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GOG Officially Expands Linux Support With Native Galaxy Client In Development

3 weeks 2 days ago
Long-time Slashdot reader pyroclast shared this report from Linux Journal: After years of requests from the Linux gaming community, GOG has officially confirmed that it is developing native Linux support for the GOG Galaxy launcher. The announcement marks one of the biggest shifts in the company's history and signals a stronger commitment to Linux as a first-class gaming platform. While GOG has offered DRM-free Linux game downloads since 2014, its Galaxy launcher has remained exclusive to Windows and macOS — until now. Although the company has not announced a release date, GOG says Linux has become a major area of investment, with development already underway... Unlike the web-based game downloads that Linux users already have access to, GOG Galaxy serves as a full-featured game management application. The launcher currently offers features including: — Automatic game installation and updates — Cloud save synchronization — Achievement tracking — Playtime statistics — Game library organization — Integrated storefront browsing — Friends lists and social features — Cross-platform launcher integration Today, Linux users typically access these capabilities through community projects such as Heroic Games Launcher, Lutris, or Bottles. A native Galaxy client would provide an officially supported alternative with direct integration into GOG's ecosystem... For GOG, supporting Linux more fully aligns with its philosophy of giving users greater control over their purchased games. The article argues this news shows Linux growing in importance for game publishers. After the rapid adoption of Valve's Steam Deck, there's also been continuous improvements to Proton and Vulkan, increasing hardware compatibility, and native Linux game development efforts. "As more companies recognize the platform's growth, Linux users can expect broader support from game publishers and software developers alike."

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EditorDavid

IT Teams are Spending 11 Hours a Week on Cloud Connectivity Problems

3 weeks 2 days ago
Researchers found enterprises are spending time troubleshooting cloud connectivity due to increased AI workloads, reports Computer Weekly. More than 400 IT and infrastructure decision-makers (US and UK) were surveyed for internet/cloud/AI exchange operator DE-CIX by market researchers Censuswide. But despite 96% of respondents claiming their enterprise networks are ready for cloud/AI loads, the average IT team still spends more than 11 hours each week resolving cloud connectivity problems: Other leading concerns included downtime or reliability issues (26%), latency or slow performance (28%), and security vulnerabilities/DDoS attacks (27%). Cost of connectivity, staff expertise and lack of visibility/control over data flows were also cited as major challenges... As a result, as indicated in the study, many businesses are now turning to private interconnection, which enables enterprises to connect directly to cloud providers over dedicated infrastructure rather than routing traffic across the public Internet. Designed to deliver lower latency, greater resilience, enhanced security and more predictable performance, private interconnection has become an increasingly important way of supporting modern cloud and AI workloads. Specifically, the data showed that 61% of companies are already using private connectivity to clouds, while another 31% are actively considering it... [And 71% of enterprises with 1000 or more employees] Only 8.62% of the smaller companies were spending 21 to 40 hours per week dealing with connectivity issues, while just 2.53% of the largest companies in the sample do. Summing up these findings, DE-CIX said that together they suggest direct interconnection is rapidly becoming a core component of enterprise cloud and AI infrastructure and a competitive advantage for companies, though optimising interconnection strategies clearly remains a pressing challenge for small and medium-sized enterprises... "Every AI application depends on data moving quickly, securely and predictably between users, clouds and AI infrastructure. Our research suggests that far too many enterprises are still spending valuable time trying to maintain that kind of connectivity, with more than a third spending between 11 and 20 hours per week, and just under one in 10 spending between 21 to 40 hours per week. This confirms what we already knew — that that network architecture can make or break AI adoption." Elsewhere The Register reports that cloud infrastructure services "grew at their fastest for eight years during the second quarter of 2026, thanks to the AI craze and continued demand for flexible and scalable IT infrastructure." According to the latest figures from Synergy Research, enterprise spending on cloud infrastructure passed $143 billion in Q2, a year-on-year growth rate of 43 percent. This followed 11 successive quarters of increasing growth rates, during which the market has now doubled in size... "AI has, of course, driven most of that incremental growth, and we now see year-on-year growth rates of 165 percent for AI-specific cloud services...." And the top three global players continue to dominate the market, with Amazon Web Services (AWS), Microsoft Azure and Google Cloud together accounting for 67 percent of all the cloud revenue during the quarter. That percentage has increased since the third quarter of last year, when the triumvirate made up 63 percent of enterprise cloud infra spending.

Read more of this story at Slashdot.

EditorDavid

IT Teams Report 11 Hour a Week on Cloud Connectivity Problems

3 weeks 2 days ago
Researchers found enterprises are spending time troubleshooting cloud connectivity due to increased AI workloads, reports Computer Weekly. More than 400 IT and infrastructure decision-makers (US and UK) were surveyed for internet/cloud/AI exchange operator DE-CIX by market researchers Censuswide. But despite 96% of respondents claiming their enterprise networks are ready for cloud/AI loads, the average IT team still spends more than 11 hours each week resolving cloud connectivity problems Other leading concerns included downtime or reliability issues (26%), latency or slow performance (28%), and security vulnerabilities/DDoS attacks (27%). Cost of connectivity, staff expertise and lack of visibility/control over data flows were also cited as major challenges... As a result, as indicated in the study, many businesses are now turning to private interconnection, which enables enterprises to connect directly to cloud providers over dedicated infrastructure rather than routing traffic across the public Internet. Designed to deliver lower latency, greater resilience, enhanced security and more predictable performance, private interconnection has become an increasingly important way of supporting modern cloud and AI workloads. Specifically, the data showed that 61% of companies are already using private connectivity to clouds, while another 31% are actively considering it... [And 71% of enterprises with 1000 or more employees] Only 8.62% of the smaller companies were spending 21 to 40 hours per week dealing with connectivity issues, while just 2.53% of the largest companies in the sample do. Summing up these findings, DE-CIX said that together they suggest direct interconnection is rapidly becoming a core component of enterprise cloud and AI infrastructure and a competitive advantage for companies, though optimising interconnection strategies clearly remains a pressing challenge for small and medium-sized enterprises... "Every AI application depends on data moving quickly, securely and predictably between users, clouds and AI infrastructure. Our research suggests that far too many enterprises are still spending valuable time trying to maintain that kind of connectivity, with more than a third spending between 11 and 20 hours per week, and just under one in 10 spending between 21 to 40 hours per week. This confirms what we already knew — that that network architecture can make or break AI adoption." Elsewhere The Register reports that cloud infrastructure services "grew at their fastest for eight years during the second quarter of 2026, thanks to the AI craze and continued demand for flexible and scalable IT infrastructure." According to the latest figures from Synergy Research, enterprise spending on cloud infrastructure passed $143 billion in Q2, a year-on-year growth rate of 43 percent. This followed 11 successive quarters of increasing growth rates, during which the market has now doubled in size... "AI has, of course, driven most of that incremental growth, and we now see year-on-year growth rates of 165 percent for AI-specific cloud services...." And the top three global players continue to dominate the market, with Amazon Web Services (AWS), Microsoft Azure and Google Cloud together accounting for 67 percent of all the cloud revenue during the quarter. That percentage has increased since the third quarter of last year, when the triumvirate made up 63 percent of enterprise cloud infra spending.

Read more of this story at Slashdot.

EditorDavid

New Spinning Drone Hides In Plain Sight

3 weeks 2 days ago
To design invisible drones, researchers have tried camouflage, transparent materials and light-bending optical systems. But engineers at Northwestern University used "motion blur," which an announcement from the school notes is the effect that makes fast-spinning fans seem to disappear. "The drone spins up to 25 times per second, which is too fast for the human eye to see clearly. While it isn't completely invisible, it morphs into a ghostly smudge that seamlessly blends into the background... " To design the drone, the Northwestern team first used a computational model to generate roughly 20,000 drone configurations capable of stable flight. Then, they used artificial intelligence (AI) and optimization algorithms to repeatedly rearrange the drones' major components, including a motor, propeller, circuit board, counterweight and batteries. After sifting through many different configurations, the algorithms determined the ideal placement of the drone's components to minimize its visibility from virtually every viewing angle while allowing for stable flight. After selecting promising candidates, the engineers simulated each drone spinning in flight and overlaid those images a hundred real-world backgrounds. Then, they used a perception model that approximates human vision to determine how noticeable each design appeared. Designs that blended into their surroundings received lower visibility scores. The team selected the 500 lowest-scoring designs and applied the optimization algorithm, which repeatedly adjusted the positions of components to further minimize those scores. "The design process was fully automated," [said Northwestern's associate CS professor Michael Rubenstein, who led the work]. "Then, when we were confident that a drone met all our criteria, we built it." They've named the drone "Phantom Twist"," and plan to design future iterations with more transparent materials or quieter propulsion to make it even less noticeable. The Northwestern team presented the work on July 16 at Robotics: Science and Systems 2026 in Sydney, Australia... Thanks to long-time Slashdot reader fahrbot-bot for sharing the news.

Read more of this story at Slashdot.

EditorDavid