 billion. Its listing marks the first time a Chinese company focused primarily on AI perception and edge inference chips has gone public in the city — a milestone that underscores growing investor interest in the hardware layer of artificial intelligence.
The listing comes at a time when demand for flexible, on-device intelligence is expanding. As manufacturers, automakers and infrastructure operators integrate AI into physical systems, the need for specialized processors capable of handling visual and sensor data efficiently has grown. At the same time, China’s domestic semiconductor industry has faced increasing pressure to build local capabilities across the chip value chain. Companies such as Axera sit at the intersection of these dynamics, serving both commercial markets and broader industrial policy priorities.
For Hong Kong, the debut adds to a cohort of technology companies seeking public capital to scale hardware-intensive businesses. Unlike software firms, semiconductor designers operate in a capital-intensive environment shaped by supply chains, fabrication partnerships and rapid product cycles. Their presence on the exchange reflects a maturing investor appetite for AI infrastructure, not just consumer-facing applications.
Axera’s early backer, Qiming Venture Partners, led the company’s pre-A financing round in 2020 and continued to participate in subsequent rounds. Prior to the IPO, it held more than 6 percent of the company, making it the second-largest institutional investor. The public offering provides liquidity for early investors and new funding for a company operating in a highly competitive and technologically demanding sector.
Axera’s market debut does not resolve the competitive challenges of the semiconductor industry, where innovation cycles are short and global competition is intense. But it does signal that investors are placing tangible value on the hardware, enabling AI’s expansion beyond the cloud. In that sense, the listing represents more than a corporate milestone; it reflects a broader transition in how artificial intelligence is built, deployed and financed — moving steadily from software abstraction toward the silicon that makes real-world autonomy possible.
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How Korea is trying to take control of its AI future.
Updated
January 13, 2026 10:56 AM
SK Telecom Headquarters in Seoul, South Korea. PHOTO: ADOBE STOCK
SK Telecom, South Korea’s largest mobile operator, has unveiled A.X K1, a hyperscale artificial intelligence model with 519 billion parameters. The model sits at the center of a government-backed effort to build advanced AI systems and domestic AI infrastructure within Korea. This comes at a time when companies in the United States and China largely dominate the development of the most powerful large language models.
Rather than framing A.X K1 as just another large language model, SK Telecom is positioning it as part of a broader push to build sovereign AI capacity from the ground up. The model is being developed as part of the Korean government’s Sovereign AI Foundation Model project, which aims to ensure that core AI systems are built, trained and operated within the country. In simple terms, the initiative focuses on reducing reliance on foreign AI platforms and cloud-based AI infrastructure, while giving Korea more control over how artificial intelligence is developed and deployed at scale.
One of the gaps this approach is trying to address is how AI knowledge flows across a national ecosystem. Today, the most powerful AI foundation models are often closed, expensive and concentrated within a small number of global technology companies. A.X K1 is designed to function as a “teacher model,” meaning it can transfer its capabilities to smaller, more specialized AI systems. This allows developers, enterprises and public institutions to build tailored AI tools without starting from scratch or depending entirely on overseas AI providers.
That distinction matters because most real-world applications of artificial intelligence do not require massive models operating independently. They require focused, reliable AI systems designed for specific use cases such as customer service, enterprise search, manufacturing automation or mobility. By anchoring those systems to a large, domestically developed foundation model, SK Telecom and its partners are aiming to create a more resilient and self-sustaining AI ecosystem.
The effort also reflects a shift in how AI is being positioned for everyday use. SK Telecom plans to connect A.X K1 to services that already reach millions of users, including its AI assistant platform A., which operates across phone calls, messaging, web services and mobile applications. The broader goal is to make advanced AI feel less like a distant research asset and more like an embedded digital infrastructure that supports daily interactions.
This approach extends beyond consumer-facing services. Members of the SKT consortium are testing how the hyperscale AI model can support industrial and enterprise applications, including manufacturing systems, game development, robotics and autonomous technologies. The underlying logic is that national competitiveness in artificial intelligence now depends not only on model performance, but on whether those models can be deployed, adapted and validated in real-world environments.
There is also a hardware dimension to the project. Operating an AI model at the 500-billion-parameter scale places heavy demands on computing infrastructure, particularly memory performance and communication between processors. A.X K1 is being used to test and validate Korea’s semiconductor and AI chip capabilities under real workloads, linking large-scale AI software development directly to domestic semiconductor innovation.
The initiative brings together technology companies, universities and research institutions, including Krafton, KAIST and Seoul National University. Each contributes specialized expertise ranging from data validation and multimodal AI research to system scalability. More than 20 institutions have already expressed interest in testing and deploying the model, reinforcing the idea that A.X K1 is being treated as shared national AI infrastructure rather than a closed commercial product.
Looking ahead, SK Telecom plans to release A.X K1 as open-source AI software, alongside APIs and portions of the training data. If fully implemented, the move could lower barriers for developers, startups and researchers across Korea’s AI ecosystem, enabling them to build on top of a large-scale foundation model without incurring the cost and complexity of developing one independently.