Garmin smartwatches, known for its high-quality GPS, fitness stats, durability, and detailed workout features, has released its new Fenix 8 series in India. The smartwatch has already garnered an overwhelming response from the global market.

The Fenix 8 series is available in three sizes – 43mm, 47mm, and 51mm. While all come in the AMOLED version, the solar-charging models are available only in the 47mm and 51mm variants. The watch is topped with a scratch-resistant sapphire lens and features a titanium bezel. The additional features of the multi-sport smartwatch include a built-in speaker and mic for voice commands and phone calls. However, the highlight of the new launches is the fitness and workout features that allow for exhaustive performance tracking.

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There are advanced strength training plans for sport-specific workout activity trackers; advanced mapping with TopoActive maps with relief shading and built-in maps for golf courses and ski resorts worldwide; dynamic round trip routing to help wearers set how far they want to go and for guiding them back on time; ski difficulty tracking to let the user know how much time they are spending on different difficulties throughout the day; and dive capability with a 40-metre dive rating and leak-proof buttons. The ‘Garmin share’ feature allows the wearer to easily share saved locations, courses, and workouts with friends, while the Garmin messenger app helps one communicate directly via their smartwatch. Additionally, the brand has also announced a personalised application, designed specifically for coaches and athletes to map their performance.

“The Fenix 8 Series is perfect for individuals looking to elevate their performance or maintain a healthy lifestyle. Whether you are an experienced athlete or someone who enjoys staying active, this new series offers advanced features and extended battery life for outstanding versatility,” says, Tim Spurling, General Manager, Emerging Markets CAMEA, Garmin.

Along with these, the watch is packed with a built-in LED flashlight, and 24/7 health and wellness trackers, which include wrist-based heart rate, advanced sleep monitoring, respiration tracking, pulse, and more. There is music control, a connect IQ store for adding and changing watch faces and data field, endurance score, body’s energy level tracker, and much more. The AMOLED display model runs up to 29 days, while the solar charging variants have a life of up to 48 days. The watches start at Rs. 86,990.

Qualcomm made big announcement this week. The company just unveiled its new Snapdragon 8 Elite chip, and even if you don’t keep a particularly close eye on the smartphone chipset world, it’s something that’s worth getting excited about. Qualcomm is promising substantial performance and efficiency improvements over last year’s already excellent Snapdragon 8 Gen 3, which is great news for next year’s slate of flagship Android phones.

But there’s more to the Snapdragon 8 Elite than it being more powerful and more efficient. It also has the potential to substantially change the way we use the cameras on our phones. How so? I talked to Judd Heape, VP of product management at Qualcomm, to better understand it myself, and I came away significantly more excited about the immediate (and faraway) future of our smartphone cameras.

Behind-the-scenes camera upgrades that matter

A big part of the Snapdragon 8 Elite is what Qualcomm calls its “AI ISP.” An ISP (image signal processor) is a standard component of every smartphone chip, including Snapdragon ones, and is what facilities image processing on your phone’s camera. For the Snapdragon 8 Elite, the AI ISP has a much tighter connection to the NPU (neural processing unit) than any other Snapdragon chip before it. That may sound like a lot of technical jargon, but it essentially means that critical camera features should run much better than before.

What kind of camera features? One of the most exciting is how the AI ISP should improve auto white balance. Why is that a big deal? “One of the things that cameras get wrong a lot based upon very complex lighting, like lighting an interior versus exterior at the same time, if you’re outdoors in a parking lot and the lights are very orange … that sort of thing,” Heape said. “Your skin tone can get really messed up really easily because of that, and that’s a failure of auto white balance.”

Because this new ISP has a tighter connection to the Snapdragon 8 Elite’s NPU, it can “generate proper skin tone no matter what the lighting condition is.” The really exciting thing is that these auto white balance improvements don’t just happen after you’ve taken a photo. You see those enhancements in real time through the viewfinder, so the image you see as you’re taking a picture is what you’ll get.

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Another promising change is that the new ISP consumes less power. “The power consumption also of the ISP has gone down due to the new architecture,” Heape said. “So, in really interesting use cases, like 4K 60 fps HDR video recording, the ISP consumes 25% less power … which means that you’ll have less thermal problems when you’re trying to shoot videos.” Speaking of video, the new ISP also improves Qualcomm’s “temporal noise filters.” Those filters look at more video frames than before so “the video that you’ll shoot is a lot cleaner than it used to be. It was good before but it’s even better now.”

Are these flashy AI camera features like the Google Pixel 9’s Add Me mode or the numerous camera/photo editing tools in Galaxy AI? No. But are they ones that could legitimately result in better photos and videos for any phone with a Snapdragon 8 Elite? Absolutely. And that’s the type of AI camera enhancements I want to see more of.

What does the future of smartphone cameras look like?

Beyond immediate enhancements coming with the Snapdragon 8 Elite, Heape also shared a few insights about what the greater future of smartphone cameras may look like — and what he, as someone who works closely on this stuff at Qualcomm — wants to see more of.

While talking about the auto white balance improvements and seeing those enhancements through the viewfinder in real time, Heape admitted that “the industry needs to drive toward that. What you see is what you get is really important. It gives the photographer confidence … OEMs need to concentrate on that.”

Heape was also asked about his “dream application” for Qualcomm’s ISP advancements and what he was most excited to see smartphone companies do with it in the next few years — and I thought his answer was fascinating. As he explained, Heape is interested in “reducing the cost and complexity of the camera system.”

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“I think we can get away with two cameras instead of three in some cases … which reduces the processing and power … plus using AI for super resolution and using AI to augment capabilities in lowlight.” When asked to look even further ahead about how he’d like to see AI used to further improve the smartphone camera experience compared to what we have today, Heape said he wants to see a world where your camera gets to know you.

“Your camera getting to know you, and know what you like, and know the edits you tend to make and the shots you like to take … basically training your camera. Learning what kind of shots you like and the composition and the camera getting to know you over time and then making those adjustments for you the more images you shoot. I think that’s kind of where we need to get to next … kind of like having the Copilot PC, if you will, for your camera.”

As someone who’s felt pretty unimpressed with existing AI camera tools, I really hope Heape’s ideal camera future is the one we’re headed toward — one where AI is working in the background and giving you better photos and videos without you having to think about it. I don’t particularly care about (or want) AI features that alter my photos into something they aren’t. I want my phone to take the best picture possible without me needing to think about it too much, and talking with Heape, that sounds like the future he wants to see, too.

I think we’re heading in the right direction

Ever since smartphone brands and chip manufacturers started going all in on AI over the last couple of years, I’ve found it difficult to get truly excited about almost any of it. We’ve seen cool tech demos and a few cool features here and there, but nothing that I’ve felt has genuinely changed how we use our phones — particularly when it comes to the camera.

While it remains to be seen just how well the Snapdragon 8 Elite and its new ISP actually perform in the real world — and whether the camera future Heape describes is the one we’re actually headed toward — I will admit that I’m genuinely curious and hopeful about all of it. I firmly believe that the best use of AI is having it work in the background and allowing you to use your phone as you normally would but making it better. Give me better white balance and video recording any day of the week over wonky image generator tools. It really feels like that’s the direction Qualcomm is headed, and if that’s the future we can look forward to with smartphone cameras, count me in.

The Xiaomi 15 Ultra has just surfaced, and it has an odd-looking camera layout. These images comes from SmartPrix, a site that partnered with Yogesh Brar, a tipster.

Do note that the tipster in question here has a mixed track record, but this is not the first time this design has appeared. It surfaced earlier this month in a sketch form, and this is only its render form.

The Xiaomi 15 Ultra has just appeared with an odd-looking camera layout, but these are not official renders

It’s obvious that the renders included here have been created by a third-party, they’re not official leaks. So it’s possible they’re simply based on the sketch that surfaced earlier this month.

In any case, you will notice that the phone has rounded corners and a centered display camera hole. The bezels are very thin, and even though they don’t look uniform in this render, chances are that they will be.

All the physical buttons sit on the right-hand side of the phone. We don’t see its frame on the side, but it’ll likely be mostly flat. On the back, you’ll spot a huge camera oreo, which takes up a huge chunk of the phone’s upper side.

Inside that camera oreo, four cameras are located. The main one sits at the bottom, and it’s centered between two other shooters. The periscope telephoto camera is included in the top-right corner.

Leica will once again be a part of the package

The Leica logo is also visible on the inside of this camera oreo, and the same goes for an LED flash. The camera island shown here will likely protrude quite a bit on the back of the device. Xiaomi will use larger camera sensors.

The source pictured this phone in black and white colors here, with a vegan leather backplate., It’s quite possible that the phone will arrive in those colors, with that material on the back. Just note that these are not leaked renders, so these are not color leaks either. The real thing will likely look at least a bit different.

Unlike the Xiaomi 15 and Xiaomi 15 Pro, the Xiaomi 15 Ultra is not expected to arrive this month. Those two phones are coming on October 29, while the Xiaomi 15 Ultra will follow next year.

The popcorn bucket wars just became literal with Cinemark’s latest entry for Gladiator II. The theater chain’s new entry is not only shaped like the Roman colosseum, it plays a cutesy augmented reality gladiator battle when you point your smartphone at QR code on the bottom (AR-ENA, get it?). The butter on the popcorn is Cinemark’s tagline, claiming “you can eat war.”

In fact, all of the ad copy is brilliantly cheesy: “Every kernel of strength, every ounce of honor, is for the glory of Rome. As you preside over this gladiator arena, you can… eat war. Finish the popcorn and unleash the battle within. You will be entertained.” Being intoned in the Honest Trailer style takes it up an extra notch.

It’s the latest popcorn bucket movie merch, following high-profile entries from Dune and Deadpool. We’ve also seen entries for Ghostbusters: Frozen Empire, Beetlejuice Beetlejuice and others that didn’t quite capture the same zeitgeist.

Sure, you might need to wipe off some popcorn grease to read the Cinemark bucket’s QR code, and the AR animation of two fighting gladiators is reminiscent of a PlayStation 2 render. Still, neither the Dune nor Wolverine buckets boast any interactive features, so the Gladiator II bucket has them beat there — and it’s a smart way to rope in the tech press.

Cinemark’s vessel is also plausibly shaped like a popcorn bucket with its colosseum form. The same can’t be said for Dune‘s sandworm-shaped bucket or Deadpool’s Wolverine head bucket (Dune director Denis Villeneuve called the latter “horrific” and he’s right). If you’re looking to expand your collection, the Gladiator II popcorn bucket will arrive “soon” and the movie itself hits theaters on November 22.

A pair of researchers at OpenAI has published a paper describing a new type of model — specifically, a new type of continuous-time consistency model (sCM) — that increases the speed at which multimedia including images, video, and audio can be generated by AI by 50 times compared to traditional diffusion models, generating images in nearly a 10th of a second compared to more than 5 seconds for regular diffusion.

With the introduction of sCM, OpenAI has managed to achieve comparable sample quality with only two sampling steps, offering a solution that accelerates the generative process without compromising on quality.

Described in the pre-peer reviewed paper published on arXiv.org and blog post released today, authored by Cheng Lu and Yang Song, the innovation enables these models to generate high-quality samples in just two steps—significantly faster than previous diffusion-based models that require hundreds of steps.

Song was also a leading author on a 2023 paper from OpenAI researchers including former chief scientist Ilya Sutskever that coined the idea of “consistency models,” as having “points on the same trajectory map to the same initial point.”

While diffusion models have delivered outstanding results in producing realistic images, 3D models, audio, and video, their inefficiency in sampling—often requiring dozens to hundreds of sequential steps—has made them less suitable for real-time applications.

Theoretically, the technology could provide the basis for a near-realtime AI image generation model from OpenAI. As fellow VentureBeat reporter Sean Michael Kerner mused in our internal Slack channels, “can DALL-E 4 be far behind?”

Faster sampling while retaining high quality

In traditional diffusion models, a large number of denoising steps are needed to create a sample, which contributes to their slow speed.

In contrast, sCM converts noise into high-quality samples directly within one or two steps, cutting down on the computational cost and time.

OpenAI’s largest sCM model, which boasts 1.5 billion parameters, can generate a sample in just 0.11 seconds on a single A100 GPU.

This results in a 50x speed-up in wall-clock time compared to diffusion models, making real-time generative AI applications much more feasible.

Reaching diffusion-model quality with far less computational resources

The team behind sCM trained a continuous-time consistency model on ImageNet 512×512, scaling up to 1.5 billion parameters.

Even at this scale, the model maintains a sample quality that rivals the best diffusion models, achieving a Fréchet Inception Distance (FID) score of 1.88 on ImageNet 512×512.

This brings the sample quality within 10% of diffusion models, which require significantly more computational effort to achieve similar results.

Benchmarks reveal strong performance

OpenAI’s new approach has undergone extensive benchmarking against other state-of-the-art generative models.

By measuring both the sample quality using FID scores and the effective sampling compute, the research demonstrates that sCM provides top-tier results with significantly less computational overhead.

While previous fast-sampling methods have struggled with reduced sample quality or complex training setups, sCM manages to overcome these challenges, offering both speed and high fidelity.

The success of sCM is also attributed to its ability to scale proportionally with the teacher diffusion model from which it distills knowledge.

As both the sCM and the teacher diffusion model grow in size, the gap in sample quality narrows further, and increasing the number of sampling steps in sCM reduces the quality difference even more.

Applications and future uses

The fast sampling and scalability of sCM models open new possibilities for real-time generative AI across multiple domains.

From image generation to audio and video synthesis, sCM provides a practical solution for applications that demand rapid, high-quality output.

Additionally, OpenAI’s research hints at the potential for further system optimization that could accelerate performance even more, tailoring these models to the specific needs of various industries.

Lithuania’s Vinted has secured a new valuation of €5 billion (around $5.4 billion at current exchange rates), after the second-hand fashion marketplace closed a secondary share sale worth €340 million ($367 million).

The transaction was led by private equity giant TPG, with other new participants including Baillie Gifford, FJ Labs, Hedosophia, Invus Opportunities, Manhattan Venture Partners, and Moore Strategic Ventures. It’s unclear how much Vinted’s existing investors cashed out, but the company says that all its existing institutional investors — which include Accel, EQT, Insight Partners, and Lightspeed Venture Partners — have retained at least some stake.

It’s proving to be a bumper year for secondary market transactions, particularly in Europe, as scale-ups seek to unlock liquidity for their employees and VCs in a decidedly tepid IPO market. In the past few months alone, we’ve seen neobanks Revolut and Monzo pursue secondary market routes, attaining lofty valuations off the back of strong user growth and profitability.

In the U.S., meanwhile, fintech giant Stripe followed a similar path to unlock liquidity, reaching a private valuation of $65 billion back in February as it continues to delay a long-rumored IPO. This figure later jumped to $70 billion as Sequoia sought a larger stake from existing investors.

Vinted CEO Thomas Plantenga (pictured above) noted that the sale “rewards our employees for their dedication in making Vinted a success.” The company was valued at €3.5 billion ($3.8 billion) pre-money for its previous €250 million Series F fundraise back in 2021. Since then, it has gone from strength to strength, reporting record revenue growth of 61% in 2023 compared to the previous year and reaching profitability for the first time.

At the same time, Vinted has expanded geographically and is also extending beyond its core fashion roots into the electronics realm — a growth trajectory that prompted marketplace stalwart eBay to respond by removing seller fees in key European markets.