Turning computing heat into a practical heating solution for greenhouses.
Updated
January 8, 2026 6:27 PM
Inside of a workstation computer with red lighting. PHOTO: UNSPLASH
Most computing systems have one unavoidable side effect: they get hot. That heat is usually treated as a problem and pushed away using cooling systems. Canaan Inc., a technology company that builds high-performance computing machines, is now showing how that same heat can be reused instead of wasted.
In a pilot project in Manitoba, Canada, Canaan is working with greenhouse operator Bitforest Investment to recover heat generated by its computing systems. Rather than focusing only on computing output, the project looks at a more basic question—what happens to all the heat these machines produce and can it serve a practical purpose?
The idea is simple. Canaan’s computers run continuously and naturally generate heat. Instead of releasing that heat into the environment, the system captures it and uses it to warm water. That warm water is then fed into the greenhouse’s existing heating system. As a result, the greenhouse needs less additional energy to maintain the temperatures required for plant growth.
This is enabled through liquid cooling. Instead of using air to cool the machines, a liquid circulates through the system and absorbs heat more efficiently. Because liquid retains heat better than air, the recovered water reaches temperatures that are suitable for industrial use. In effect, the computing system supports greenhouse heating while continuing to perform its primary computing function.
What makes this approach workable is that it integrates with existing infrastructure. The recovered heat does not replace the greenhouse’s boilers but supplements them. By preheating the water that enters the boiler system, the overall energy demand is reduced. Based on current assumptions, Canaan estimates that a significant portion of the electricity used by the servers can be recovered as usable heat, though actual results will be confirmed once the system is fully operational.
This matters because heating is one of the largest energy expenses for commercial greenhouses, particularly in colder regions like Canada. Many facilities still rely heavily on fossil-fuel-based heating and policies such as carbon pricing are encouraging lower-emission alternatives. Reusing computing heat offers a way to improve efficiency without requiring a complete overhaul of existing systems.
The project is planned to run for an initial two-year period, allowing Canaan to evaluate real-world performance factors such as reliability, system stability and maintenance needs. These findings will help determine whether the model can be replicated in other agricultural or industrial settings.
More broadly, the initiative reflects a shift in how computing infrastructure can be designed. Instead of operating as energy-intensive systems isolated from everyday use, computing equipment can contribute to real-world applications. Canaan’s greenhouse pilot highlights how excess heat—often seen as a by-product—can become part of a more efficient and thoughtful energy loop.
In doing so, the project suggests that improving sustainability in technology is not only about reducing energy consumption, but also about finding smarter ways to reuse the energy already being generated.
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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.