Robots enter the World Cup, shifting how large-scale events are run and experienced
Updated
April 8, 2026 10:35 AM
Hyundai Motor Company Dealership, Alabama, US. PHOTO: ADOBE STOCK
As the FIFA World Cup 2026 approaches, attention is beginning to shift beyond the matches themselves to how an event of this scale is organised and run. Managing teams, coordinating venues and handling large crowds requires a system that works with precision. This time, robotics is set to become part of that system.
Hyundai Motor Company, a long-time FIFA partner, is expanding its role for the 2026 tournament. Alongside its traditional responsibility of providing vehicles for teams, officials and media, the company will introduce robotics in collaboration with Boston Dynamics. Robots including Atlas and Spot are expected to be deployed at selected venues.
According to the announcement, these systems will be used to support tournament operations while contributing to safety and efficiency. They will also play a role in shaping how fans experience the event, indicating a broader use of technology within the tournament environment. While specific use cases have not been detailed, the inclusion of robotics reflects a growing effort to integrate advanced systems into large-scale public events.
The direction was introduced through the company’s global campaign, “Next Starts Now,” unveiled at the 2026 New York International Auto Show. The campaign is positioned around its wider focus on innovation across mobility and robotics, aligning with its long-standing partnership with FIFA, which now spans more than two decades. As part of the 2026 tournament, the company will also deploy its largest mobility fleet to date, working alongside these newer systems across venues.
Beyond operations, the initiative extends into community engagement. Youth football camps are set to take place across four host cities in the United States—Atlanta, Miami, New Jersey and Los Angeles—targeting children between the ages of six and twelve. A global drawing programme will also invite young fans to submit artwork supporting their national teams, with selected designs to be featured on official team buses during the tournament.
Taken together, the introduction of robotics alongside existing infrastructure points to a gradual shift in how major events are supported. Rather than operating only behind the scenes, technology is becoming more visible within the event itself. How these systems perform in a live, large-scale setting will become clearer once the tournament begins.
Keep Reading
The hidden cost of scaling AI: infrastructure, energy, and the push for liquid cooling.
Updated
January 8, 2026 6:31 PM
The inside of a data centre, with rows of server racks. PHOTO: FREEPIK
As artificial intelligence models grow larger and more demanding, the quiet pressure point isn’t the algorithms themselves—it’s the AI infrastructure that has to run them. Training and deploying modern AI models now requires enormous amounts of computing power, which creates a different kind of challenge: heat, energy use and space inside data centers. This is the context in which Supermicro and NVIDIA’s collaboration on AI infrastructure begins to matter.
Supermicro designs and builds large-scale computing systems for data centers. It has now expanded its support for NVIDIA’s Blackwell generation of AI chips with new liquid-cooled server platforms built around the NVIDIA HGX B300. The announcement isn’t just about faster hardware. It reflects a broader effort to rethink how AI data center infrastructure is built as facilities strain under rising power and cooling demands.
At a basic level, the systems are designed to pack more AI chips into less space while using less energy to keep them running. Instead of relying mainly on air cooling—fans, chillers and large amounts of electricity, these liquid-cooled AI servers circulate liquid directly across critical components. That approach removes heat more efficiently, allowing servers to run denser AI workloads without overheating or wasting energy.
Why does that matter outside a data center? Because AI doesn’t scale in isolation. As models become more complex, the cost of running them rises quickly, not just in hardware budgets, but in electricity use, water consumption and physical footprint. Traditional air-cooling methods are increasingly becoming a bottleneck, limiting how far AI systems can grow before energy and infrastructure costs spiral.
This is where the Supermicro–NVIDIA partnership fits in. NVIDIA supplies the computing engines—the Blackwell-based GPUs designed to handle massive AI workloads. Supermicro focuses on how those chips are deployed in the real world: how many GPUs can fit in a rack, how they are cooled, how quickly systems can be assembled and how reliably they can operate at scale in modern data centers. Together, the goal is to make high-density AI computing more practical, not just more powerful.
The new liquid-cooled designs are aimed at hyperscale data centers and so-called AI factories—facilities built specifically to train and run large AI models continuously. By increasing GPU density per rack and removing most of the heat through liquid cooling, these systems aim to ease a growing tension in the AI boom: the need for more computers without an equally dramatic rise in energy waste.
Just as important is speed. Large organizations don’t want to spend months stitching together custom AI infrastructure. Supermicro’s approach packages compute, networking and cooling into pre-validated data center building blocks that can be deployed faster. In a world where AI capabilities are advancing rapidly, time to deployment can matter as much as raw performance.
Stepping back, this development says less about one product launch and more about a shift in priorities across the AI industry. The next phase of AI growth isn’t only about smarter models—it’s about whether the physical infrastructure powering AI can scale responsibly. Efficiency, power use and sustainability are becoming as critical as speed.