By Siôn Geschwindt The European Space Agency has released the first major batch of data from its “dark universe” telescope Euclid. What’s inside could change our understanding of dark matter and the expansion of the universe. The data comprises just one week’s worth of deep field images from three points in space. They make up just 0.4% of the vast area Euclid will capture, which scientists say will be the largest 3D map of the sky ever created. With one scan of each region so far, Euclid has already spotted 26 million galaxies, each potentially containing millions of stars and billions of planets.…This story continues at The Next Web

Source:: The Next Web

By Hisan Kidwai The iPhone camera shutter sound is pretty iconic and helpful in letting you know when you’ve…
The post How to Turn Off Camera Sound on iPhone: 3 Ways appeared first on Fossbytes.

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By Deepti Pathak Abbreviations and acronyms change daily, so keeping up with the latest slang can be difficult if…
The post TS Meaning in Texts Explained: Use Cases & Examples appeared first on Fossbytes.

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New PCs introduced Tuesday by Dell sport high-powered Nvidia GPUs designed to help workers test AI models before deployment.

The new AI PC lineup includes laptops and desktops with Nvidia’s latest Blackwell Ultra and Blackwell GPUs, which provide the muscle needed to test compute-intensive AI models. AI PCs are designed to run generative AI tools and models more efficiently than standard PCs.

“These AI developer PCs will make it much easier for developers to prototype, to test and even scale their models into production environments,” said Kevin Terwilliger, vice president and general manager for consumer, commercial and gaming PCs at Dell.

The announcement coincides with Nvidia’s rollout of its latest GPU Blackwell Ultra at the GTC conference in San Jose. The GPU is the successor to the red-hot Blackwell GPU, which racked up $11 billion in sales in the most recent quarter.

The Pro Max series of workstations bring hardware previously used in data centers to desktops. “These systems will redefine AI developer experiences by really bridging the gap between desk side experimentation and enterprise scale AI deployment,” Terwilliger said.

The new Pro Max with GB300 packs the tightly coupled Blackwell Ultra GPU and Grace CPU, both made by Nvidia. It includes 784GB of unified system memory — 288GB HBM3e memory and 496GB of LPDDR5X memory.

Developers can test and prototype AI models with up to 460 billion parameters on the Pro Max with GB300. The system delivers 20 petaflops of performance with the FP4 data type, which is a low-precision measure for inferencing.

The Pro Max with GB10 includes Nvidia’s Blackwell GPU — a generation behind the Blackwell Ultra — and the Grace CPU. Developers will be able to work with AI models with up to 200 billion parameters on a  PC that delivers 1 petaflop of FP4 performance.

The systems are slated to be available later this year, include Nvidia’s DGX Base OS or Ubuntu Linux, and will be preconfigured with Nvidia’s AI software.

Desktop prototyping makes it easy to determine the size and performance of AI models, according to Terwilliger. “Once you right size it for the data set, then it’s appropriate to then scale it into the data center,” he said.

Some Dell customers need a secure test environment where they can tune some of their own data, said Matt Toolan, a Dell spokesman. For example, customers have tested different digital assistants to determine whether chat capabilities and responses were meaningful and on target, Toolan said.

Anshel Sag, principal analyst at Moor Insights and Strategy, was skeptical about Dell’s claim of using Pro Max PCs to scale AI models to data centers.

Instead, the AI tools more about making the deployments of on-device AI smoother, Sag said. “I don’t really think PC workloads are really useful for data-center scale deployments. I do believe Dell is uniquely positioned to enable hybrid AI that are entirely on-premise,” Sag said.

Dell also announced Pro Max laptops with RTX Pro GPUs based on the Blackwell architecture. The company claimed the PCs will be up to 36% faster than the previous-generation Precision PCs.

The Dell Pro Max laptops have “tandem” OLED displays, haptic touchpads, lattice-less keyboards and 8-megapixel IR cameras. The systems come with Intel Core Ultra Series 2 or AMD Ryzen processors, offer screen sizes from 14-in. to 18-in., and will ship later this year. 

Dell did not provide pricing information for the systems.

Source:: Computer World

If you’re looking for an AI PC, why wouldn’t you be looking for a Mac?

After all, Apple’s systems are built for privacy and security and, thanks to Apple Silicon, are now quite capable of running big generative AI (genAI) models swiftly in-house — and at a fraction of the energy costs of Windows-based systems. While a move to Apple won’t suit every company or even every situation, it’s absolutely true that the platform is a viable one for AI, and has remained so for some time.

To understand how viable Macs are for running AI in your business, consider the recently-launched M3 Ultra Mac Studio. Apple made impressive claims for these systems on launch. It told us its highest-end Mac Studio was 16.9 times faster than the M1 Ultra Mac Studio at generating tokens using a large language model (LLM) with hundreds of thousands of parameters. That neat claim was recently put to the test when YouTuber Dave Lee showed us that the most highly specified M3 Ultra Mac Studio is capable of running a 671-billion-parameter AI model natively on the system at under 200 watts of energy. (He used DeepSeek RI, of course.)

A supercomputer on your bookshelf

That’s an amazing statistic; it means you can run a powerful genAI models using DeepSeek on a system that fits on a shelf above your desk, which must be a compelling proposition to any enterprise purchaser considering deployment of an in-house self-hosted system for AI. It’s even more impressive when you consider that comparable performance on traditional PCs would require multiple GPUs and consume 10 times as much energy. 

(You might be able to find some way to put together a PC-based cluster to deliver the same kind of performance, but it is arguable that you’ll still spend the $14,000 you’d need to drop to get the most powerful Mac desktop. (In some cases, you might not need quite as much of a system.)

What this all means — or should mean — is that the enterprise landscape is ripe for Apple. After all, the company’s devices are private by design, secure by nature, and deliver performance and energy consumption advantages other PCs at the same price points don’t match. Not only do they deliver this, but they also have the processor horsepower it takes to run AI natively.

If you just need to run smaller AI models, then an M4 MacBook Air also has you covered, allowing most businesses to now consider Mac-based and self-hosted AI deployments for a range of use cases.

Apple, the perfect endpoint AI solution

While buffeted by bad news elsewhere in its business, the Mac has become a bright star for Apple, thanks to Apple Silicon. While Apple Intelligence might have let the company down, Apple Silicon has not. That matters quite a lot, given a recent report from IDC Research claiming that four-in-five (80%) of PCs sold this year will be AI PCs, though there are some challenges to that.

Apple helps meet those challenges, of course. IDC’s survey revealed that while nearly all organizations are using or intend to use cloud-based AI platforms, the security and data privacy inherent to these systems remains the biggest challenge to broad deployment, even more than cost.

While most business users are looking at the ever-expanding plethora of enterprise-focused cloud-based AI systems, they are really concerned about what happens to their data when shared in the cloud, particularly in regulated industries where compliance matters, such as healthcare.

That’s driving many enterprises seeking to deploy AI to search for solutions that let them deploy genAI tools on endpoints — self-hosted AI that runs natively on a device they own and have in their own office, in other words.

That, of course, is what Apple’s Macs — and certainly its Mac Studio — are more than capable of doing. 

AI models for the few

There’s a lot more to running AI in business than text summaries, automated writing tools, Microsoft Copilot, or even super-smart Webex AI bots; enterprise users are seeking to build or buy their own bespoke AI packages capable of learning from their own heavily curated business data and helping them with their business. That’s not software that necessarily comes in a box (digital or otherwise), but is software that, at best for ultimate privacy and security, runs natively on the device.

Apple Silicon is more than up to the task. (And you get an annual free OS upgrade of what is arguably the most secure operating system, too.)

You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

By Siôn Geschwindt Aerospike rocket engines are the stuff of legend in the space industry. Conceived in the 1960s, their unique spiked-nozzle design promises better efficiency, reusability, and performance at all altitudes. But their complexity — and the shutdown of major space programmes towards the end of the 20th century — meant they never entered the mainstream.  But now, startups are dusting off old designs and using new technologies to revive aerospike engines for modern spaceflight. One of these ventures is Spain’s Pangea Aerospace. Founded in 2018, Pangea has been operating under the radar for most of its seven-year history. But today, the…This story continues at The Next Web

Source:: The Next Web

By Siôn Geschwindt Oslo-based startup Visoid has raised €700,000 in seed funding for its AI software, which helps architects turn their 3D models into striking renders within seconds.  For architects and designers, a good render can mean the difference between winning or losing a client. However, rendering typically requires a lot of time, effort, expertise — and money. Tools like Visoid look to disrupt the status quo. “What started as a simple tool for architects to generate beautiful visualisations has led us on a journey to simplify and democratise the visualisation process itself,” said co-founder Joachim Holwech. Here’s how the software works:  You…This story continues at The Next Web

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By Hisan Kidwai Back when the internet had a designated place in our homes, phone books were the only…
The post How to Find Someone’s Phone Number Online: 4 Ways appeared first on Fossbytes.

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It is now clear that Google Assistant will be replaced by generative AI (genAI) tool Gemini in most Android-based phones. The process is expected to begin shortly and be completed before the end of the year, according to the official Google blog The Keyword.

Mobile phones running Android 9 or earlier will not be affected by the decision, as they would likely run into problems using Gemini.

In addition to smartphones, Gemini will also be integrated into tablets, smart watches, televisions, monitors, cars and headphones, according to 9to5Google.

Source:: Computer World

By Siôn Geschwindt Dutch unicorn Mews will most likely list in the US instead of in Europe if the hospitality management company goes public, its CEO and co-founder Matthijs Welle told TNW.  “An IPO is one of the options that we would consider for the future, and if we were to go down that route, a listing in the US is the most likely option, although it is too early to specify further details regarding a potential listing,” Welle said. “Most other vertical SaaS companies, who are comparable to us, are listed in the US, where there are deeper capital markets and a…This story continues at The Next Web

Source:: The Next Web

Apple has a lot of challenges these days. Would Steve Jobs really be handling these problems better than current leaders?

The problems, some are long-term, others short-term, include (but are not confined to):

Chinese consumers turning to domestic brands in response to the US trade war.

US customers feeling the impact of tariffs and anticipated increase in product prices.

Regulators in every nation seemingly intent on chipping away at the services empire Apple built from thin air. 

Apple’s recently-disclosed failure to launch with Apple Intelligence.

Supply chain problems, partly in response to trade wars and partly exposed during Covid, when single-source supply chains collapsed overnight.

Declining consumer trust in technology.

These challenges are in addition to the tasks Apple has always had to manage — maintaining hardware and software quality, developing new products and services that surprise and delight customers, building consumer engagement, and inventing the best hardware in the world. A look at the recently introduced Mac Studio and M4 MacBook Air  show the company still has the ability to do that. Both are the best computers in the world in their class.

Challenges everywhere

But the central problem Apple has is mirrored in its own actions. 

You see, reports claim the company’s marketing teams insisted on promoting Apple Intelligence and its much-vaunted contextual understanding of users, even though the feature wasn’t ready. They not only insisted on it, but they also went large on pushing it, helping build just the right environment to create a crisis of belief when it was revealed the company would be unable to make the grade. (Subsequent reports suggest the feature is already working, but just not consistently enough; perhaps Apple should introduce it as a public beta to show how far it’s come.)

What problem does this mirror? 

Just as Apple’s own teams focused on a service that wasn’t ready, the rest of us out here continue to seek solace in impossible dreams. We live in a world of confusion in which populists, snake oil salesmen, and fake thought leaders thrive. Lack of belief, combined with a search for easy answers, means we choose the answers that seem easy. That’s what happened with Apple Intelligence — so great was the need to seem to occupy space in AI, the company chose to market a feature it hadn’t got working yet. 

It took an easy road, rather than a hard one, and in doing so reflected the muddy waters of our times.

That’s not how things were when Jobs introduced the iMac, iPod, or iPhone. Back then, we thought tech would help us, social media hadn’t yet been weaponized against wider public good, and many still wanted to believe global governments would meet the goals of Agenda 21, rather than using 1984 as an instruction manual. Conflict hadn’t yet exposed the deep rifts underlying the fragile global consensus, and Apple under Jobs spoke a language of hope and optimism that reflected a more optimistic zeitgeist. 

Apple today can’t cling to that past. 

A new language for a new time

That aspect of the brand no longer seems to match the existence so many of its customers experience. And it’s arguable whether senior management, ensconced in the Silicon Valley bubble, is exposed enough to identify a product design and marketing language that resonates in our new, highly complex, polarized, conflicted reality. While Apple has done extraordinarily well as the ultimate aspirational brand and enthusiasm for its products will remain among those who can reasonably afford them. But declining sales means declining profits, and in a world set up to mirror Wall Street’s irrational belief that perpetual growth is possible on a finite planet, decline is unacceptable.

That’s true even for the most successful company in human history.

That’s a lot of pressure for Apple’s top brass to handle. Plus, of course, in every case, the answers they have available to them appear to be least-worse responses, rather than good ones. Adding additional complexity, the challenges are themselves intertwined as societies everywhere undergo significant structural change, as political forces of various hues attempt to hold things together with false narratives of a history that never really happened. 

Just how can the future look better tomorrow when it’s based on a past that never existed? 

The journey

All the same, the more complex things become, the harder we work just to stand still. And with myriad connected challenges, it’s not at all certain even Steve Jobs would be able to visualize an easy way through. The simple answer is to keep hope alive, but the uncomfortable truth is that, just as it did with the iMac, Apple’s biggest challenge now is to find a consumer product truly emblematic of its time, something that speaks to us of who are we, what we need, and where we are going. 

In that light, perhaps the failure of the launch of Apple Intelligence really reflects the time we’re in. We can see the mountain but can’t yet make it to the top.

You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

By Siôn Geschwindt Irish startup Equal1 has unveiled the world’s first quantum computer that runs on a hybrid quantum-classical silicon chip.  Dubbed Bell-1 — after quantum physicist John Stewart Bell — the computer weighs around 200kg and plugs into a regular electrical socket. The rack-mountable machine is designed to simply slot into high-performance computing (HPC) data centres alongside standard servers.  Equal1’s CEO Jason Lynch told TNW that combining quantum technology with today’s most advanced classical processors offers the fastest route to a quantum computer capable of potentially world-changing calculations.  The potential applications are endless. Quantum computers have the potential to solve complex problems…This story continues at The Next Web

Source:: The Next Web

By Deepti Pathak Snapchat is filled with slang, abbreviations, and sometimes confusing symbols, particularly if unfamiliar. One of those…
The post ONG Meaning on Snapchat Explained: Use Cases & Examples appeared first on Fossbytes.

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By Hisan Kidwai The newest iteration of the WWE 2K franchise is finally here, giving players the chance to…
The post WWE 2K25 Locker Codes (March 2025) appeared first on Fossbytes.

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Imagine a world of the near future where Android and Apple iOS users can message one another with the certainty that their communication is secured against eavesdropping by end-to-end encryption (E2EE).

And it would not only be for one-to-one chats, but across large groups of employees and users, something that is impossible to guarantee today without resorting to standalone apps such as WhatsApp.

These capabilities might soon be a reality, thanks to a technical specification released this week, the GSM Association’s RCS Universal Profile version 3.0.

In development since 2007 as a replacement for SMS, Rich Communication Services (RCS) already allows a range of features including read receipts, typing indicators, and media sharing. But E2EE security, a much more complex technical feat, has always proved elusive.

Thanks to some IETF-backed magic inside RCS 3.0 called the Messaging Layer Security (MLS) protocol, that is about to change. Specifications may come and go, but history suggests that the addition of security to a spec is always a significant moment when people start to feel more positive about its adoption; at least that’s what the GSMA is hoping.

This is especially true for businesses, which value two features above all: absolute certainty about messaging security, and the ability for employees to communicate in large groups. RCS 3.0 with MLS delivers on both fronts, said GSMA technical director, Tom Van Pelt.

“[This ensures] that messages and other content such as files remain confidential and secure as they travel between clients,” he said.

“RCS will be the first large-scale messaging service to support interoperable E2EE between client implementations from different providers. Together with other unique security features such as SIM-based authentication, E2EE will provide RCS users with the highest level of privacy and security for stronger protection from scams, fraud, and other security and privacy threats,” said Van Pelt.

RCS fragmentation

RCS 3.0’s big feature is interoperability, which makes it easier for different apps to implement the same features consistently.  Today, while RCS is widely implemented by OS platforms, mobile networks, and device makers, each does it in their own way. This has led to fragmentation, hindering uptake. 

The result is that if you want to send a secure RCS message between Android devices, you need to use Google’s own Messages app at both ends; it implements E2EE using the well-worn Signal protocol. Similarly, Apple adopted RCS in iMessage last year, but with a proprietary implementation of E2EE.

In short, it’s a confusing jumble. This is one reason why alternatives such as WhatsApp and Signal, both of which also use the Signal protocol, have become so popular; you get E2EE out of the box without compatibility worries, and they allow groups of up to 1,024 members.

Having a single protocol, MLS, covering E2EE changes the story. Now RCS with MLS can offer a range of advanced features including large groups, which are critical for businesses which need many-to-many communication. Right now, if even one user in a group is using an RCS app without compatible E2EE, the security of the whole group chat can be compromised. MLS gives every app maker one IETF standard to aim for.

The WhatsApp effect

Google has said it plans to adopt MLS inside Messages, which means replacing the proven Signal protocol that struggles to handle larger groups. That will take time, during which it will probably support one with a fallback to the other. Apple, too, said it is committed to MLS.

“We will add support for end-to-end encrypted RCS messages to iOS, iPadOS, macOS, and watchOS in future software updates,” said Apple spokesperson Shane Bauer, in support of the GSMA.

As the two biggest platform apps, these names are important. However, one that’s not on the RCS list yet is WhatsApp, an app for both Android and Apple that, with three billion users, operates in a parallel world to RCS-enabled apps.

WhatsApp is in no hurry to adopt MLS. For parent Meta, the real prize is to turn WhatsApp into a secure business communications platform that dominates the messaging space across multiple types of engagement. Despite that, it will eventually have to adopt MLS in some form, not least to comply with the EU’s Digital Markets Act, which mandates greater app interoperability.

“It’s questionable if and when WhatsApp and Signal are going to support this protocol, as both have already implemented end-to-end encryption within each respective ecosystem,” commented Arne Möhle, CEO of secure email provider Tuta Mail.

“As an encrypted email service, we can also say that interoperability is a challenge,” he added. “It comes with complications such as spam and phishing attempts, an issue that WhatsApp has had to fight hard against. This will get even worse once the app starts allowing people to chat with their friends on other platforms as well.”

But E2EE was only today’s privacy issue. Soon, he predicted, messaging platforms will need to evolve to counter the ability of quantum computers to undermine the security of public key encryption.

“The GSMA protocol needs to be updated with quantum-resistant encryption keys,” said Möhle.

Ironically, a major uncertainty is E2EE itself. This is now being probed by the UK government, which has decided to use Apple as its test case in a campaign to introduce backdoors into the encryption used in iCloud services. So far, Apple is resisting, choosing to disable security rather than allow surveillance. Talks are reportedly ongoing.

E2EE, which stores keys on devices rather than centrally, isn’t part of this effort, but might come under fire if the UK government reheats its controversial idea of client-side scanning (scanning messages before they are encrypted on-device).

Source:: Computer World

By Siôn Geschwindt Baby Elon Musk. Shrimp Jesus. The Titanic colliding with an iceberg lettuce. Social media is saturated with AI slop — low-quality, often ridiculous and sometimes disturbing images, videos, or words created using generative artificial intelligence.  While some AI slop is glaringly fake, a lot isn’t. I remember the first time AI hoodwinked me. It was a striking video I saw on Instagram of a pair of snowy owls in the Arctic with a brood of six little chicks. Amazed by the scene, I instantly shared it with my wife. Her response was: “Surely that can’t be real?!”  It wasn’t. A…This story continues at The Next WebOr just read more coverage about: Instagram

Source:: The Next Web

By Thomas Macaulay A new startup called Skylark has taken flight today — with TNW lending an extra set of wings. The company launches with a central mission: empowering non-technical founders to quickly create high-quality Minimum Viable Products (MVPs). To bring their plans to life, Skylark has created an AI-enhanced framework that promises rapid, efficient iteration cycles. Freelance developers apply the framework to build the MVP. While they code, Skylark’s internal team handles the client acquisition. Every solution is customised for the founder’s objectives. By drawing from a pool of freelancers, Skylark can then find developers that fit each project’s specific needs.  The…This story continues at The Next Web

Source:: The Next Web

In the past month and a half, the Trump Administration has drastically reduced the federal government workforce.

The cuts alone have generated concern and anger among workers and those who rely on US government services. Adding to the angst: a new concern that government employees could be fired by an algorithm, as engineers modify a legacy reduction-in-force (RIF) software program to assist in their efforts, according to Abigail Kunkler, a law fellow with the nonprofit Electronic Privacy Information Center (EPIC).

Kunkler referenced a February article by Wired citing unnamed sources who told it the unofficial Department of Government Efficiency (DOGE) was retooling AutoRIF software to assist in deciding which employees to lay off. (Wired’s sources reported that most layoffs to that point had been determined manually.)

The day after the article was published, the US Office of Personnel Management ordered agencies to submit RIF plans and file them with the Office of Management and Budget (OMB). 

While not an actual federal department, DOGE is a government entity created by President Donald J. Trump with the self-stated mission of reducing waste, fraud, and abuse. To date, DOGE’s efforts have affected 18 federal agencies with layoffs or buyouts. While the exact number of federal job cuts in 2025 remains unclear, reports estimate there have been roughly 222,000 layoffs so far, with more expected as agencies implement budget cuts.

Driven by the government cuts, US layoffs surged 245% in February, according to Reuters.

“It is not clear how AutoRIF has been modified or whether AI is involved in the RIF mandate (through AutoRIF or independently),” Kunkler wrote in a blog post. “However, fears of AI-driven mass-firings of federal workers are not unfounded. Elon Musk and the Trump Administration have made no secret of their affection for the dodgy technology and their intentions to use it to make budget cuts. And, in fact, they have already tried adding AI to workforce decisions.”

Proponents of automated decision-making software claim it improves efficiency and reduces risks of mismanagement and discrimination. However, its use raises concerns about bias, surveillance, and lack of transparency, Kunkler said. The tools often perpetuate bias due to flawed information, such as incomplete or discriminatory historical data, and can lead to arbitrary or discriminatory decisions, potentially violating workers’ rights and laws like Title VII of the Civil Rights Act of 1964.

The creep of worker data collection, surveillance, rating systems, and automated decision-making is called “algorithmic management.” DOGE’s attempts to use a large language model (LLM) to cull “unnecessary” workers is a form of algorithmic management and automated decision-making, Kunlkler said.  

AutoRIF, developed by the Department of Defense more than 20 years ago, helps agencies manage workforce reductions. Wired reported that DOGE operatives have been editing its code, with updates made recently through a repository in the Office of Personnel Management’s GitHub, managed by Musk associates after Trump took office. However, a review of that GitHub site contained no “public” repositories.

Efforts to contact and/or get comment from the White House, DOGE, the DOGE Caucus or the Office of Personnel Management were unsuccessful.

“Federal employers using automated decision-making tools sharply reduces transparency for workers and their representatives,” Kunkler said. “There is often no insight into how the tool works, what data it is being fed, or how it is weighing different data in its analysis. The logic behind a given decision is not accessible to the worker and, in the government context, it is near impossible to know how or whether the tool is adhering to the statutory and regulatory requirements a federal employment tool would need to follow.”

Source:: Computer World

Expired certificates have recently caused a lot of chaos, including for Chromecast users. With that in mind, Mozilla is now urging all Firefox users to immediately update the browser to the latest version.

The reason: an older certificate expires on Friday, which means users who have not updated for a long time could be in trouble. According to Bleeping Computer, this means warnings about stolen passwords and malicious websites can no longer be displayed.

Firefox isn’t the only browser affected; others that use the same certificate include Tor, Librewolf and Waterfox.

Source:: Computer World

By Chris Chinchilla When the modern-day internet began emerging in the early 2000s, finding hosting services and resources to run the new wave of dynamic web applications was hard. You needed a database to store application data. These were slow, expensive, and unreliable, regularly bringing applications to a grinding halt when a single instance failed. You needed a server to run interpreted languages like PHP, Python, or Ruby. These were equally expensive, often needed configuration, had security issues, and frequently ran out of memory or CPU resources, again bringing applications to a grinding halt. For anyone on a small budget, running web 2.0-era…This story continues at The Next Web

Source:: The Next Web