I opened DaVinci Resolve and started editing some 4K footage and everything felt buttery smooth, but more important is the fact that thanks to iPadOS 26, you’re able to complete rendering tasks in the background without needing to stay on the app. I hit the export and render button, swapped to another app, and … well, turns out DaVinci Resolve doesn’t support this new feature just yet, so I had to keep the app open for the render to complete. You shouldn’t have an issue on Final Cut Pro, though.

The most professional task I typically use with my iPad is editing RAW images in Adobe Lightroom, and, unsurprisingly, the M5 performed its duties with ease, even with my liberal use of Adobe’s AI-erase tool. However, I also didn’t really have much issue with this on the “weaker” iPad Air. What I find annoying is the fact that this powerful machine still only comes with one USB-C port. I can’t plug it into my camera and edit photos and charge the tablet at the same time; you need a USB hub.

The iPad Pro is for a very specific type of person, and you probably know who you are. If you’re mostly editing photos and typing up documents like me, the iPad Air is more than sufficient. But if you’re regularly in apps like Final Cut Pro or generating all sorts of weird AI images, you may like the extra power the M5 iPad Pro provides—though you can certainly get by with the older M4 model and maybe save some cash.

But unlike the iPad Air, which is just affordable enough to exist as a nice complement to a MacBook for days you don’t want the bulk of a laptop, the Pro feels more like a choice you have to make between clamshell and slate because of its high price. At present, I’d probably pick up the new M5 MacBook Pro instead, but with more desktop apps coming to iPad, I don’t think you’ll have to wait too long until the iPad Pro finally becomes the touchscreen Mac of your dreams.

Researchers from the James Watt School of Engineering in Glasgow are claiming to have constructed a new development in affordable, open-source mobile networks that enables near-real-time control of robotic arms. The technology could help doctors work on patients in remote locations in the years to come.

The first demonstration of the medical innovation has seen the research team use the system to perform mock dental exams on a pair of dentures, highlighting its potential for use in medical procedures.

The system is based on off-the-shelf hardware that has been used to build a 4G LTE mobile network which connects a haptic controller to a robot arm, with the network allowing users to direct the arm’s movements with very low latency, enabling a high level of control.

The research team built their framework using the Open Radio Access Network (O-RAN) framework, which uses open-source software to control mobile network hardware. They repurposed a USB network dongle, more commonly used for consumer mobile internet, to create stable connections between the haptic input device, the robotic arm and a computer configured to act as an intelligent base station.

The system’s signal quality, data rates and latency were monitored and fine-tuned using specialised xApps software.

Its mobile dongle also helped the team create a network that drew considerably less power than comparable connections using the software-defined radio (SDR) more commonly used in similar tasks. The system used 4.5 watts, a 90% reduction on the 45 watts required by traditional SDRs to perform the same activities.

From a performance basis during lab tests, the researchers enabled communications between the base station, the controller and the robotic arm with a bandwidth of 10Mbps. They said that such a connection allowed them to control the arm to simulate a dental exam on dentures with less than a second of latency and minimal signal loss.

The James Watt School of Engineering is part of the University of Glasgow, which was the first institution in the UK to confer degrees in engineering, and established the first chair of engineering in the UK in 1840. Its research environment includes coverage of a broad range of engineering subjects, as well as the interfaces with biology, chemistry, computer science, medicine and physics. 

The college claims its research and teaching is “at the forefront of discovery, creation and practice that is internationally leading in education, innovation and new capability”.

Commenting on the project and its aims in a paper outlining the research, Saber Hassouna of the James Watt School of Engineering said: “The O-RAN framework holds a great deal of potential for enabling intelligent, data-driven, programmable and virtualised networks, but a significant amount of work remains to be done to demonstrate that potential being achieved in the real world, beyond theoretical modelling.

“The testbed we’ve developed here using commercially available hardware shows that O-RAN can be used to enable excellent performance in robotic teleoperation, which is a complex task. For applications like dental procedures, the robotic arm must move very smoothly, which requires high data throughput and low latency, both of which we’ve been able to achieve for the first time with O-RAN.”

Qammer Abbasi, head of the University of Glasgow’s communications, sensing and imaging hub, added: “This is a very encouraging demonstration of the potential of O-RAN to enable fine-grained, close-to-real-time control of a robotic arm. [This] showcases the performance we’ve been able to deliver in a single room with a direct line of sight between the base station and the arm, and we’re currently working on developing the system further to ensure it can deliver the same level of performance at greater distances.

“Ultimately, this could be a step towards creating reliable, affordable methods of performing complex tasks remotely, opening up new applications in medicine, automation, industry and beyond.”

The research was supported by funding from the Communications Hub for Empowering Distributed Cloud Computing Applications and Research and the Engineering and Physical Sciences Research Council.

Easter Island statues, traditionally known as moai on the remote island of Rapa Nui in the South Pacific, are some of the most impressive artifacts of ancient Polynesian civilization. How the statues were transported has long remained a conundrum, because they can weigh up to several tons yet are scattered throughout the island. Various theories have been proposed, including that they were dragged on wooden sleds or rolled along the ground, but no supportive evidence has backed those claims.

In 2012, a US research team succeeded in propping up a 4.35-ton replica of a moai statue and making it “walk.” The technique, in which two teams using ropes tugged the statue in opposite directions to teeter it forward while a third team ensured it wouldn’t topple over, challenged the conventional theories that moai were moved in a horizontal position.

The question then is how much effort it would have taken to move much larger moai. “Once the moai are in motion, it’s not at all difficult,” explained Carl Lipo, an anthropologist at Binghamton University.

Lipo and his team systematically surveyed 962 moai statues on Easter Island, focusing primarily on 62 found along ancient roads. They recently published a paper providing strong evidence that moai were transported in an upright position.

The team also succeeded in moving an exact replica of roadside moai 100 meters in 40 minutes with only 18 people, a far more efficient result than those of previous experiments.

Rules of the Road

The study discovered that moai statues positioned along Rapa Nui’s roads have common characteristics. The broad D-shaped base and forward leaning design of the statues optimized the moai for “walking,” even as they increased in size. In fact, moai abandoned by the side of the road were found to have imbalanced centers of gravity and show signs of toppling over during transport.

This hypothesis is also supported by the ancient roads themselves, which are approximately 4.5 meters wide and have slightly concave cross-sections. Researchers believe these were ideal conditions to aid in stabilizing the moai as they were walked.

A statistical analysis of the distribution of moai showed 51.6 percent were concentrated within 2 km of the quarry where they originated, demonstrating an exponential decay pattern associated with mechanical failure rather than deliberate ceremonial placement. It’s likely these statues were damaged or fell over during transport and left where they lay.