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{Updated} You need to use the dpkg command or apt-get command/apt command, which is a package manager from shell/command prompt under a Debian and Ubuntu Linux. You can use this tool to install, build, remove and manage packages. The dpkg itself is controlled entirely via command line parameters. Let us see how to install .deb package file in Ubuntu Linux using the CLI.The post How Do I install .deb Packages in Ubuntu Linux Using the CLI or GUI? appeared first on nixCraft. 2023-07-27T11:31:00Z 2023-07-27T11:31:00Z Vivek Gite

Am I using X11 (Xorg) or Wayland? Here is how to check for Wayland or Xorg (X11) Linux desktops using the CLI and GUI options. Love this? sudo share_on: Twitter - Facebook - LinkedIn - Whatsapp - Reddit The post How to check for Wayland or Xorg (X11) Linux desktop appeared first on nixCraft. 2023-07-25T02:29:20Z 2023-07-25T02:29:20Z Vivek Gite

Let us see how to check for ssh connectivity in a shell script running under macOS, FreeBSD, or Linux/Unix desktop using BatchMode=yes and ConnectTimeout=$VALUE options. This simple trick helps write a wrapper script that does other things, such as making a backup or running external command agents such as Salt or Ansible to do other tasks. Love this? sudo share_on: Twitter - Facebook - LinkedIn - Whatsapp - Reddit The post How to check for ssh connectivity in a shell script appeared first on nixCraft. 2023-07-23T15:43:02Z 2023-07-23T15:43:02Z Vivek Gite

Debian Linux project announces the first update of the Debian project's stable distribution, Debian 12 (codename "bookworm") named Debian 12.1. This update mainly addresses security issues and significant problems. Security advisories have been published and are now available to download. Love this? sudo share_on: Twitter - Facebook - LinkedIn - Whatsapp - Reddit The post Debian Linux 12.1 released with Security Updates appeared first on nixCraft. 2023-07-23T09:30:01Z 2023-07-23T09:30:01Z Vivek Gite

Red Hat launched the Ansible Lightspeed Code Assistant Generative AI with IBM Watson Code Assistant in May 2023. This preview is now available to all Ansible users, allowing them to explore the technology, provide feedback to Red Hat, and further train the AI model. In this brief blog post, I will share my personal experience with installing and utilizing Ansible Lightspeed AI to create playbooks in VSCode using Ubuntu Linux 20.04 LTS desktop. Love this? sudo share_on: Twitter - Facebook - LinkedIn - Whatsapp - Reddit The post Setting up VSCode for Ansible Lightspeed AI in Ubuntu 22.04 desktop appeared first on nixCraft. 2023-07-22T14:01:07Z 2023-07-22T14:01:07Z Vivek Gite

This week the Washington Post noted that just last year nearly 1.2 million more electric vehicles were sold in America, "accounting for over 7 percent of total new car sales and a new national record." But "data show that EV sales are far outpacing growth in the U.S. charging network... In 2016, there were seven electric cars for each public charging point; today, there's more than 20 electric cars per charger." The article points out that 80% of America's EV's are just charging at home, according to the U.S. Energy Department. (Which seems to leave one public charger for every four EVs that don't charge at home.) And the article notes several other important caveats: Experts say that there is no "magic number" for the best ratio of EVs on the road to public chargers. "It absolutely depends on the local landscape," said Peter Slowik, U.S. passenger vehicles lead for the International Council on Clean Transportation. Globally, there is about 1 public charger for every 11 EVs, according to the International Energy Agency. But in countries where there are more single-family homes and garages, the ratio could be lower.... In a way, the United States' slow charging build-out could be a benefit in the long-term: Many automakers have now promised to switch to Tesla's charging connector in the next few years, which could help put most cars on the same system. Not everyone agrees there is a delay. Slowik says that his team's research shows that the United States is on-track for building out the charging needed over the next eight years. An increase in the number of EVs per public charger is a natural part of the adoption process, he argues, that will subside with more sales and as more chargers come online. Still, the article argues if Americans continue buying electric cars, public chargers will be essential "to support long road trips, help apartment-dwellers go electric and alleviate overnight pressure on electricity grids." Today U.S. Transportation Secretary Pete Buttigieg reiterated America's commitment to having a national network of 500,000 charges by 2030, saying the country is at "the absolute very, very beginning stages of the construction to come."

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"64% of Americans live within 2 miles of a public charging station," Pew Research reported this week, citing a survey paired with an analysis of U.S. Energy Department data that found over 61,000 publicly accessible charging stations. And those who live closest to public chargers "view EVs more positively." The vast majority of EV charging occurs at home, but access to public infrastructure is tightly linked with Americans' opinions of electric vehicles themselves. Our analysis finds that Americans who live close to public chargers view EVs more positively than those who are farther away. Even when accounting for factors like partisan identification and community type, Americans who live close to EV chargers are more likely to say they: - Already own an electric or hybrid vehicle - Would consider buying an EV for their next vehicle - Favor phasing out production of new gasoline cars and trucks by 2035 - Are confident that the U.S. will build the necessary infrastructure to support large numbers of EVs on the roads The number of EV charging stations has more than doubled since 2020. In December 2020, the Department of Energy reported that there were nearly 29,000 public charging stations nationwide. By February 2024, that number had increased to more than 61,000 stations. Over 95% of the American public now lives in a county that has at least one public EV charging station. EV charging stations are most accessible to residents of urban areas: 60% of urban residents live less than a mile from the nearest public EV charger, compared with 41% of those in the suburbs and just 17% of rural Americans. California is home to about 25% of all of America's charging stations, according to the report. But this means EV-owning Californians "might also have a harder time than residents of many states when it comes to the actual experience of finding and using a charger." Despite having the most charging stations of any state, California's 43,780 individual public charging ports must provide service for the more than 1.2 million electric vehicles registered to its residents. That works out to one public port for every 29 EVs, a ratio that ranks California 49th across all 50 states and the District of Columbia. At the other end of the spectrum, Wyoming (one-to-six), North Dakota (one-to-six) and West Virginia (one-to-eight) have the most ports relative to the much smaller number of EVs registered in their respective states. Another interesting finding? "Attitudes toward EVs don't differ that much based on how often people take long car trips. "In fact, those who regularly drive more than 100 miles are slightly more likely to say they currently own an electric vehicle or hybrid — and also to say they'd consider purchasing an EV in the future — when compared with those who make these trips less often."

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Will Major League Baseball games use "automated" umpires next year to watch pitches from home plate and call balls and strikes? "We still have some technical issues," baseball Commissioner Rob Manfred said Thursday. NBC News reports: "We haven't made as much progress in the minor leagues this year as we sort of hoped at this point. I think it's becoming more and more likely that this will not be a go for '25." Major League Baseball has been experimenting with the automated ball-strike system in minor leagues since 2019. It is being used at all Triple-A parks this year for the second straight season, the robot alone for the first three games of each series and a human with a [robot-assisted] challenge system in the final three. In "challenge-system" games, robo-umpires are only used for quickly ruling on challenges to calls from human umpires. (As demonstrated in this 11-second video.) CBS Sports explains: Each team is given a limited number of "incorrect" challenges per game, which incentivizes judicious use of challenges... In some ways, the challenge system is a compromise between the traditional method of making ball-strike calls and the fully automated approach. That middle ground may make approval by the various stakeholders more likely to happen and may lay the foundation for full automation at some future point. Manfred cites "a growing consensus in large part" from Major League players that that's how they'd want to see robo-umpiring implemented, according to a post on X.com from The Athletic's Evan Drellich. (NBC notes one concern is eliminating the artful way catchers "frame" caught pitches to convince umpires a pitch passed through the strike zone.) But umpires face greater challenges today, adds CBS Sports: The strong trend, stretching across years, of increased pitch velocity in the big leagues has complicated the calling of balls and strikes, as has the emphasis on high-spin breaking pitches. Discerning balls from strikes has always been challenging, and the stuff of the contemporary major-league pitcher has made anything like perfect accuracy beyond the capabilities of the human eye. Big-league umpires are highly skilled, but the move toward ball-strike automation and thus a higher tier of accuracy is likely inevitable. Manfred's Wednesday remarks reinforce that perception.

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Linux 6.10-rc1 Kernel Released With Many New Features  Phoronix

Linus Torvalds Announces First Linux Kernel 6.10 Release Candidate  9to5Linux

"Merged this Friday evening into the Linux 6.10 kernel is the new mseal() system call for memory sealing," reports Phoronix: The mseal system call was led by Jeff Xu of Google's Chrome team. The goal with memory sealing is to also protect the memory mapping itself against modification. The new mseal Linux documentation explains: "Modern CPUs support memory permissions such as RW and NX bits. The memory permission feature improves security stance on memory corruption bugs, i.e. the attacker can't just write to arbitrary memory and point the code to it, the memory has to be marked with X bit, or else an exception will happen. Memory sealing additionally protects the mapping itself against modifications. This is useful to mitigate memory corruption issues where a corrupted pointer is passed to a memory management system... Memory sealing can automatically be applied by the runtime loader to seal .text and .rodata pages and applications can additionally seal security-critical data at runtime. A similar feature already exists in the XNU kernel with the VM_FLAGS_PERMANENT flag and on OpenBSD with the mimmutable syscall." The mseal system call is designed to be used by the likes of the GNU C Library "glibc" while loading ELF executables to seal non-writable memory segments or by the Google Chrome web browser and other browsers for protecting security sensitive data structures.

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"Merged this Friday evening into the Linux 6.10 kernel is the new mseal() system call for memory sealing," reports Phoronix: The mseal system call was led by Jeff Xu of Google's Chrome team. The goal with memory sealing is to also protect the memory mapping itself against modification. The new mseal Linux documentation explains: "Modern CPUs support memory permissions such as RW and NX bits. The memory permission feature improves security stance on memory corruption bugs, i.e. the attacker can't just write to arbitrary memory and point the code to it, the memory has to be marked with X bit, or else an exception will happen. Memory sealing additionally protects the mapping itself against modifications. This is useful to mitigate memory corruption issues where a corrupted pointer is passed to a memory management system... Memory sealing can automatically be applied by the runtime loader to seal .text and .rodata pages and applications can additionally seal security-critical data at runtime. A similar feature already exists in the XNU kernel with the VM_FLAGS_PERMANENT flag and on OpenBSD with the mimmutable syscall." The mseal system call is designed to be used by the likes of the GNU C Library "glibc" while loading ELF executables to seal non-writable memory segments or by the Google Chrome web browser and other browsers for protecting security sensitive data structures.

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"While general-purpose languages like Python, C++, and Java remain popular in AI development," writes VentureBeat, "the resurgence of AI-first languages signifies a recognition that AI's unique demands require specialized languages tailored to the domain's specific needs... designed from the ground up to address the specific needs of AI development." Bend, created by Higher Order Company, aims to provide a flexible and intuitive programming model for AI, with features like automatic differentiation and seamless integration with popular AI frameworks. Mojo, developed by Modular AI, focuses on high performance, scalability, and ease of use for building and deploying AI applications. Swift for TensorFlow, an extension of the Swift programming language, combines the high-level syntax and ease of use of Swift with the power of TensorFlow's machine learning capabilities... At the heart of Mojo's design is its focus on seamless integration with AI hardware, such as GPUs running CUDA and other accelerators. Mojo enables developers to harness the full potential of specialized AI hardware without getting bogged down in low-level details. One of Mojo's key advantages is its interoperability with the existing Python ecosystem. Unlike languages like Rust, Zig or Nim, which can have steep learning curves, Mojo allows developers to write code that seamlessly integrates with Python libraries and frameworks. Developers can continue to use their favorite Python tools and packages while benefiting from Mojo's performance enhancements... It supports static typing, which can help catch errors early in development and enable more efficient compilation... Mojo also incorporates an ownership system and borrow checker similar to Rust, ensuring memory safety and preventing common programming errors. Additionally, Mojo offers memory management with pointers, giving developers fine-grained control over memory allocation and deallocation... Mojo is conceptually lower-level than some other emerging AI languages like Bend, which compiles modern high-level language features to native multithreading on Apple Silicon or NVIDIA GPUs. Mojo offers fine-grained control over parallelism, making it particularly well-suited for hand-coding modern neural network accelerations. By providing developers with direct control over the mapping of computations onto the hardware, Mojo enables the creation of highly optimized AI implementations. According to Mojo's creator, Modular, the language has already garnered an impressive user base of over 175,000 developers and 50,000 organizations since it was made generally available last August. Despite its impressive performance and potential, Mojo's adoption might have stalled initially due to its proprietary status. However, Modular recently decided to open-source Mojo's core components under a customized version of the Apache 2 license. This move will likely accelerate Mojo's adoption and foster a more vibrant ecosystem of collaboration and innovation, similar to how open source has been a key factor in the success of languages like Python. Developers can now explore Mojo's inner workings, contribute to its development, and learn from its implementation. This collaborative approach will likely lead to faster bug fixes, performance improvements and the addition of new features, ultimately making Mojo more versatile and powerful. The article also notes other languages "trying to become the go-to choice for AI development" by providing high-performance execution on parallel hardware. Unlike low-level beasts like CUDA and Metal, Bend feels more like Python and Haskell, offering fast object allocations, higher-order functions with full closure support, unrestricted recursion and even continuations. It runs on massively parallel hardware like GPUs, delivering near-linear speedup based on core count with zero explicit parallel annotations — no thread spawning, no locks, mutexes or atomics. Powered by the HVM2 runtime, Bend exploits parallelism wherever it can, making it the Swiss Army knife for AI — a tool for every occasion... The resurgence of AI-focused programming languages like Mojo, Bend, Swift for TensorFlow, JAX and others marks the beginning of a new era in AI development. As the demand for more efficient, expressive, and hardware-optimized tools grows, we expect to see a proliferation of languages and frameworks that cater specifically to the unique needs of AI. These languages will leverage modern programming paradigms, strong type systems, and deep integration with specialized hardware to enable developers to build more sophisticated AI applications with unprecedented performance. The rise of AI-focused languages will likely spur a new wave of innovation in the interplay between AI, language design and hardware development. As language designers work closely with AI researchers and hardware vendors to optimize performance and expressiveness, we will likely see the emergence of novel architectures and accelerators designed with these languages and AI workloads in mind. This close relationship between AI, language, and hardware will be crucial in unlocking the full potential of artificial intelligence, enabling breakthroughs in fields like autonomous systems, natural language processing, computer vision, and more. The future of AI development and computing itself are being reshaped by the languages and tools we create today. In 2017 Modular AI's founder Chris Lattner (creator of the Swift and LLVM) answered questions from Slashdot readers.

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Malaysia Airlines Flight 370 vanished in 2014 — and efforts continue to find it. In 2018 a UK-based video producer claimed to have discovered the crashed aircraft on Google Maps — but Newsweek pointed out the same wreckage "is visible in imagery dating back to January 1, 2004 — more than a decade before MH370 disappeared." Marine robotics company Ocean Infinity also failed to find the aircraft after a five-month search in 2018 — but has returned to the headlines this March, writes the Independent, "claiming that they have scientific evidence" for the flight's final resting place. (The company's CEO says the last six years they've been "innovating with technology and robotics to further advance our ocean search capabilities.") And this week Indian Express reported that researchers from the UK's Cardiff University investigating the mystery "have come up with a novel plan to unravel it — sea explosions." More from the Economic Times: Scientists have said that airplanes crashing over oceans create unique acoustic signatures that can travel more than 3,000km through water. These acoustic signatures can be recorded by a network of 11 hydroacoustic stations worldwide that are dotted along the seabed. Researchers at Cardiff University have said that a series of controlled underwater explosions or air gunfire along the 7th arc [where the plane last communicated] can be done to see whether they can isolate a more precise location for MH370. More details from NDTV: "[W]ithin the time frame and location suggested by the official search, only a single, relatively weak signal was identified,'' Dr Kadri said... ''Similar exercises were performed in the search and rescue mission for the ARA San Juan, a submarine that vanished off the coast of Argentina in 2017. This shows us that it is relatively straightforward and feasible and could provide a means to determine the signal's relevance to MH370, prior to resuming with another extensive search. If found to be related, this would significantly narrow down, almost pinpoint, the aircraft's location,'' Dr Kadri added... Despite the largest search in aviation history, the plane has never been found. An announcement from Cardiff University adds that "The experiments would also help develop the use of hydroacoustic technology as a tool for authorities to draw upon when narrowing down potential crash locations for airplanes in the future."

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Space.com calls it a movie "adding more combustible material to the inferno of AI unease sweeping the globe." Its director tells them James Cameron was a huge inspiration, saying Atlas "has an Aliens-like vibe because of the grounded, grittiness to it." (You can watch the movie's trailer here...) But Tom's Guide says "the reviews are just as shocking as the movie's AI." Its "audience score" on Rotten Tomatoes is 55% — but its aggregate score from professional film critics is 16%. The Hollywood Reporter called it "another Netflix movie to half-watch while doing laundry." ("The star plays a data analyst forced to team up with an AI robot in order to prevent an apocalypse orchestrated by a different AI robot...") The site Giant Freakin Robot says "there seems to be a direct correlation between how much money the streaming platform spends on green screen effects and how bad the movie is" (noting the film's rumored budget of $100 million)... But Tom's Guide defends it as a big-budget sci-fi thriller that "has an interesting premise that makes you think about the potential dangers of AI progression." Our world has always been interested in computers and machines, and the very idea of technology turning against us is unsettling. That's why "Atlas" works as a movie, but professional critics have other things to say. Ross McIndoe from Slant Magazine said: "Atlas seems like a story that should have been experienced with a gamepad in hand...." Todd Gilchrist from Variety didn't enjoy the conventional structure that "Atlas" followed... However, even though the score is low and the reviews are pretty negative, I don't want to completely bash this movie... If I'm being completely honest, most movies and TV shows nowadays are taken too seriously. The more general blockbusters are supposed to be entertaining and fun, with visually pleasing effects that keep you hooked on the action. This is much like "Atlas", which is a fun watch with an unsettling undertone focused on the dangers of evolving AI... Being part of the audience, we're supposed to just take it in and enjoy the movie as a casual viewer. This is why I think you should give "Atlas" a chance, especially if you're big into dramatic action sequences and have enjoyed movies like "Terminator" and "Pacific Rim".

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"The fact it's possible at all is a credit to the ingenuity of the open-source community," writes the blog OMG Ubuntu: Switchroot is an open-source project that allows Android and Linux-based distros like Ubuntu to run on the Nintendo Switch — absolutely not something Nintendo approves of much less supports, endorses, or encourages, etc! I covered the loophole that made this possible back in 2018. Back then the NVIDIA Tegra X1-powered Nintendo Switch was still new and Linux support for much of the console's internal hardware in a formative state (a polite way to say 'not everything worked'). But as the popularity of Nintendo's handheld console ballooned (to understate it) so the 'alternative OS' Switch scene grew, and before long Linux support for Switch hardware was in full bloom... A number of Linux for Switchroot (L4S) distributions have since been released, designated as Linux for Tegra (L4T) builds. As these can boot from a microSD card it's even possible to dualboot the Switch OS with Linux, which is neat! Recently, a fresh set of L4T Ubuntu images were released based on the newest Ubuntu 24.04 LTS release. These builds work on all Switch versions, from the OG (exploit-friendly) unit through to newer, patched models (where a modchip is required)... I'm told all of the Nintendo Switch internal hardware now works under Linux, including Wi-Fi, Bluetooth, sleep mode, accelerated graphics, the official dock... Everything, basically. And despite being a 7 year old ARM device the performance is said to remain decent. "Upstream snafus have delayed the release of builds with GNOME Shell..."

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"The fact it's possible at all is a credit to the ingenuity of the open-source community," writes the blog OMG Ubuntu: Switchroot is an open-source project that allows Android and Linux-based distros like Ubuntu to run on the Nintendo Switch — absolutely not something Nintendo approves of much less supports, endorses, or encourages, etc! I covered the loophole that made this possible back in 2018. Back then the NVIDIA Tegra X1-powered Nintendo Switch was still new and Linux support for much of the console's internal hardware in a formative state (a polite way to say 'not everything worked'). But as the popularity of Nintendo's handheld console ballooned (to understate it) so the 'alternative OS' Switch scene grew, and before long Linux support for Switch hardware was in full bloom... A number of Linux for Switchroot (L4S) distributions have since been released, designated as Linux for Tegra (L4T) builds. As these can boot from a microSD card it's even possible to dualboot the Switch OS with Linux, which is neat! Recently, a fresh set of L4T Ubuntu images were released based on the newest Ubuntu 24.04 LTS release. These builds work on all Switch versions, from the OG (exploit-friendly) unit through to newer, patched models (where a modchip is required)... I'm told all of the Nintendo Switch internal hardware now works under Linux, including Wi-Fi, Bluetooth, sleep mode, accelerated graphics, the official dock... Everything, basically. And despite being a 7 year old ARM device the performance is said to remain decent. "Upstream snafus have delayed the release of builds with GNOME Shell..."

Read more of this story at Slashdot.

A Rust Foundation blog post begins by reminding readers that Rust programs "are unable to compile if memory management rules are violated, essentially eliminating the possibility of a memory issue at runtime." But then it goes on to explore "Unsafe Rust in the wild" (used for a small set of actions like dereferencing a raw pointer, modifying a mutable static variable, or calling unsafe functions). "At a superficial glance, it might appear that Unsafe Rust undercuts the memory-safety benefits Rust is becoming increasingly celebrated for. In reality, the unsafe keyword comes with special safeguards and can be a powerful way to work with fewer restrictions when a function requires flexibility, so long as standard precautions are used." The Foundation lists those available safeguards — which "make exploits rare — but not impossible." But then they go on to analyze just how much Rust code actually uses the unsafe keyword: The canonical way to distribute Rust code is through a package called a crate. As of May 2024, there are about 145,000 crates; of which, approximately 127,000 contain significant code. Of those 127,000 crates, 24,362 make use of the unsafe keyword, which is 19.11% of all crates. And 34.35% make a direct function call into another crate that uses the unsafe keyword [according to numbers derived from the Rust Foundation project Painter]. Nearly 20% of all crates have at least one instance of the unsafe keyword, a non-trivial number. Most of these Unsafe Rust uses are calls into existing third-party non-Rust language code or libraries, such as C or C++. In fact, the crate with the most uses of the unsafe keyword is the Windows crate, which allows Rust developers to call into various Windows APIs. This does not mean that the code in these Unsafe Rust blocks are inherently exploitable (a majority or all of that code is most likely not), but that special care must be taken while using Unsafe Rust in order to avoid potential vulnerabilities... Rust lives up to its reputation as an excellent and transformative tool for safe and secure programming, even in an Unsafe context. But this reputation requires resources, collaboration, and constant examination to uphold properly. For example, the Rust Project is continuing to develop tools like Miri to allow the checking of unsafe Rust code. The Rust Foundation is committed to this work through its Security Initiative: a program to support and advance the state of security within the Rust Programming language ecosystem and community. Under the Security Initiative, the Rust Foundation's Technology team has developed new tools like [dependency-graphing] Painter, TypoMania [which checks package registries for typo-squatting] and Sandpit [an internal tool watching for malicious crates]... giving users insight into vulnerabilities before they can happen and allowing for a quick response if an exploitation occurs.

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This week Red Hat announced one of America's leading pediatric hospitals is using AI to analyze X-rays, "to improve image quality and the speed and accuracy of image interpretation." Red Hat's CTO said the move exemplifies "the positive impact AI can have in the healthcare field". Before Boston Children's Hospital began piloting AI in radiology, quantitative measurements had to be done manually, which was a time-consuming task. Other, more complex image analyses were performed completely offline and outside of the clinical workflow. In a field where time is of the essence, the hospital is piloting Red Hat OpenShift via the ChRIS Research Integration Service, a web-based medical image platform. The AI application running in ChRIS on the Red Hat OpenShift foundation has the potential to automatically examine x-rays, identify the most valuable diagnostic images among the thousands taken and flag any discrepancies for the radiologist. This decreases the interpretation time for radiologists. But it also seems to be a big win for openness: Innovation developed internally is immediately transferable to public research clouds such as the Massachusetts Open Cloud, where large-scale data sharing and additional innovation can be fostered. Boston Children's Hospital aims to extend the reach of advanced healthcare solutions globally through this approach, amplifying their impact on patient well-being worldwide. "Red Hat believes open unlocks the world's potential," the announcement concludes, "including the potential to share knowledge and build upon each other's discoveries. Additionally, Red Hat believes innovation — including AI — should be available everywhere, making any application, anywhere a reality. "With open source, enabling AI-fueled innovation across hybrid IT environments that can lead to faster clinical breakthroughs and better patient outcomes is a reality."

Read more of this story at Slashdot.

This week Red Hat announced one of America's leading pediatric hospitals is using AI to analyze X-rays, "to improve image quality and the speed and accuracy of image interpretation." Red Hat's CTO said the move exemplifies "the positive impact AI can have in the healthcare field". Before Boston Children's Hospital began piloting AI in radiology, quantitative measurements had to be done manually, which was a time-consuming task. Other, more complex image analyses were performed completely offline and outside of the clinical workflow. In a field where time is of the essence, the hospital is piloting Red Hat OpenShift via the ChRIS Research Integration Service, a web-based medical image platform. The AI application running in ChRIS on the Red Hat OpenShift foundation has the potential to automatically examine x-rays, identify the most valuable diagnostic images among the thousands taken and flag any discrepancies for the radiologist. This decreases the interpretation time for radiologists. But it also seems to be a big win for openness: Innovation developed internally is immediately transferable to public research clouds such as the Massachusetts Open Cloud, where large-scale data sharing and additional innovation can be fostered. Boston Children's Hospital aims to extend the reach of advanced healthcare solutions globally through this approach, amplifying their impact on patient well-being worldwide. "Red Hat believes open unlocks the world's potential," the announcement concludes, "including the potential to share knowledge and build upon each other's discoveries. Additionally, Red Hat believes innovation — including AI — should be available everywhere, making any application, anywhere a reality. "With open source, enabling AI-fueled innovation across hybrid IT environments that can lead to faster clinical breakthroughs and better patient outcomes is a reality."

Read more of this story at Slashdot.