News
- Windows 11 could be getting a new 'shared audio' option
- The feature, spotted in testing, allows for piping audio to multiple speakers
- It's not clear exactly how it works yet, though, as it's just hidden in testing in an early form, and not live in preview builds yet
If you've ever wanted to play music (or anything else) from your Windows 11 PC through more than one speaker, it looks like your multi-output dreams may be coming true.
At least based on the findings of a well-known leaker on X, PhantomOfEarth, who has been doing the usual combing through hidden bits of Windows 11, and found the relevant feature, then enabled it with a configuration utility (in a preview build).
Windows 11 is getting a "shared audio" quick setting to let you easily play audio through multiple output devices! (Hidden in the latest Dev/Beta CUs) pic.twitter.com/aalAJ68OSzJuly 19, 2025
As you can see in the above post, the feature is fired up via a 'shared audio' option in Windows 11's quick settings, and it's apparently in the current Dev and Beta preview builds of the operating system.
Click on it and you're presented with a panel that allows you to select multiple output devices to receive audio from the PC. Tick the speakers you'd like to use, and Windows 11 will pipe sound through all of them.
Analysis: sounds like a plan(Image credit: Shutterstock)What we aren't shown in this leak is whether the connection can be made wirelessly (via Bluetooth), or has to be wired (with a cable), or indeed whether two Bluetooth speakers can both be hooked up for simultaneous playback.
We guess the capability isn't functional in any way yet - if it was, presumably the leaker would have shared further details on how it works. Remember, this isn't live in testing - shared audio remains work in the background of Windows 11 for now - and it may not ever be realized. However, it makes sense that Microsoft would want to provide this functionality, given that it's long overdue.
In fact, it's a bit of a headscratcher why Microsoft didn't enable this in a version of Windows many moons ago. While it may admittedly be something of a niche feature, it's undoubtedly of use to some people - you only need to look at forum posts online enquiring about how to do this in Windows. The answer to that question previously was to install a third-party app, but having the ability native in Windows 11 - and easily accessible via quick settings - is clearly a useful addition for the OS.
Assuming Microsoft does push forward with the share audio capability, of course, and I'm betting that this should go live in test builds before too long.
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The relationship between data and AI is inherently symbiotic: better data enables better AI, and better AI allows for more sophisticated data processing. This virtuous cycle should accelerate enterprise AI adoption, yet most organizations find themselves stuck before it even begins.
The culprit isn't computational power or model sophistication — it's data variety. While enterprises rush to deploy large language models and agentic systems, they're discovering that the messy, inconsistent, and wildly diverse nature of their data creates an insurmountable bottleneck.
The statistics tell a sobering story. While 94% of data and AI leaders say interest in AI is leading to a greater focus on data, 75% of surveyed leaders find AI adoption challenging, with 69% saying most AI projects don't make it into live operational use. Of companies that reported cost reductions from AI, most had savings of less than 10 percent, while those with revenue increases mostly reported gains of less than 5 percent.
Yes, we've all heard about data volume and velocity. But it's not the size or speed that trips up AI projects — it's the fact that data is messy, diverse, and wildly inconsistent across systems, formats, and structures within organizations and among external partners. With data volumes expected to increase more than tenfold from 2020 to 2030, this challenge is rapidly intensifying.
What Makes Data Variety So Challenging?Enterprise data variety shows up across multiple, compounding layers that create exponential complexity. Every SaaS application, database, file system, and partner platform speaks a different language, requiring dozens or sometimes hundreds of unique connectors just to establish basic connectivity.
Each connector has to handle data arriving in countless forms: structured formats like CSV and JSON, semi-structured content like XML and spreadsheets, and fully unstructured materials including PDFs, contracts, images, and emails. Each requires context-sensitive parsing to extract usable information.
Even when dealing with the same business concepts, different systems use entirely different definitions and schemas. "Customer ID" in your CRM may bear no resemblance to "Account Number" in your billing software. Meanwhile, APIs evolve, vendors update fields, and data formats change mid-stream, making integration a constant maintenance challenge rather than a one-time effort.
External data compounds this complexity exponentially. While internal systems can be well controlled, external data sources from partners, suppliers, regulators, and customers introduce constant variability. New data providers mean new schemas, and existing ones may change unexpectedly without warning.
Why AI Alone Can't Solve the ProblemIt's tempting to believe that AI, especially large language models, can simply be pointed to a data system, allowing AI-powered code generation to ingest raw data and figure it all out. In reality, there are multiple layers of technical challenges to solve when building truly enterprise-grade, reliable, and scalable integrations. Moreover, testing and maintaining integrations in light of the fact that many systems aren’t even well documented, makes this a problem that is incredibly hard for both humans and AI.
The combined human and AI effort, however, is very promising. It starts with taking advantage of the fact that AI excels at pattern recognition, suggesting schema mappings, and parsing unstructured content. But the foundational work of orchestration, reliable connectors, business logic implementation, and governance requires engineering discipline that pure AI cannot deliver alone.
Finally comes the people and process factor. Data and AI leaders consistently agree that cultural and change management challenges are the primary barrier to becoming data- and AI-driven, suggesting that technology alone is insufficient for success.
The Emerging Solution: Agentic Integration ArchitectureThe path forward isn't pure AI or pure software engineering — it's their thoughtful combination. We need AI-powered software abstractions that allow systems to adapt to variety rather than fight it.
At each layer of the data stack, AI assists while software engineering principles enforce durability, reliability, and governance:
Virtual data products represent a particularly powerful abstraction in this hybrid approach. By creating consistent, reusable interfaces that act as contracts between data producers and consumers, organizations can decouple physical data location and format from actual usage. This abstraction layer enables seamless collaboration while supporting diverse data formats without complex coding or integration barriers.
Modern platforms now support multi-speed data processing, allowing data pipelines to be defined once but operate across different processing engines and latencies. This flexibility ensures that real-time, batch, and streaming workloads can coexist within the same architectural framework.
Perhaps most importantly, successful implementations maintain human-in-the-loop collaboration where AI assists but humans validate critical decisions around schema inference, semantic mapping, and business logic. For example, newer standards like MCP and A2A are making it possible for AI to discover and recommend integrations or flows.
Data products that support MCP enable AI to discover the right data and actions, and then make recommendations for end-to-end integration. But engineers are still needed to establish governance, security, and guardrails against errors in AI-based planning to ensure that business needs are met.
Maintenance and assurance of quality as new model versions come is another key guardrail that engineers will build. This approach keeps integrations reliable while dramatically improving speed and scalability.
The Strategic PayoffEnterprises that solve data variety challenges don't just reduce integration headaches — they unlock genuine competitive advantages. AI project cycles shrink from months to weeks when teams spend less time preparing data and more time using it.
Integration costs and times drop dramatically when reusable data products eliminate redundant connector development. When combined with the latest standards, they enable AI to help deliver more of the integration work.
Most significantly, model performance improves substantially thanks to higher-quality inputs, while teams can focus on innovation rather than data plumbing.
As PwC notes in their 2025 AI predictions, "A shrewd strategy will instead emphasize what can set you apart — how you leverage AI with your institutional knowledge and proprietary data". The companies that engineer for data variety early, using thoughtful combinations of AI, software engineering, and domain expertise, will find themselves with sustainable competitive moats.
The New Competitive RealityAs AI models become increasingly commoditized and accessible, the real differentiator won't be better models — it'll be better data systems. With more than 80 percent of organizations not yet seeing a tangible enterprise-level impact from generative AI, and most companies not even using half of their data, those that solve the data variety challenge will pull ahead decisively.
Ultimately, AI-ready data isn't about having more data — it's about having the right data, in the right shape, at the right time. The AI race won't be won in model labs. It will be won in the trenches of data integration, where variety is tamed via a rich collaboration between intelligent engineering and AI rather than magically solved by AI.
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- A phishing campaign spotted trying to work around FIDO keys
- The "cross-device sign in" feature triggers a QR code
- Crooks can relay the QR code to bypass MFA and log in
Hackers have found a way to steal login credentials even for accounts protected with Fast IDentity Online (FIDO) physical keys. It revolves around a fallback created in these multi-factor authentication (MFA) solutions, and only works in certain scenarios.
FIDO keys are small physical, or software authenticators, that use cryptographic technology to securely log users into websites and apps. They serve as a multi-factor authenticator, preventing cybercriminals who have already obtained login credentials from accessing the targeted accounts.
To use the authenticator, most of the time users need to physically interact with the device. In some scenarios, however, there is a replacement mechanism - scanning a QR code. Criminals have started using this fallback in so-called adversary-in-the-middle (AitM) attacks.
Phishing for QR codesObserved by security researchers Expel, the attacks start with the usual phishing email.
It leads victims to a landing page that mimics the look and feel of the company’s normal authentication process, including an Okta logo and sign-in fields for username and password.
Normally, after entering the login credentials, the user would need to physically interact with the FIDO key. In this case, however, the user is presented with a QR code instead.
This is because in the background, the attackers used the login credentials, and requested “cross-device sign-in”, which triggered the QR code fallback. If the victim scans the QR code, the login portal and the MFA authenticator communicate, and the attackers successfully log in.
The best way to defend against this attack is to enable Bluetooth proximity checks on FIDO, so that QR codes only work in the phone scanning them is physically near the user’s computer.
Alternatively, companies should educate their employees on how to spot suspicious login pages and unexpected QR codes, since this malicious landing page could easily be spotted by looking at the URL and the domain.
Finally, IT teams should audit authentication logs for strange QR-based logins, or new FIDO registrations, which can serve as an indicator of compromise.
Via The Hacker News
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What if editing photos on your phone felt as natural and capable as editing on a desktop computer? That’s exactly what Luminar’s mobile photo editor (available for Android, ChromeOS and iOS) is built for. Whether you’re a photo enthusiast capturing everyday scenes or a working photographer creating content on location, having reliable AI tools on your phone can streamline your workflow and bring more flexibility to your creative process.
Luminar’s mobile photo editor isn’t just another camera app with filters. It’s built specifically for photographers, with tools that focus on enhancing photos so they look real to life, not over-processed or artificial. From subtle corrections to advanced AI-driven enhancements, every tool is designed to support a photographer’s vision while keeping the image natural and true to its original character.
Why mobile photo editing has become essentialSmartphone cameras have evolved into powerful creative tools. Many phones now offer impressive image quality, even in challenging lighting conditions. That means more photographers are using mobile devices not only to capture photos, but also to edit and share them. Even top-level pros use smartphones to take behind-the-scenes photos when teaching, documenting lighting setups, sharing live moments, or posting previews while on location.
However, mobile editing often comes with limitations. Slower apps, clunky interfaces, or basic editing features can make it hard to maintain a consistent creative flow. Luminar’s mobile app addresses that by offering intelligent tools that are easy to use and capable of producing high-quality results.
Built with the same design principles as Luminar Neo and available for both iOS and Android/ChromeOS, the mobile editor provides a familiar experience for existing users. While it doesn’t yet offer full integration with the desktop version, both platforms share a similar editing approach, making it easier to transition between mobile and desktop workflows when needed.
(Image credit: Luminar)Practical AI features that make a differenceThe strength of Luminar’s mobile editor lies in its AI-powered tools. These features go beyond simple filters. Each one is designed to solve common editing challenges in a quick and intuitive way, with adjustments that understand the content of the image.
Enhance AI in action: the before image is on the left. (Image credit: Luminar)Enhance AI
Enhance AI simplifies the editing process by combining up to twelve core adjustments into a single smart slider. This includes tone, contrast, color, clarity, and more. Instead of spending time making each adjustment manually, the tool analyzes the photo and applies intelligent improvements with just one control.
It’s a fast way to polish an image without compromising detail or making it look over-processed. Enhance AI also works non-destructively, allowing photographers to make changes with confidence, knowing they can always return to the original version if needed.
(Image credit: Luminar)Relight AI
Lighting is one of the most common challenges in mobile photography. Relight AI provides a simple solution by allowing users to adjust the brightness of the foreground and background independently. This helps improve underexposed subjects without overexposing the background, creating a more balanced and natural-looking photo.
It is especially useful for portraits taken indoors or in backlit conditions where traditional edits might fall short.
Sky AI and Atmosphere AI
Sky AI makes it easy to replace a dull or overexposed sky with something more fitting. Photographers can choose from a variety of skies including sunny, dramatic, and even stormy settings. The tool aligns the new sky seamlessly, accounting for reflections and lighting to make the final image believable and cohesive.
Atmosphere AI adds another layer of mood and texture. With options like mist, haze, and fog, it helps create more depth and emotion in a scene. These effects can be applied subtly or dramatically, depending on the photographer’s vision.
(Image credit: Luminar)Portrait Tools: Skin AI and Body AI
For portrait photography, the mobile app includes several AI tools designed to enhance without overdoing it. Skin AI gently smooths skin while preserving natural texture and avoiding that artificial look seen in some other apps. Body AI offers subtle adjustments to proportions, helpful in cases where lenses or angles may have distorted a subject’s appearance.
These tools help bring out the best in a portrait while keeping the result natural and respectful to the subject.
Edit anywhere without extra gearOne of the biggest advantages of Luminar’s mobile editor is its portability. There’s no need to carry a laptop or other equipment when editing can happen directly on your Android phone or iPhone. This is ideal for photographers who are constantly on the move, whether traveling, shooting events, or capturing spontaneous moments.
Quick edits can be done in the field, and more detailed work can be finished later on a larger screen using Luminar Neo. This flexibility allows for a smoother, more responsive workflow that adjusts to the needs of each shoot.
(Image credit: Luminar)A practical tool that fits any workflowLuminar’s mobile photo editor is designed with simplicity, efficiency, and quality in mind. The AI tools are intuitive enough for photo enthusiasts and powerful enough for professionals, making them accessible without lowering creative standards.
Most importantly, it’s an app built with photographers in mind. The focus is always on helping images look their best while staying true to how the scene looked and felt when captured. From landscapes and street photography to portraits and travel shots, Luminar helps photographers create natural, clean results they’ll be proud to share.
Ready to see what Luminar’s AI tools can do for your mobile photography? Try the app today and follow @luminar_global on Instagram for editing tips, photo inspiration, and updates from the Luminar community.
As far as Netflix documentaries are concerned, Trainwreck is doing some heavy lifting across June and July: we’ve had weekly rollouts including Poop Cruise, The Cult of American Apparel and Balloon Boy, and this week it’s the turn of P.I. Moms. The new installment tells the story of a group of soccer moms turned private investigators, who were supposed to have their story told in a 2010 series for A&E Network’s Lifetime channel.
If you think the name or premise is vaguely familiar, that’s because the series was canceled before it ever made it to air. As it turns out, there was an even bigger scandal brewing behind the camera than there ever was in front, leading straight back to the P.I. agency’s boss, Chris Butler.
Thankfully, Trainwreck: P.I. Moms deep dives into the various allegations that were unearthed by the original reality TV show’s production team, and you can bet your bottom dollar that it gets juicy. Personally, I can’t thank Netflix enough for their efforts to brew the perfect bingeable storm 20 years on.
As I’ve started to explain, Trainwreck: P.I. Moms explores allegations made by Lifetime’s production team against Chris Butler, the boss of the P.I. agency in question. If Selling Sunset or the Real Housewives had made a private investigator team for reality TV, it would have looked like P.I. Moms, with the Bay Area private investigator firm staffed almost exclusively by soccer moms. Butler & Associates was owned by Butler, with only one other male member, Carl Marino, on staff.
The Lifetime show was supposed to be in the care of showrunner Lucas Platt, with the women themselves easily interesting and smart enough to make any type of end product an incredibly successful one. Obviously, that didn’t happen, and it’s probably less surprising to realise that was not down to the soccer moms. With wannabe actor Marino claiming he wanted a bigger role in the show, journalist Pete Crooks received alarming intel after being invited to do a ride-along with the moms for Diablo magazine. The most alarming part? The cases were being set up by Butler rather than being authentic.
After this initial discovery came more bad news for Lifetime, with reports of criminal activity within the agency, including drug dealing, illegal wiretapping, and even more staged phony sting operations. According to the US Sun, Butler had an ever longer list of allegations against him personally, such as undercover surveillance, decoy work in infidelity and domestic cases, general private investigations and assisting with "Dirty DUIs scheme”. These schemes involved getting female “helpers” to encourage men to drink and then get into a car, with corrupt police officers working with Butler to then pull the men over and arrest them for drunk driving.
The final nail in the reality TV coffin was Butler being convicted of drug dealing and running a brothel, unsurprisingly leading Lifetime to shut down production on the show. While four moms were affected by what happened, we hear from two in the new Netflix series: Denise Antoon and Ami Wiltz. The group previously appeared on Dr. Phil to discuss the potential scam, but this is the first time viewers have been given detailed access to the entire story from the inside.
Arguably, the worlds of reality TV and corruption have never been simultaneously explored in this way before, although Balloon Boy did begin to touch on some of these themes. In the words of RuPaul, I can’t wait to see how this turns out.
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- Pro+ plan price up by 23%, but Slack says "significant value" has been added
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Slack has rolled out a new pricing structure to add more value to its plans, bringing it more aligned with the Salesforce ecosystem by expanding Salesforce Channels to free plans.
Extra value has also been added to the Pro plan, which remains unchanged in terms of pricing, with Business+ seeing a 23% price hike alongside the introduction of a new Enterprise+ plan.
As part of the upgrade, Salesforce is injecting more artificial intelligence into its paid plans, however each will have a varying degree of assistance.
Slack plans get a big upgrade – only some prices risePro plans will see no changes to pricing, but they will get some of the company's core AI features including AI summarization and huddle notes, as well as enhanced security and deeper Salesforce integration.
The company explained the Business+ price increase, from £9.75 per user per month to £12, reflects the "significant value" added, including advanced AI tools like translation, workflow generation and recaps, as well as further Salesforce features and security improvements.
Enterprise-grade AI, premium Salesforce integrations, and enhanced security, admin controls, governance and compliance are the key additions to Enterprise+, which is a new plan coming to the Slack family.
Understandably, artificial intelligence is the central topic of discussion here, with 38,000 custom APIs built plus dozens of partner AI apps from the likes of Box, Writer, AWS, Adobe, Cohere and Perplexity available in the Slack Marketplace.
Being that Slack is owned by Salesforce – a company that's invested heavily in AI and one that's working on finding the right balance between human and machine – it should come as no surprise that autonomous AI agents via Agentforce are also available to paid tiers.
The company describes the Slack platform as the "work operating system for the agentic era."
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Larry (Harry Richardson) and Marian (Louisa Jacobson) only became a couple at the beginning of The Gilded Age season 3, but it’s as if we’ve been shipping them forever. Five episodes into the new season on HBO Max this month and Larry has now proposed, meaning Larian (their fandom name, obviously) is officially on.
Their friendship has always had a healthy dose of chemistry, but now they are a couple, Marian doesn’t actually know everything about Larry’s fairly scandalous dating history. Back in season 2, he had an affair with Susan Blane (Laura Benanti), which they had to keep a secret even though neither of them were married. Susan was an older widow, giving Larry something of a reputation, and we still don’t know how – or if – this could affect Marian.
Even with all this Larian excitement, I’m not convinced this was the most exciting news to come out of The Gilded Age season 3 episode 5. If nothing else, I’m a huge fan of being a hater, and the HBO Max show delivered that to me on a plate perfectly in the form of Maud Beaton (Nicole Brydon Bloom).
While Larry and Marian are blissfully in love in episode 5 of The Gilded Age season 3, the groom-to-be seemingly lies about his plans, choosing to celebrate the good news in a less-than-reputable establishment called The Haymarket. It’s essentially the New York version of the Moulin Rouge, so you can imagine the kinds of behaviour we’re likely to see there. Out of the corner of his eye, he spots Maud, the woman who conned Oscar (Blake Ritson) out of his entire family fortune.
When Larry confronts Maud about who she is, Maud denies it, introducing herself as Dolly Trent. The next day, Larry tells Oscar about what happened, who comes to the conclusion Maud no longer has the money she previously stole. While Oscar still wants answers and some kind of revenge, John (Ben Ahlers) thinks Maud’s new circumstances are punishment enough. Basically, it’s now up in the air whether Maud will come back into the bigger picture for her just deserts.
For me, that’s a much more exciting prospect than watching two lovely and sweet people get married. Sure, everybody loves a Pride and Prejudice moment for a happy ending, but what The Gilded Age has always done best is dripfeed its drama in the classiest of ways. If someone stole your family’s money and coincidentally reappeared back on the scene, you’d probably still be holding a grudge no matter how much time has passed. Instead of calming down, new episodes now have the potential to become a lot more chaotic, and I’m all here for it.
Seeing Maud will potentially get Larry in some trouble, meaning there could be some trouble in paradise when it comes to Larian’s wedding. As I’ve touched on, Larry is withholding details of his personal life from Marian as it is, so the extra gut punch of lying about his whereabouts and running into Maud isn’t likely to go down too well either. It only takes one small straw to break the camel’s back, and this could be a delicious one.
Don’t get me wrong – I’m not wishing ill will on the newly engaged couple. But isn’t the show so much more fun when disaster is imminent? There’s nothing more tantalising than things going wrong in the Victorian upper classes, and God, The Gilded Age does it so well.
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