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Two politically pointed statues have mysteriously appeared in the nation’s capital in the leadup to the election: a pile of poop on the former House speaker's desk and a hand holding a tiki torch.

(Image credit: Saul Loeb)

Webflow is growing increasingly popular among cybercriminals phishing for cryptocurrency wallet information, login credentials, and more, experts have warned.

A report from Netskope Threat Labs claims that between April and September 2024, it observed a ten-fold increase in traffic to phishing pages created in Webflow.

Webflow is a website builder design and development platform that allows users to visually build responsive websites without coding, while also offering hosting and content management features.

Smash and grab

The goal of the campaign is, first and foremost, to obtain cryptocurrency wallet information. By tricking victims into sharing seed phrases and login credentials for Coinbase, MetaMask, Phantom, Trezor, or Bitbuy, the crooks can gain full control over the wallets and drain them of any funds, or NFTs.

Besides crypto wallets, the miscreants were also hunting for credentials for multiple company webmail platforms, as well as Microsoft 365 login credentials.

In total, more than 120 organizations worldwide have been targeted, with the majority being located in North America, and Asia. Usually, the crooks were going for organizations in financial services, banking, and technology.

“Attackers abuse Webflow in two ways,” Netskope’s researchers claim. “Creating standalone phishing pages and using Webflow pages to redirect victims to phishing pages hosted elsewhere.” The former is more stealth-oriented, since it contains no phishing lines of code, and thus cannot be spotted by usual security scanners. The latter, on the other hand, provides more flexibility and allows for more complex attacks.

Webflow also provided custom publicly accessible subdomains without additional cost, which the crooks happily used.

What makes the phishing sites easy to spot is the way they mimic legitimate pages. Crooks would simply grab a full-screen screenshot of the legitimate app’s homepage, and use that on their own site. Some pages simply redirected people from this image to the actual phishing page hosted elsewhere.

Therefore, if you see that a website’s homepage is not interactive at all, and behaves as a single image, be careful - you’re probably being targeted.

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Rumors surrounding a potential rebrand for Samsung’s Galaxy S series smartphones have been swirling for some time now, and while we expect the upcoming Samsung Galaxy S25 line to stick with tradition, more evidence is mounting that future Galaxy phones could adopt an entirely new naming scheme.

According to leaker @Jukanlosreve on X, Samsung is “studying the possibility of creating a new brand to separate the premium segment from the Galaxy brand.” @Jukanlosreve cites “Korean media reports” as their source, and while we haven’t been able to track down those reports ourselves, the tipster does have a decent track record with Samsung-related mobile leaks, so we’re inclined to trust their judgment.

Previous rumors on this topic had suggested that Samsung might resurrect the Note naming scheme for the Samsung Galaxy S25 Ultra (the last Note launched in 2020), with that phone being called the Samsung Galaxy Note 25, but recent Galaxy S25 Ultra renders hint that Samsung will instead retain the Ultra moniker for at least one more year.

Just in: According to reports from Korean media, Samsung is studying the possibility of creating a new brand to separate the premium segment from the Galaxy brand.October 29, 2024

Interestingly, @Jukanlosreve’s latest X post makes no mention of the Note name. Rather, they reference the supposed creation of an entirely “new brand” for the best Samsung phones, so perhaps we’ll see Samsung finally adopt the ‘Pro’ moniker, bringing its smartphones in line with premium models from the likes of Apple and Google (the iPhone 16 Pro and Google Pixel 9 Pro, for instance).

Another model on the chopping block?

The Galaxy S24 could be among the last of its kind (Image credit: Philip Berne / Future)

2026 could be a big year for Samsung’s standard (i.e. non-Ultra) S series phones, too. According to leaker Ice Universe (via SamMobile), there might not be a Samsung Galaxy S26 at all, with Samsung potentially dropping its cheapest, smallest Galaxy S model because it's "no longer competitive.”

When OPPO Find X8 is released, you will find that one of the characteristics of the new flagship in 2024 is that it is small and powerful. Chinese brands are much better at making small-sized mobile phones than Samsung and Apple. You will realize that Galaxy S25 is no longer…October 1, 2024

There's been no indication that Samsung will add or remove models from its Galaxy S25 lineup in 2025, but all roads point to a major shakeup from 2026 onwards (indeed, Ice Universe notes that Samsung "may adjust the S26 series").

Perhaps, then, the Galaxy S25 Ultra and Galaxy S25 will be the last of their kind.

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As if security teams didn’t have enough to deal with, a new threat looms on the horizon: model collapse.

As organizations and researchers voraciously feed data-hungry models with synthetic content, we're witnessing an alarming trend that could undermine the very foundations of AI reliability and effectiveness.

The practice of using synthetic data isn't new, but its overuse has sparked growing concern among experts. When AI models are trained on outputs from previous iterations, they risk falling into a dangerous spiral of error propagation and noise amplification. This self-perpetuating cycle of "garbage in, garbage out" doesn't just reduce system effectiveness—it fundamentally erodes the AI's ability to mimic human-like understanding and accuracy.

As AI-generated content proliferates across the internet, it rapidly infiltrates datasets, creating a formidable challenge for developers attempting to filter out non-human-generated data. This influx of synthetic content can trigger what we're calling "Model Collapse" or "Model Autophagy Disorder (MAD)," where AI systems progressively lose their grasp on the true data they're meant to model.

Consequences

The consequences of this phenomenon on model performance are far-reaching and deeply concerning:

- Loss of nuance: As models feed on their own outputs, subtle distinctions and contextual understanding begin to fade.

- Reduced diversity: The echo chamber effect leads to a narrowing of perspectives and outputs.

- Amplified biases: Existing biases in the data are magnified through repeated processing.

- Nonsensical outputs: In severe cases, models may generate content that is completely detached from reality or human logic.

To get ahead of this, we must first gain a nuanced understanding of data as it concerns training models.

The dark side of data

We've long been indoctrinated with the mantra that "data is the new oil." This has led many to believe that more data invariably leads to better outcomes. However, as we delve deeper into the complexities of AI systems, it's becoming increasingly clear that the quality and integrity of training data are just as crucial as its quantity. In fact, training data itself can pose a significant threat to AI security, particularly in the context of model collapse.

While not traditionally categorized as a cybersecurity threat, model collapse presents several risks that could have far-reaching implications for AI security:

Reliability concerns

As AI models degrade due to model collapse, their outputs become increasingly unreliable. In cybersecurity applications, this degradation can manifest in several critical ways:

1) False positives or negatives in threat detection systems, potentially allowing real threats to slip through unnoticed or causing unnecessary alerts

2) Inaccurate risk assessments, leading to misallocation of security resources

3) Compromised decision-making in security operations, potentially exacerbating vulnerabilities instead of mitigating them

4) Increased Vulnerability to Exploitation: Collapsed models may become more susceptible to adversarial attacks. Their degraded performance could make them easier to manipulate or fool, opening up new avenues for malicious actors to exploit AI-driven security systems.

5) Data Integrity Issues: The recursive use of AI-generated data in training can lead to a dangerous disconnect from real-world data distributions. This growing gap between AI models and reality could result in security systems failing to accurately model or respond to genuine threats, leaving organizations exposed to emerging risks.

Arm yourselves - there’s a lot you can do now

As models become increasingly reliant on AI-generated content, they risk losing their connection to human knowledge and experience, and therefore their integrity and performance.

Before this happens, there are a few steps you can take:

- Preserve and periodically retrain models on "clean," pre-AI datasets: Maintain a repository of datasets that have not been influenced by AI-generated content. These "clean" datasets serve as a baseline for training and retraining models. By periodically retraining models on these datasets, you ensure that the model retains its ability to understand and generate content based on original, human-generated data. This helps mitigate the risk of the model's outputs becoming increasingly distorted or biased due to overexposure to AI-generated content.

- Continuously introduce new human-generated content into training data: Incorporate fresh, human-generated content into the training data to maintain the relevance and accuracy of AI models. That way you can help the model stay current and reduce the risk of it becoming outdated or biased due to reliance on older or AI-generated data.

- Implement robust monitoring and evaluation processes: Establish comprehensive monitoring and evaluation systems that allow for the early detection of model degradation. This includes regular performance assessments, bias detection, and error analysis that will help identify early signs of model collapse, such as reduced accuracy, increased bias, or irrelevant outputs. That way you can take measures, such as retraining or adjusting the model's parameters, to maintain its performance and reliability.

- Utilize diverse data sources and avoid over-reliance on AI-generated content: Make sure training data comes from a wide range of sources. Relying too heavily on AI-generated content can lead to feedback loops, where the model's outputs become increasingly detached from reality. For example, you can train models with data in different languages, cultures, and domains to enhance the model's ability to generalize and avoid overfitting to any particular type of data.

AI is still in its early stages; we’re living in a brave new world. As a result, things will change quickly as models evolve and new ones are introduced. This means you have to stay agile and adapt to these changes to stay ahead. While the above doesn’t provide all the answers, it’s a solid foundation to start building on now.

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This article was produced as part of TechRadarPro's Expert Insights channel where we 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/news/submit-your-story-to-techradar-pro

The Federal Reserve is set to make its second interest rate cut in November, but mortgage rates are still over 6%.

Apple's tiniest desktop also introduces the all-new M4 Pro processor and Thunderbolt 5.

Apple announced the new Apple M4 Pro chip this morning alongside the newly revamped Apple Mac mini (2024), bringing Apple Intelligence to one of the most popular mini-PCs on the market.

The new Apple M4 Pro follows yesterday's announcement of the new Apple iMac (2024) with an Apple M4 chip, the first Mac desktop to get the upgraded silicon.

• This story is developing...

In July, what seemed like an innocuous software update from a cybersecurity vendor, CrowdStrike, caused millions of Windows-based machines across the globe to crash. This wasn’t the first major tech outage, and nor will it be the last. In fact, outages occur regularly across the tech landscape, for a huge variety of reasons. In the last six months alone, Google Cloud Platform, AWS and Microsoft Azure have all suffered outages. The fallout can be severe – planes are grounded, hospital patients are left waiting for treatment, cash fleetingly becomes king again as card payments can’t be processed.

Outages are also costly for organizations. It’s estimated that the downtime and subsequent work to fix machines in the wake of the CrowdStrike outage cost $5.4 billion to Fortune 500 companies alone. They’ll catch the eye of regulators too. Landmark EU regulations such as the Digital Operational Resilience Act (DORA) and the NIS2 Directive – both of which have an indirect impact on UK organizations and focus on risk and resilience – are coming into effect within the next six months.

This spate of outages should sound the alarm for organizations to start thinking about how resilient they are to such events and the risks of relying on a small pool of vendors, particularly cloud providers, which have become ingrained in business strategy.

Cloud consolidation conundrum

Globally, it’s estimated that the three cloud hyperscalers – AWS, Microsoft Azure and Google Cloud Platform – have a market share of 66%. This consolidation of the cloud market has upped the stakes – one faulty update or hyperscaler outage would have a profound impact on businesses globally.

Thankfully, these cloud giants are relatively resilient and full-scale outages rarely – if ever – occur. But recent history shows us that it's fairly common for at least some systems to be taken offline. This highlights why a multi cloud strategy – whereby organizations store data with more than one hyperscaler – is an absolute necessity for building resilience. Leaving all your eggs in one basket is risky, because if the basket breaks, organizations' critical services can be taken offline.

But a multi cloud strategy comes with its own challenges. Firstly, each of the hyperscalers’ platforms has its own nuances. It’s not possible to simply lift and shift data, workloads and applications from one cloud to another. Subtle changes may need to be made to data and workloads, and applications will have to be refactored to suit their new environment. This takes time, resources and specialist skills.

Multi cloud also creates data siloes. For example, a heavily regulated organization in the finance industry may utilize private cloud to maintain control over data for compliance. If they also have data in at least two public clouds, they’ll have to tie together three disparate environments, making it very difficult to drive value from their data.

Finally, multi cloud decreases visibility over data. With data sitting across multiple environments, it’s much more difficult to know where it’s located, who has access to it, how it’s being used and what it has been utilized for in the past. This amplifies challenges around governance and reporting as a single entity. But perhaps more profoundly, as organizations start to deploy generative AI use cases in production, visibility is becoming absolutely vital to success. For AI to be truly effective, it must have access to a complete set of data, otherwise organizations run the risk of hallucinations and AI giving insight that lacks the necessary business context.

Laying the foundations for resilience

So, on the one hand a multi cloud strategy helps organisations to build resilience, hardening them against the possibility of an outage or disruption to a major cloud provider. But on the other, it creates complex challenges – fragmenting data and draining resources.

This is why deploying a modern data architecture built around a unified data platform is a critical step when looking to diversify cloud providers. It provides a layer of abstraction across cloud environments, which gives organizations the flexibility to move data between clouds without the need for timely, resource-intensive refactoring. This enables them to drive value from data, no matter where it resides.

Organizations must learn from the mistakes of the recent past and end their reliance on just a small pool of providers. But they need to lay the foundations for success, ensuring that any efforts to build cloud resilience don’t hinder innovation.

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This article was produced as part of TechRadarPro's Expert Insights channel where we 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/news/submit-your-story-to-techradar-pro

Peripheral accessory brand KontrolFreek has released some limited edition Call of Duty: Black Ops 6-inspired thumbsticks that attach to your PlayStation or Xbox controller.

The KontrolFreek Call of Duty Performance Thumbsticks Deadshot Edition are available now, with an eye-catching yellow and red design inspired by the iconic Deadshot Daiquiri Zombies power-up.

On top of separate PS5 / PS4 and Xbox versions, there are two distinct variants to choose from. There’s the regular edition, which costs $19.99, and the more premium $29.99 Deadshot Edition. The Deadshot Edition features unique packaging and includes a collectible replica Deadshot Daiquiri can container. It also comes bundled with a download code for a special in-game weapon charm modeled after the can - a great little bonus for collectors.

It appears as though the item has already been quite popular, with stock of the PS5 / PS4 compatible Deadshot Edition running dry on the KontrolFreek website. The Xbox set is still in stock right now, but there is no saying whether it will hang around for long.

Third-party listings for the limited edition accessory have already started appearing on websites like eBay, with one seller asking for as much as $69.99 for a package that includes the digital code. 

You can also find plenty of sellers offering lower prices for bundles that don’t include the in-game item, suggesting that some avid fans have been picking this up purely for access to the weapon charm.

Elsewhere, hardware brand SteelSeries has unveiled a huge Call of Duty: Black Ops 6 collection with Zombies-inspired accessories many of which include their own weapon charm. The Arctis Nova 7X x Call of Duty Bundle and Arctis Nova 7P x Call of Duty Bundle are also available, and both come with a pair of KontrolFreek thumbsticks.

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Linux creator Linus Torvalds has called AI little more than a marketing ploy.

In a recent interview with TFiR at the Open Source Summit in Vienna, Torvalds acknowledged artificial intelligence is “really interesting” and that it’s “going to change the world,” however he added the initial hype doesn’t yet justify its usefulness.

Torvalds reportedly grimaced as labelled the current state of the AI market as “90% marketing and 10% reality.”

Linus Torvalds isn’t a fan of AI… yet

For now, Torvalds’ solution is to ignore artificial intelligence until the technology becomes powerful and personalized enough to matter.

“I think AI is really interesting, and I think it is going to change the world," he noted, "and, at the same time, I hate the hype cycle so much that I really don’t want to go there."

"So my approach to AI right now is I will basically ignore it because I think the whole tech industry around AI is in a very bad position," Torvalds added, "however, it seems like there is almost too much AI BS around for the Fin to tolerate."

The developer’s thoughts mirror those of other tech professionals worldwide – it seems that every day a new report is published showing how companies are struggling to deploy meaningful AI tools for a variety of reasons, including poor infrastructure and a lack of readiness on the parts of both workers and leaders.

For now, Torvalds said he recognized the usefulness of some tools, like ChatGPT, in specific use cases, but reiterated that AI’s broader applications remain limited. However, he left room for optimism, suggesting that in five years’ time, AI might mature to support meaningful, everyday applications.

Torvalds’ comments follow recent remarks by Baidu’s CEO, who predicts that the AI bubble might soon burst, leaving only a small percentage of companies in a position to benefit from the remaining interest.

The Linux maker advises tech workers to avoid being swayed by industry trends that feel like bandwagons, instead focusing on meaningful innovations that can actually deliver.

Despite the current hype around artificial intelligence, Torvalds says that he remains focused on his passion for low-level systems development: “I’ve always been interested in the area between hardware and software.”

Via TomsHardware

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Apple is once again taking the mini name to heart, unveiling today an all-new, almost impossibly tiny Mac mini running not only a 3-nanometer M4 chip but with the option of an all-new piece of Apple silicon, the M4 Pro.

When Apple introduced the Mac mini almost a decade ago, it was the smallest Mac to date, at just 6.5 inches x 6.5 inches and 2 inches tall. Recent editions have grown to almost 8 inches square, making them feel less like tiny computers and a bit more like elegant hot plates. This new model clocks in at 5.5 inches square and perhaps a bit taller than the M2 model. That's still about two inches larger than an Apple TV 4K but also small enough to fit in one decent-sized hand.

At a glance, the Mac mini M4 is familiar. It's still made of recycled aluminum (though 85% less than the last model), is still square with rounded corners, and has a circular fan vent in the base. After that, the pint-sized computer diverges. The once-clean face now offers a pair of USB-C ports and a 3.5mm headphone jack. One might argue that the smaller chassis forced the movement of some ports from the back to the front, but I think people will welcome the ease of use.

You'll find the more familiar Thunderbolt (3x), Ethernet, and HDMI ports on the back.

Image 1 of 2

(Image credit: Apple)Image 2 of 2

(Image credit: Apple)

What may matter most to Mac mini fans is the introduction of Apple's newest and fastest silicon, the M4, first seen in the iPad Pro. The last Mac mini topped out at an M2 class chip, offering performance options up to the M2 Pro. In a similar fashion, the new Mac mini marks the introduction of the M4's first iteration: an M4 Pro.

The M4 Pro brings with it an up-to-14-core CPU and an up-to-20-core GPU. It matches the M4's 16-core neural engine, which plays a large role in AI operations. One of the big changes, and one that could significantly impact performance, is the increased memory bandwidth. While the M2 Pro offers 120Gbps throughput, the M4 Pro promises 75% higher memory bandwidth.

Again, we won't know the true impact until we test the new Mac mini and its new CPU.

The new Pro-level silicon also introduces Thunderbolt 5 support, which means those ports will offer transfer speeds of up to 120Gbps, a tantalizing prospect for those who work in pro-level video editing.

Tiny and neutral

Apple is calling this its first carbon-neutral Mac because, in addition to that far reduced use of aluminum, the product features 50% recycled content and is being produced using all renewable energy.

Like other Apple silicon-running systems, the new Mac mini M4 offers full support for Apple intelligence. Perhaps that's why the new base memory for all Mac minis is now 16GB, up from 8GB. Though, you can get up to 64GB of RAM when you have the M4 Pro chip in a Mac mini.

Apple is doing that while keeping the base price at $599 / £599 / $999AU. It's a welcome change, even if it's partially necessitated by Apple Intelligence's onboard generative AI processing demands.

(Image credit: Apple)

While I have yet to test the new M4 Pro Mac mini, I have seen it in action running, for instance, an application known as Aperty that lets you do pro-level portrait photography editing.

In one demo, I watched as they added new point lighting to a photo and then dragged it around as the subject's lighting changed in real-time. The system appeared to instantly assess the 3D contours of the face, apply an invisible map, and adjust the virtual light accordingly. It can do this work and other onboard AI actions – powered mainly by the Neural Engine – that can instantly add or change makeup and remove under-eye shadows.

The new Mac mini M4 is on pre-sale today (Oct. 29) and ships on November 8 with a starting price of $599 / £599 / $999AU. The base model starts with a 10-core CPU and 10-core GPU, 16GB of memory, and 256GB of storage. It ranges up to $1,399 / £1399 / $2,199AU for a Mac mini M4 packed with a 12-core CPU, 16 Core GPU, 24GB of memory, and 512GB of storage.

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The Apple M4 Pro chip is official now that Apple has announced the new Apple Mac mini with M4 and M4 Pro.

The new chip is a step up from the existing Apple M4 chip, which is already powering the latest Apple iMac M4 and Apple iPad Pro. The new Apple M4 Pro, meanwhile, offers a boost in core counts for both the CPU and GPU built into the chip for those who need more performance without committing overkill on their latest creative project.

Since the Apple M4 Pro fits into the midrange in terms of what Apple fans are looking for from Apple Silicon, this is going to be a popular option for many, and fortunately, we have all the latest from Apple about the new chip in terms of specs and potential performance you can expect over the last-gen Apple M3 Pro and we're here to answer all your questions about this latest SoC for Mac products.

Apple M4 Pro chip: Cut to the chase

• What is it? The follow-up to Apple's M3 Pro chip
• When is it available? Available with select Mac products, shipping November 8, 2024
• What does it cost? It won't sell on its own, but will come installed on Apple Mac products like the Apple Mac mini (2024).

Apple M4 Pro chip: Release date

(Image credit: Apple)

The Apple M4 Pro chip won't sell on its own, will come as an optional upgrade for the newly announced Apple Mac mini 2024 and the likely Apple MacBook Pro 14-inch and Apple MacBook Pro 16-inch refreshes, expected to launch this year.

While you can pre-order the new Mac mini with Apple M4 Pro now, you'll have to wait until November 8th to actually get your hands on any new hardware with the Apple M4 Pro chip - as the new Mac mini models will start shipping out by then or you can pick it up in store.

Apple M4 Pro chip: Price

The Apple M4 Pro chip will not sell on its own, but instead, it will power the new Mac mini as a premium upgrade, and will likely be an option for the highly anticipated 14-inch and 16-inch MacBook Pro models widely expected to be revealed later this month.

Apple M4 Pro chip: Specs & performance

(Image credit: Shutterstock / Alex Ost)

The new Apple M4 Pro will have some noticeable improvements over last year's Apple M3 Pro, while it will stay the same in other areas.

First, it's a 'second-generation' 3nm system-on-a-chip, so it has a similar architecture to the Apple M3 Pro, but there are some important differences.

First, it features faster clock speeds than the Apple M3 Pro, at least according to Apple.

There's also the neural engine, which is capable of 38 TOPS compared to the Apple M3 Pro's 18 TOPS, which is exactly what you'll need if you want to take advantage of the new Apple Intelligence tools, apps, and functionality introduced in this latest generation of Macs.

Additionally, you also have support for Thunderbolt 5 and increased memory bandwidth, which makes the unified memory more efficient despite remaining the same starting amount as last year's M3 Pro.

In terms of performance, Apple said that it will have up to twice the ray-tracing performance as the Apple M3 Pro and faster performance and efficiency cores, though Apple hasn't revealed much yet about the latter.

Ultimately, we'll have to see how the new chip performs once we get our hands on the new Mac devices that it powers to know for sure, so watch this space for reviews and performance breakdowns once we have them.

This desktop computer has its first design change since 2010, with a smaller footprint, vents at the bottom, and ports on the front.

The cleric takes over after Israel killed Hezbollah's longtime leader, Hassan Nasrallah, in an airstrike in a Beirut suburb in late September.

(Image credit: Bilal Hussein)

You could fill a stadium or two with all the cheap headphones out there. We tested a ton to help you pick the right pair.

We've all got opinions on what the best Netflix shows are. If you're anything like me, you might find yourself going back to specific episodes or moments, because they're just that good. But it can be frustrating trying to remember timestamps or episode titles, meaning there's a little effort required to revisit our favorite moments.

Thankfully, the best streaming service has a genius new solution. They've just introduced a new feature called Netflix Moments, which calls time on the endless scrolling and simplifies finding those all-important scenes. Whether you're looking for your favorite twisted children's game ahead of Squid Game season two or you can't stop thinking about that romantic Bridgerton moment, there's now a way to fast-track the experience.

What is Netflix Moments?

Netflix's newest feature essentially lets you clip scenes from its library so they're easier for you to access. These can be saved as bookmarks so you can navigate to them to watch from that point onwards, meaning you don't need to scroll through or keep hitting the skip button.

It also allows you to share these Moments to social media, whether you want to put it on your Instagram Story or send it directly via WhatsApp. This is actually a pretty genius way to convince your friends to watch something, or just scream about that big moment none of you have been able to stop thinking about. Whatever you use it for, it's going to make reliving and sharing scenes a breeze.

The streaming service has rolled out Moments alongside a new global campaign called "It's So Good", which features some famous figures discussing those unmissable scenes. Take a look at that below.

Moments is expected to start appearing across devices very soon, and seems perfectly suited to mobiles especially due to the scene sharing capabilities. While Netflix has not confirmed an exact timeline for the rollout, keep an eye on your My Netflix tab and you should be seeing it in the near future.

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