CES 2026 and the move toward wearable robots you don’t wear all day.
Updated
January 13, 2026 10:56 AM
The π6 exoskeleton from VIGX. PHOTO: VIGX
CES 2026 highlighted how robotics is taking many different forms. VIGX, a wearable robotics company, used the event to introduce the π6, a portable exoskeleton robot designed to be carried and worn only when needed. Unveiled in Las Vegas, the device reflects a broader shift at CES toward robotics that move with people rather than staying fixed in industrial or clinical settings.
Exoskeletons have existed for years, most commonly in controlled environments such as factories, rehabilitation facilities and specialised research settings. In these contexts, they have tended to be large, fixed systems intended for long sessions of supervised use rather than something a person could deploy on their own.
Against that backdrop, the π6 explores a more personal and flexible approach to assistance. Instead of treating an exoskeleton as permanent equipment, it is designed to be something users carry with them and wear only when a task or situation calls for extra support.
The π6 weighs 1.9 kilograms and folds down to a size that fits into a bag. When worn, it sits around the waist and legs, providing mechanical assistance during activities such as walking, climbing or extended movement. Rather than altering how people move, the system adds controlled rotational force at key joints to reduce physical strain over time.
According to the company, the device delivers up to 800 watts of peak power and 16 Nm of rotational force. In practical terms, this means the system is designed to help users sustain effort for longer periods, especially during physically demanding activities_ by easing the body's load rather than pushing it beyond normal limits.
The π6 is designed to support users weighing between 45 kilograms and 120 kilograms and is intended for intermittent use. This reinforces its role as a wearable companion — something taken out when needed and set aside when not — rather than a device meant to be worn continuously.
Another aspect of the system is how it responds to different environments. Using onboard sensors and processing, the exoskeleton can detect changes such as slopes or uneven ground and adjust the level of assistance accordingly. This reduces the need for manual adjustments and helps maintain a consistent walking experience across varied terrain, with software fine-tuning how assistance is applied rather than directing movement itself.
The hardware design follows a similar logic. The power belt contains a detachable battery, allowing users to remove or swap it without handling the entire system. This keeps the wearable components lighter and makes the exoskeleton easier to transport. The battery can also be used as a general power source for small electronic devices, adding a layer of practicality beyond the exoskeleton’s core function.
VIGX frames its work around accessibility rather than industrial automation. “To empower ordinary people,” said founder Bob Yu, explaining why the company chose to focus on exoskeleton robotics. “VIGX is dedicated to expanding the physical limits of humans, enabling deeper outdoor adventures, making running and cycling easier and more enjoyable and allowing people to sustain their outdoor pursuits regardless of age.”
Placed within the wider context of CES, the π6 sits alongside a growing number of portable robots and wearable systems that prioritise convenience, mobility and personal use. By reducing the physical and practical barriers to wearing an exoskeleton, VIGX is testing whether assistive robotics can move beyond niche environments and into everyday life. If that experiment succeeds, wearable robots may become less about dramatic augmentation and more about quiet support — present when needed and easy to put away when not.
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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.