If you look around your environment, you can probably pick off quite a few things that you’ve made, at least if you’ve been at this a while. You probably aren’t reading this from the bottom of a body of water though, which means you lack the incredible confidence of submarine builder [Hank Pronk]. Not only is he building himself a capable-looking diesel-electric submarine over on YouTube, he’s even DIYing CO2 scrubbers for it! Yeah, that’s a man who believes in himself.
Luckily [Hank] is not anywhere near the Caribbean, so needn’t worry about being misidentified as a narco-sub, but he still has to be concerned about his oxygen supply when tooling around beneath the local lakes. Perhaps more important than the oxygen supply in a sub is the build up of CO2. It doesn’t matter how many oxygen tanks you bring down with you if you can’t scrub CO2 out of the air to make room for it. Just like the Apollo missions, he’s using a chemical adsorbent to take carbon dioxide out of the air — and just like Apollo 13, he’s switching from square to round.
Or, rather, from a rather rectangular commercial model to a DIY little round unit. That’s because he doesn’t need the big scrubber in this sub: being diesel-powered, he expects to spend a lot of time at snorkel depth, where both the pilot and the engines can get clean air through the tube. Dives are expected to be short, and in that use case, too big of a CO2 scrubber is really a waste. If for some reason he gets stuck on the bottom, well, the lake isn’t that deep. He can swim to surface, and has a detailed bailout plan. If he wants to stay under overnight to avoid bailing at night, he’s carrying enough extra adsorbent for that.
As physical AI enters our homes, workspaces and public infrastructure, it will have a transformative effect. Autonomous vehicles will become the norm on our streets, factories and warehouses will move to full automation, AI-enabled devices will assist in surgeries and medical procedures, and greater intelligence will be embedded into domestic devices.
Such is the emerging significance of physical AI, Gartner has identified it as a top strategic trend that will shape enterprise priorities over the next five years. There is no doubt the opportunities are great. But are organizations ready to roll out autonomous robots and drones, self-driving vehicles and industrial automation at scale?
Anuj Seth
VP of IoT & Engineering for EMEA & APAC at Cognizant.
Project leaders are finding that the deployment of AI in physical spaces, where they will coexist with humans, is very different from deployment of AI in an abstract cloud computing environment. Physical AI is requiring machines and systems to perceive what’s happening around them, interpret context and act autonomously in the real world.
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For obvious reasons, these deployments must be proven safe and reliable. To successfully achieve this, leaders are required to overcome numerous practical complications, such as the constraints on edge devices, regulatory compliance and environmental considerations.
In addition to this, project leaders also need to convince their senior leadership teams that physical AI can be scaled across operations.
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This will require them to show that the ongoing operational costs are manageable – and that a clear return on investment, be that through improved uptime, energy optimization or workforce efficiency, is evident. If they fail to demonstrate this, projects will never get past the pilot phase.
Embrace AI from the outset
To address these challenges, the first step for leaders is to ensure physical AI solutions and their benefits are factored in at the outset of any project. When organizations fail to include AI at the earliest stage – during the design and development of any product or operational environment – it creates challenges.
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This typically results in fragmentation across hardware, firmware, applications and cloud computing – and results in a build-up of technical debt and diminishing returns. Siloed operational assets also result in disjointed workflows, operational bottlenecks and suboptimal performance.
Where this is the case, we often see organizations struggle to innovate and pivot whenever new commercial opportunities arise, such as through new smart consumer devices, factory robotics or in-vehicle infotainment.
Gartner estimates that the organizations taking a proactive approach in reducing, what it refers to as, “AI debt” will mature up to 500% faster over the next three years.
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Enable edge inference
In contrast to cloud AI deployments, physical AI requires organizations to integrate real-time edge inference with several computing layers. Specific solutions will need to be engineered to compensate for the numerous hard constraints encountered on edge devices, including compute capacity, memory, power consumption, thermal limits and form factor.
These constraints typically force deliberate trade-offs in model size, update frequency, hardware selection and inference strategy. As edge capabilities continue to advance, these constraints can increasingly be addressed. Low power GPUs and specialized AI accelerators are expanding the range of workloads that can be executed locally.
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Techniques such as model compression and quantization also help reduce computational demand while maintaining acceptable performance.
In particularly constrained environments, distributed edge architectures can be used to offload specific tasks to nearby devices. With these advances, what matters less is where intelligence runs, and more how deliberately edge constraints are engineered from the outset.
This will increase reliability, reduce reliance on cloud computing and lower the ongoing operational costs.
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Run simulations
These edge engineering solutions will provide organizations with a proof of concept. But, to enable these to scale, project leaders also need to test scenarios and understand second-order impacts across operations. They will want to do this without disrupting production, compromising safety or committing capital prematurely.
Project leaders can derisk investments and validate their decisions, however, by leveraging advanced simulation platforms, such as NVIDIA’s Omniverse. This enables them to create digital twins of factories, assets and workflows, and allows teams to explore “what-if” scenarios.
Simulations allow teams to assess performance and identify constraints early. In energy intensive environments, for example, teams can assess power usage and sustainability trade-offs. This enables leaders to evaluate costs, right size capital investment, accelerate planning cycles and align stakeholders around a shared view of the future.
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Build confidence
The use of simulations also helps to identify quick wins that will help leaders to demonstrate early success. This will provide crucial evidence that the technology is safe and reliable, but also that it can provide a clear return on investment.
This should act as the first phase of a staged rollout program. With physical AI, it is advisable that organizations take an incremental approach, as it will help to build confidence in the project among the senior leadership team – and remove the hesitancy that can hold projects back and prevent them from scaling.
To further instill confidence, project leaders should simultaneously roll out a structured organizational change management project too. This will prepare stakeholders and the workforce for the impact of physical AI within their operations.
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Lead organizational change
The skill sets required in a physical AI project are different to those needed in a cloud AI deployment. Organizations need deeper expertise in embedded systems, real-time software and lower-level programming languages. As a result, there may be a need to augment workforces and evolve organizational structures.
To encourage acceptance of the technology, a clear communication strategy will also be necessary – one that explains how physical AI will provide value, and how the deployment will impact individual roles and processes. It may also be necessary to provide additional training and ongoing support throughout the roll out process.
Physical AI can no longer be considered a futuristic concept – it’s already transforming the world around us. It’s enabling organizations to innovate, go to market faster and seize commercial opportunities. It is also helping to optimize operational workflows, increase productivity and reduce costs.
If organizations want to take advantage and accelerate adoption, however, they must develop the solutions that work for their specific needs and derisk their deployment strategies. When they do this, organizations typically find they can scale physical AI quickly and reap the benefits sooner.
This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit
South Korean authorities have imposed a record-breaking fine of $624 billion won (over $400 million) on retail giant Coupang after a data breach last year compromised the personal data of more than 34 million customers.
Seoul’s Personal Information Protection Commission issued the maximum penalty on Thursday following discovery of the breach in December 2025. The retail giant, which is headquartered in the U.S. but popular in South Korea and likened to the “Amazon of Asia,” had said the months-long data breach allowed a former employee to obtain names, email and shipping addresses, phone numbers and order histories of about two-thirds of South Korea’s population.
Coupang told BBC News that it plans to challenge the regulator’s decision. The fine represents a rare case of a financial penalty issued against a U.S.-based firm. Korean lawmakers have accused some of their American counterparts of imposing political pressure after reports that U.S. representatives were linking the data breach with U.S.-South Korean bilateral ties in response to the case against Coupang’s executives.
U.S. companies rarely face financial sanctions or criminal prosecution for data breaches as a result of lacking laws and enforcement powers.
Tomb Raider is back. Again. Lara Croft is back. Yet again. This time, her character is positioned between the “Survivor” trilogy of the last decade and her iconic debut in 1996. Yes, 30 years ago.
Legacy of Atlantis is a remake of that very first adventure, centered on Atlantean mythology, tomb raiding and, well, a few dinosaurs. At Summer Game Fest 2026, Crystal Dynamics and Flying Wild Hog shared the first gameplay demo, with Unreal Engine 5 adding vivid detail and lushness to Lara’s travails.
The developers made a clever choice, centering the demo on an early part of the original game. Set in the Peruvian mountainside, my playthrough included a giant cog puzzle I remember from playing the original. There were also several shootouts with a herd of dinosaurs, the same vivid red velociraptor-adjacent creatures from Tomb Raider (1996).
Retreading the original game’s ground gives a clear demonstration of how Legacy of Atlantis will elevate the game from the original, making a relatively insipid cog puzzle (find the giant wheels, bring them together, interrupt the waterfall to make a path) into a more exploratory, exciting experience. Yes, you can swan-dive into the waterfall pool whenever you want.
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Lara can collect and use healing packs between fights, gathering resources from trees and caves, as well as mythical curios and historical objects. Not all the contemporary gaming changes are welcome: I’m not particularly thrilled with the inclusion of collectible hunting. The Assassin’s Creed series has largely moved on and I think a lot of gamers have done the same. Some collectibles, like fangs, can be converted into skill points, meaning I will feel obliged to scour for objects.
Lara’s PDA (love it: that’s some 1996 nonsense) combines encyclopedia entries for everything you find, along with the current task. It also includes a scanner that can be used intermittently to offer some tips on what to do next. I did get lost at times, and that was due to my not paying enough attention. Legacy of Atlantis leans into verticality a lot, and pretty much each time I lost my way, the route forward was either literally above my head (grappling hooks!) or under my feet. (Of course, there’s a cave behind that tiny waterfall.)
A grappling hook and climbing axe round out the equipment loadout, drawing inspiration from more recent Tomb Raider titles. Besides swinging across chasms, the grappling hook can also be used to pull objects towards the player and is crucial to solving the cog puzzle.
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After scaling the mountainside and unlocking a route through the waterfall, the demo jumps a little farther forward, deep into the jungle. Dinosaurs soon surround Lara, and she doesn’t even blink. While I wasn’t able to shoot two targets at once, OG Tomb Raider style, I wouldn’t be surprised if that’s some kind unlockable skill in the full game — skill trees were blocked in this demo.
Crystal Dynamics
While there’s no shared development core, parts of the game reminded me of another recent game with a connection to the Amazon industrial entertainment complex: 007 First Light. It’s not just the detailed environments and quippy British lead but a new skill for Lara. Focus, when pressed during gunfights, slows time, helping you to shoot with more precision or switch to a distant target. Oh, she also does so while doing an aerial (a sort of hands-free cartwheel), reminding me of Max Payne, any of The Matrix’s spin-off games and many others. Thankfully, Lara’s dual pistols have infinite ammo and it was easy enough to down the pack of dinosaurs, though not before they gored me a few times.
Not long after, a T. rex enters the scene and we’re locked into a high-speed set piece as I attempt to escape the dinosaurs without falling to my death. I’m relieved that Legend of Atlantis plays more like the original action-adventure titles, while integrating some of the more advanced game mechanics of the last few games. Lara isn’t invincible, but she’s now made of sterner stuff.
Tomb Raider: Legacy of Atlantis launches on February 12 2027, on PlayStation 5, Xbox Series X/S, Steam and Nintendo Switch 2.
Longtime Slashdot reader MattSparkes shares a report from NewScientist, captioned: “For years we’ve had unconfirmed reports, rumors, hints… now we know.” From the report: Fully autonomous drones with no human oversight have killed soldiers on the battlefield for the first time. This is according to a senior figure in the Ukrainian defense industry, marking a watershed moment in warfare. The one-off test involved 10 AI-controlled “Terminator” drones on the front line of the Ukraine war. Russian soldiers were killed.
“We tried it,” says drone-maker Alexander Kokhanovskyy, who supplied the technology and spoke to New Scientist at a press event hosted by the Ukrainian embassy. “It’s a test. We never implemented it [more widely].” The test took place two years ago and involved quadcopter drones that were programmed to fly towards the front line, cover between 3 and 5 kilometres over around 10 minutes and then engage “Terminator mode,” in which an AI model searches for and intercepts targets. “We just launch it and we know everything will be dead — everything that will be found there in this particular area will be dead,” says Kokhanovskyy. “There is no connection to the drone at all, you cannot see the video, nothing… Everything it sees will be killed.”
With no way to tell what the automated drones had seen or targeted, human-piloted drones were sent into the area after the test to manually check results. Victims included “a couple of soldiers, one truck,” says Kokhanovskyy. While there is no recording of the automated drones attacking these targets, it was concluded that the drones had killed them. Kokhanovskyy says that he was not at the test personally but that it was carried out by an unnamed military unit near the cities of Bakhmut and Chasiv Yar as part of a Ukrainian counteroffensive push. The Ukrainian Ministry of Defence did not respond to questions about the test or the current legal position on the use of fully autonomous weapons.
Late one night the machine made a sound. Its builder checked the logs and found a trace of its inner state. The robot had been wondering when its person would return. It did not want to be alone. That moment sits at the center of a project called GrowBot. The creator, who runs the YouTube channel Art of the Problem, set out to build the simplest possible robot that could learn movement, perception, and even a kind of personality from the ground up. The result cost roughly $80 in parts, ran on a single Raspberry Pi Zero 2, and ended up revealing something unexpected about how fast physical action and slower thought can work together.
The hardware is purposefully kept basic. The Pi is housed in a little red 3D printed body, together with a simple camera module, electronics to track the robot’s tilt and motion, a microphone, a tiny speaker, and an LED ring to offer some basic visual messages. The legs are made up of two smart serial-bus servos powered by a small drone battery via a boost converter: no high-end motors, extra computers, or fancy wiring are necessary. You can literally place this item on a tabletop and it will interact with everything around it.
The builder pioneered simulation by using reinforcement learning to run small neural networks in a digital twin. These little guys learned to stand, walk, twirl, and maintain their balance on their own. Because the training was done in parallel across a huge number of simulated versions of the robot, the entire procedure was quick and cost-effective. Once the policies had been understood in the virtual realm, they were quite simple to transfer to physical hardware. Early tests found that it could rock on a yoga ball and keep its equilibrium when poked, which was remarkable given the simplicity of the technology.
The next step was to give the robot real decision-making power by employing a vision language model. This type of AI excels at evaluating pictures, reading sensor data, and making sense of it all. Instead of hard-coding each response, the architect simply let the model to read raw data from the camera and motion sensors. It then reported what it saw, set some goals, and started writing little Python scripts to sort things out. These scripts would then use pre-trained motor policies, or combine them with new instructions. It could also detect faces, study how people interacted with the robot, and update its memory banks for each person it met.
Without direct programming, the robot started to develop a personality. One mode uses motion timing, noises, and light patterns to communicate affection, disapproval, or merely purring. It learned to act dead when roughed up, to look for ‘uppies’, and to knock over Jenga towers with some leg swinging added in for fun. When it was playing hide and seek, it would search rooms; in mimic games, it would try to simulate human movements by generating loops to replay sensor patterns; and in between all of this, it would have these ‘dream’ episodes. A more complex language model would then review the day’s memory files, consolidating all repeating events into lessons and removing any contradictory notes. The robot’s stored profiles of its builder and visitors have become more precise over time.
To be honest, things went so well until the smooth physical action became a limitation. The vision language model could take anywhere from 1-4 seconds to evaluate a scene and determine its next step. However, in the real world, bodies must be able to correct for minor weight shifts or tremors in fractions of a second. The high-level model could plan an action, but it lacked the essential quick forward model, which tells a body what will happen if it moves in a certain way in the next instant. That gap changed the smooth motions, making them slow or uneven.
In 2021, I wrote about Fire Emblem for our 20th anniversary GBA story. Over the past five years, I’ve played it from start to finish two times, and can once again confirm that it is my favorite Game Boy Advance game.
I hadn’t even heard about Fire Emblem as a series until I got into Advance Wars, another Intelligent Systems game. From there, I discovered that a whole series of fantasy-inspired games with similar gameplay existed, but had never been translated into English. Thirsty for more, but with a distinct lack of Japanese language skills, I spent a year getting deep into Final Fantasy Tactics, old Shining Force games, Vandal Hearts and basically anything vaguely Fire Emblem-shaped that was available in English. Then, off the back of Advance Wars‘ success, Nintendo decided to release a Fire Emblem game in the west, and simply called it Fire Emblem.
Released as Fire Emblem: The Blazing Blade in Japan, Fire Emblem was technically the second GBA FE title and the seventh overall. The battles were challenging, and its RPG elements drew me in much more than Advance Wars ever did. With a vast story full of twists and turns, and a cast of characters I truly cared about, I was instantly hooked. Which made it all the more tough when I encountered perhaps FE’s most famous mechanic: permadeath. The loss of a character who’s seen you through thick and thin dying a pathetic and meaningless death, all because you left them one square away from safety, is memorable.
Despite a few missteps, over the years Fire Emblem became my favorite series, and I am deeply excited by Fortune’s Weave finally getting a release date. But I still come back to the GBA game to relive that love-at-first-sight moment.
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In 2026, I’m so familiar with the game that it’s very rare for me to lose a party member by accident. Those once-challenging battles are now more of a warm embrace. Unfortunately, playing it has become harder in recent years. Though I still have my original cart, both my Game Boy Advance and my old DS Lite are really worse for wear. I tried to play on the Switch 2’s online library recently, but I think the screen size just isn’t a great match for GBA games.
In that respect, modern retro handhelds have been a godsend. I spent way too much on the Aya Neo Pocket Micro Classic, a machine with the same aspect ratio of the original GBA, and loved my playthrough of Fire Emblem on that. It does feel weird playing it on anything but a Game Boy Advance, though. I’ve been saying this for the best part of a decade at this point, but I do wish Nintendo would take advantage of this deep thirst for its old games and produce a bespoke console similar to the Classic Editions of the SNES and NES.
The number of iPhones stolen in London that have been reactivated by thieves has plummeted in recent weeks, preventing them from being sold and, hopefully, making iPhones less likely to be stolen in the future.
The theft of iPhones has become a real problem for London in recent years. So much so that some thieves have been known to hand back a stolen phone if it turns out not to be an iPhone.
Thieves typically use mopeds to ride up to a victim before snatching their iPhone and riding off. But the thieves don’t want the iPhone itself; they want to sell it on for cash. And that only works if they can unlock and reset it.
But in an interview with the BBC, Metropolitan Police Commissioner Sir Mark Rowley admitted that’s happening less than usual.
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The comment came as Rowley was calling on tech firms to make stolen phones harder to unlock and sell. But he also admitted that Apple appears to have already made a huge dent in the problem with an existing security feature.
Stolen, but not forgotten
While iPhones have supported Stolen Device Protection since 2023, Apple enabled it by default with the iOS 26.4 update in March 2026.
Stolen Device Protection, when enabled, requires biometric authentication when doing a range of things. Vitally for stolen iPhones, those things include turning off Lost Mode as well as erasing its content and settings.
Some security actions even require a delay before they can be enacted, giving the owner of a stolen iPhone the time to mark it as lost using the Find My network.
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This means that a thief cannot reset an iPhone, even if they know your passcode. And that may well have been enough to make iPhones more difficult for thieves to sell on.
Rowley told the BBC Radio 4’s Today program that thieves were using software to “factory reset” devices before selling them on. But he says that Apple has “cracked” the problem with data showing that “the vast majority of phones” stolen in recent weeks have not been reset.
Rowley also added that the Metropolitan Police has entered into an “intelligence sharing agreement” with Apple. It’s hoped this will result in a better understanding of how iPhones are being stolen and sold in London.
China used ChatGPT to generate comments, posts, and cartoons
The content capitalized on issues surrounding data centers and tariffs
The material was shared on social media to exacerbate existing tensions
OpenAI has banned a number of accounts that it says were linked to social media influence campaigns surrounding the growing opposition to data centers and President Trump’s tariffs on foreign imports.
The two campaigns, named “Data Center Bandwagon” and “Tech and Tariffs”, used ChatGPT to generate posts, comments and cartoons intended to sow political division in the US.
China’s intention was to deepen the divide by drumming up online engagement with AI generated posts, OpenAI said, but the campaigns failed to gain any traction.
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China exacerbates existing tensions
The negative effects of data center construction and the additional costs imposed on consumers by tariffs are existing areas of contention within US society, but they weren’t narratives invented by China.
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Instead, according to OpenAI, these campaigns were designed to increase the scale of the issues and broaden their visibility among online groups and on social media sites such as X.
It is the first time that OpenAI models have been used in a Chinese foreign influence campaign, a spokesperson told Axios.
OpenAI said that a Chinese government contractor was responsible for the data center campaign, which shared posts drawing on existing concerns surrounding power grid capacity and electricity prices in areas where data centers were planned or constructed.
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OpenAI’s account of a foreign country using AI to capitalize on political issues adds some limited validity to recent Republican claims that the entire data center opposition movement being a Chinese influence campaign, but does little to address the very real, tangible effects that data center projects are having on local communities in the US.
A group of Republicans recently called upon FBI Director Kash Patel to investigate anti-data center sentiment, alleging that the rising tide of opposition is being fueled by China, as the inclusion of similar phrasing around water usage, energy constraints, transparency surrounding approval, and utility bill use “language too similar to be coincidental”.
Xbox CEO Asha Sharma, roughly 100 days into her tenure, delivered a blunt assessment of Microsoft’s gaming business in a memo to employees Wednesday, saying that heavy spending with thin profit margins and declining revenue “cannot continue.”
The memo, posted publicly on the Xbox blog, came as Bloomberg News reported that the division is planning major job cuts next month, soon after the close of Microsoft’s fiscal year on June 30. Xbox is also planning significant cuts to marketing and other budgets, according to the report.
The exact scale of the layoffs is not yet clear. Microsoft declined to comment. The Verge also reported that Xbox “will be hit with significant layoffs next month,” citing people familiar with the plans.
Sharma’s memo did not mention layoffs but described a business that needs a sweeping reset. She and Xbox content chief Matt Booty, who co-signed the memo, cited rising hardware component costs, an overextended studio system, and aging platform infrastructure among the challenges facing the division.
Xbox will end the fiscal year at about a 3% “accountability margin,” an internal metric Microsoft uses to measure the profitability of the business, according to the memo.
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“Excluding Activision Blizzard King, over the past five years, we have spent over $20 billion on ongoing investments in our content, platform, and hardware subsidy, but our annual revenue has declined nearly half a billion during that time,” Sharma and Booty wrote. “Going forward, this cannot continue.”
Microsoft’s most recent quarterly filing illustrates the challenge. Gaming revenue fell 7% to $5.3 billion in the quarter ended March 31, with Xbox hardware revenue down 33% on lower console sales, and Xbox content and services revenue down 5%.
The memo follows Sunday’s Xbox Games Showcase, where Sharma reversed course on the company’s multiplatform strategy, announcing that Gears of War: E-Day and Clockwork Revolution will be Xbox console exclusives. Bloomberg reported Wednesday that a PlayStation 5 version of the new Gears of War game had been in development, and was canceled, before the announcement.
Sharma took over in February from Phil Spencer, the longtime Xbox leader who announced his retirement after 38 years at Microsoft. A former Instacart COO and Meta product executive, she previously ran Microsoft’s CoreAI product organization.
Samsung’s next rugged smartwatch could be getting one of the biggest battery upgrades we’ve seen on a Wear OS device.
According to a new report, the Galaxy Watch Ultra 2 will feature a battery with a rated capacity of 784mAh. This would likely be marketed as an 800mAh cell when the watch launches. If accurate, that would represent a jump of more than 30% over the current Galaxy Watch Ultra’s already sizeable 590mAh battery.
Battery life has become one of the biggest battlegrounds for smartwatch makers. This is especially true in the Wear OS world, where many devices still struggle to make it comfortably through multiple days of use. That’s what makes this rumoured upgrade stand out.
For comparison, reports suggest Samsung will equip the upcoming 40mm Galaxy Watch 9 with a 382mAh battery. Meanwhile, Google’s latest Pixel Watch 4 models pack 325mAh and 455mAh cells, depending on size. On paper at least, the Galaxy Watch Ultra 2 would offer almost double the battery capacity of many mainstream Wear OS watches.
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Of course, battery size doesn’t automatically translate into battery life. Factors such as display efficiency, software optimisation and processor performance all play a major role. However, the original Galaxy Watch Ultra already ranks among the better-performing Wear OS watches for endurance. As a result, a larger battery could make its successor even more appealing for users who prioritise longevity over slim designs.
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The report also suggests Samsung will pair the new watch with Qualcomm’s Snapdragon Wear Elite platform. This platform will power several upcoming flagship smartwatches. If the chip delivers meaningful efficiency gains alongside the larger battery, Samsung could be looking at a substantial real-world improvement.
It’s also shaping up to be the first major refresh of the Ultra line since the original model launched. While last year’s update focused largely on refinements, the Galaxy Watch Ultra 2 is beginning to look like a more significant upgrade. This could be especially true if battery life becomes its headline feature.
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Samsung is widely expected to unveil the Galaxy Watch Ultra 2 in July alongside the Galaxy Z Fold 8.
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