I took this Oppo smartwatch swimming, and it tracked everything except my excuses


I recently covered a report suggesting that people who use fitness trackers and smartphone apps tend to stay more physically active. While my experience sits far outside the scope of that study that involved cardiovascular disease, I now understand how a wearable can turn an ordinary workout into something you want to repeat.

I have been trying to get back into swimming, and the Oppo Watch X3 arrived at the perfect time.

During a recent session, I took it into a 50-meter pool and swam 1,100 meters. The watch tracked the pool lengths, distance, pace, heart rate, strokes, rest periods, and even the different swimming styles I switched between. My swimming still needs plenty of work, and seeing the effort I put in translating to progress, I could understand what sold it to me.

I never worried about the watch

Taking an expensive smartwatch into a pool still requires a small leap of faith. Water resistance ratings don’t matter as your wrist disappears beneath the surface, and yet, the Watch X3 kept me reassured. From random bumps to going 6 feet under the water, the smartwatch blends ruggedness with a sleek look. Its case and bezel use titanium alloy, and the watch carries IP68, IP69, and 5ATM, and MIL-STD-810H durability ratings.

The 5ATM rating is the important one here, since it certifies resistance to static water pressure equivalent to 50 meters and makes the watch suitable for pool swimming. So apart from the first few lengths, I never found myself checking for water damage.

It kept track of far more than distance

The Watch X3 can automatically recognize swimming, although I manually started the workout as soon as I entered the pool. The setup asked for the pool length, so I selected 50 meters and got moving. By the end, the watch had logged 1,100 meters across 22 lengths. It lined up with the pool size and the distance I knew I had covered, which gave me confidence in the basic tracking.

That’s not all, the Oppo Watch X3 recorded a reported average pace of 1 minute and 53 seconds per 100 meters, 581 strokes, an average SWOLF score of 83, and heart-rate data throughout the session. It also identified when I moved between breaststroke, backstroke, and freestyle. Stroke recognition was one of the biggest surprises. I expected reasonable distance tracking from a modern smartwatch. Watching the app break the workout down by swimming style made the result far more useful, especially when I could compare how long each length took.

I would need a chest strap, manual stroke count, and a second reference device before making any scientific accuracy claims about the heart-rate and stroke data. From a practical user perspective, the information matched the structure of my swim closely enough to be genuinely helpful.

It even caught my conversation break

At one point, I started talking to a stranger at the pool. A quick chat stretched into several minutes, as these things tend to do. When the rest period approached five minutes, the watch paused the workout. That kept the session clear from the actual swimming and extended breaks I took in between the sessions.

Once I got moving again, the tracking continued without requiring me to rebuild the workout from scratch. The watch also showed useful information while I was in the water. Oppo advertises Splash Touch for operating the display with wet fingers, and the touchscreen remained usable in damp conditions. But the watch does lock the touch input when you start the swimming session. Though you can navigate using the crown, holding the second button for two seconds takes you out of the session.

Being able to keep track your activity in real-time motivated me more than I thought it would. Just a quick glance was enough to see the information I cared about, never requiring much interaction. I could check my distance, number of laps I’ve done, my pace, and even the duration of the activity and heart rate.

A color-coded heart-rate indicator also divided my effort into zones such as warm-up, fat burning, endurance, anaerobic, and threshold. I was hardly conducting a professional training session, but the visual feedback made it easy to see when I was pushing harder. The display stayed readable under strong poolside sunlight too, which matters when water, reflections, and a bright sky are all competing with a relatively small watch screen.

The software stayed out of my way

The Snapdragon W5 platform inside the Watch X3 is no longer the newest wearable hardware around. That never became an issue during my session. Starting the workout, entering the pool size, switching between data screens, and reviewing the results remained smooth. Afterwards, the OHealth app presented the session in a clear summary with distance, duration, pace, calories, and a bunch of other things.

Fitness tracking becomes the priority, rather than having you fight the menu. I have noticed similar consistency during walks. The step count has usually landed within one or two steps of the number I counted manually during shorter tests. Step and swim tracking are hardly exclusive to the Watch X3, but the accuracy and convenience were easily the highlight.

I finally understand the motivation

A fitness tracker cannot swim the lengths for me, improve my technique, or drag me back to the pool next week. What it can do is make progress visible. Without the Watch X3, I would have remembered the session as a reasonably long swim where I switched strokes and took a lengthy break to talk to someone. With the data, I knew a lot more.

Those numbers give me something to improve during the next session. That’s when I thought about that research again. Wearables can create a simple feedback loop. One where I complete an activity, see the result, and return with a new goal every day. My single pool session proves nothing about long-term health outcomes, though it gave me a reason to keep swimming.



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Meta stripped NameTag facial recognition code from its AI app one day after WIRED exposed it on 50 million phones. Meta says no decision has been made.

Meta removed nearly all traces of an unreleased facial recognition system from its smart glasses companion app on Friday, one day after WIRED reported that the software had been quietly embedded in an app installed on more than 50 million phones. The feature, which Meta internally called NameTag, was designed to convert faces captured by the company’s Ray-Ban smart glasses into unique biometric signatures and compare them against a database stored on the user’s device. WIRED also found that faces the system failed to recognise were cropped, indexed, and stored locally for future processing.

Andy Stone, Meta’s vice president of communications, told WIRED on Monday that the feature is “purely exploratory,” adding that no final decision has been made on what to do with it. That characterisation sits uneasily with the evidence WIRED documented. The version of Meta AI published the day of WIRED’s Thursday report contained several code libraries explicitly named for face recognition, a process for running the NameTag recognition pipeline, and a “Person recognised” alert the app would have shown if someone were identified.

Friday’s release stripped all of it out, along with a folder where the app would have stored the cropped images and biometric signatures of unrecognised faces. Meta did not answer WIRED’s questions about why the code was removed or whether the changes were planned before the story was published. A few fragments remain in the latest version, including an internal debug menu label and a dormant link meant to open a recognised person’s profile, pointing to parts of the system that are no longer there.

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The gap between Meta’s public statements and the code WIRED found is the central tension. Before the Thursday report, Stone dismissed the findings by writing that the company could not answer questions about how the system would work because “the feature does not exist.” Andrew Bosworth, Meta’s chief technology officer, called the reporting “incredibly misleading” and “absolutely dishonest.” Yet the code was functional enough to include three AI models, one to detect faces, another to crop them, and a third to encode them as biometric data, all embedded in the companion app for a product already at the centre of a mounting privacy crisis.

Meta declined to answer ten questions WIRED posed before publishing, including whether it had already created the database of face profiles NameTag uses, how long the app retains photographs and biometric data of unrecognised people, and whether that data would ever be sent back to Meta’s servers. The company also did not respond to questions about whether it was building NameTag for blind or low-vision users, or to criticism from privacy advocates who warned the system could let stalkers and abusers identify strangers in public.

NameTag first surfaced in February, when The New York Times, citing internal Meta documents, reported that the company was developing face recognition for its smart glasses and considering a launch as early as this year. One internal memo reportedly described releasing the feature during a “dynamic political environment” when privacy and civil liberties advocates would be distracted by other concerns. WIRED subsequently found that much of NameTag’s machinery had been built into the Meta AI app as early as January, months before any public acknowledgement, adding another layer to the company’s pattern of shipping first and disclosing later when it comes to its smart glasses.

Kade Crockford, director of the technology for liberty programme at the American Civil Liberties Union of Massachusetts, said the removal does not undo the original decision to ship the code and pointed to it as evidence that consumer privacy needs stronger legal protection than Congress has been willing to provide. The Massachusetts House of Representatives last week unanimously passed a consumer privacy bill that, if enacted as written, would impose strong enforcement provisions including a private right of action allowing aggrieved users to sue. “State lawmakers need to do their job and step up to protect consumer privacy,” Crockford said.

Meta’s sneaky tactics in slipping the face-recognition code into its smart glasses show exactly why data privacy bills need the teeth of strong enforcement,” Crockford added. “Companies like Meta prioritise their bottom line, so lawmakers need to speak in the only language its C-suite understands.” Whether a code removal prompted by investigative reporting constitutes a victory or merely a tactical retreat depends on what Meta does next, and on whether the regulatory pressure building on both sides of the Atlantic produces enforceable consequences before the feature quietly returns under a different name.



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