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Hello and welcome to another update on what’s been happening at the GNOME Foundation. It’s been two weeks since my last update, and there’s been plenty going on, so let’s dive straight in.

GNOME 50!

My update wouldn’t be complete without mentioning this week’s GNOME 50 release. It looks like an amazing release with lots of great improvements! Many thanks to everyone who contributed and made it such a success.

The Foundation plays a critical role in these releases, whether it’s providing development infrastructure, organising events where planning takes place, or providing development funding. If you are reading this and have the means, please consider signing up as a Friend of GNOME. Even small regular donations make a huge difference.

Board Meeting

The Board of Directors had its regular monthly meeting on March 9th, and we had a full agenda. Highlights from the meeting included:

• The Board agreed to sign the Keep Android Open letter, as well as endorsing the United Nations Open Source Principles.
• We heard reports from a number of committees, including the Executive Committee, Finance Committee, Travel Committee, and Code of Conduct Committee. Committee presentations are a new addition to the Board meeting format, with the goal of pushing more activity out to committees, with the Board providing high-level oversight and coordination.
• Creation of a new bank account was authorized, which is needed as part of our ongoing finance and accounting development effort.
• The main discussion topic was Flathub and what the organizational arrangements could be for it in the future. There weren’t any concrete decisions made here, but the Board indicated that it’s open to different options and sees Flathub’s success as the main priority rather than being attached to any particular organisation type or location.
• The next regular Board meeting will be on April 13th.

Travel

The Travel Committee met both this week and last week, as it processed the initial batch of GUADEC sponsorship applications. As a result of this work the first set of approvals have been sent out. Documentation has also been provided for those who are applying for visas for their travel.

The membership of the current committee is quite new and it is having to figure out processes and decision-making principals as it goes, which is making its work more intensive than might normally be the case. We are starting to write up guidelines for future funding rounds, to help smooth the process.

Huge thanks to our committee members Asmit, Anisa, Julian, Maria, and Nirbeek, for taking on this important work.

Conferences

Planning and preparation for the 2026 editions of LAS and GUADEC have continued over the past fortnight. The call for papers for both events is a particular focus right now, and there are a couple of important deadlines to be aware of:

• If you want to speak at LAS 2026, the deadline for proposals is 23 March – that’s in just three days.
• The GUADEC 2026 call for abstracts has been extended to 27 March, so there is one more week to submit a talk.

There are teams behind each of these calls, reviewing and selecting proposals. Many thanks to the volunteers doing this work!

We are also excited to have sponsors come forward to support GUADEC.

Accounting

The Foundation has been undertaking a program of improvements to our accounting and finance systems in recent months. Those were put on hold for the audit fieldwork that took place at the beginning of March, but now that’s done, attention has turned to the remaining work items there.

We’ve been migrating to a new payments processing platform since the beginning of the year, and setup work has continued, including configuration to make it integrate correctly with our accounting software, migrating credit cards over from our previous solution, and creating new web forms which are going to be used for reimbursement requests in future.

There are a number of significant advantages to the new system, like the accounting integration, which are already helping to reduce workloads, and I’m looking forward to having the final pieces of the new system in place.

Another major change that is currently ongoing is that we are moving from a quarterly to a monthly cadence for our accounting. This is the cycle we move on to “complete” the accounts, with all data inputted and reconciled by the end of the cycle. The move to a monthly cycle will mean that we are generating finance reports on a more frequent basis, which will allow the Board to have a closer view on the organisation’s finances.

Finally, this week we also had our regular monthly “books” call with our accountant and finance advisor. This was our usual opportunity to resolve any questions that have come up in relation to the accounts, but we also discussed progress on the improvements that we’ve been making.

Infrastructure

On the infrastructure side, the main highlight in recent weeks has been the migration from Anubis to Fastly’s Next-Gen Web Application Firewall (WAF) for protecting our infrastructure. The result of this migration will be an increased level of protection from bots, while simultaneously not interfering in peoples’ way when they’re using our infra. The Fastly product provides sophisticated detection of threats plus the ability for us to write our own fine-grained detection rules, so we can adjust firewall behaviour as we go.

Huge thanks to Fastly for providing us with sponsorship for this service – it is a major improvement for our community and would not have been possible without their help.

That’s it for this update. Thanks for reading and be on the lookout for the next update, probably in two weeks!

Version:next-20260320 (linux-next) Released:2026-03-20

Most Linux admins assume they know which TCP/IP ports their servers expose, until a scan reveals something unexpected. A database port listening on all interfaces, a forgotten development service, or a management interface that was meant to stay internal can easily appear once you look from the network side.

What is a port scan?A port scan is a diagnostic or reconnaissance technique used to identify open communication ports on a remote system. By sending packets to specific destinations and observing how the system responds, it becomes possible to map which services are reachable and how a host presents itself from the outside.Most Linux admins assume they already know that answer. Until a scan shows otherwise.From the system itself, everything looks controlled. Configuration files define what should be running, and local tools like netstat or ss confirm which services are active. But from the network, that same Linux system can tell a very different story.Port scanning makes that gap visible. It shows what is actually reachable, how services respond under external pressure, and whether that exposure lines up with what was intended.

Version:6.19.9 (stable) Released:2026-03-19 Source:linux-6.19.9.tar.xz PGP Signature:linux-6.19.9.tar.sign Patch:full (incremental) ChangeLog:ChangeLog-6.19.9

Version:6.18.19 (longterm) Released:2026-03-19 Source:linux-6.18.19.tar.xz PGP Signature:linux-6.18.19.tar.sign Patch:full (incremental) ChangeLog:ChangeLog-6.18.19

One of the most optimized algorithms in any standard library is sorting. It is used everywhere so it must be fast. Thousands upon thousands of developer hours have been sunk into inventing new algorithms and making sort implementations faster. Pystd has a different design philosophy where fast compilation times and readability of the implementation have higher priority than absolute performance. Perf still very much matters, it has to be fast, but not at the cost of 10x compilation time.

This leads to the natural question of how much slower such an implementation would be compared to a production quality one. Could it even be faster? (Spoilers: no) The only way to find out is to run performance benchmarks on actual code.

To keep things simple there is only one test set, sorting 10'000'000 consecutive 64 bit integers that have been shuffled to a random order which is the same for all algorithms. This is not an exhaustive test by any means but you have to start somewhere. All tests used GCC 15.2 using -O2 optimization. Pystd code was not thoroughly hand optimized, I only fixed (some of the) obvious hotspots.

Stable sort

Pystd uses mergesort for stable sorting. The way the C++ standard specifies stable sort means that most implementations probably use it as well. I did not dive in the code to find out. Pystd's merge sort implementation consists of ~220 lines of code. It can be read on this page.

Stdlibc++ can do the sort in 0.9 seconds whereas Pystd takes .94 seconds. Getting to within 5% with such a simple implementation is actually quite astonishing. Even when considering all the usual caveats where it might completely fall over with a different input data distribution and all that.

Regular sort

Both stdlibc++ and Pystd use introsort. Pystd's implementation has ~150 lines of code but it also uses heapsort, which has a further 100 lines of code). Code for introsort is here, and heapsort is here.

Stdlibc++ gets the sort done in 0.76 seconds whereas Pystd takes 0.82 seconds. This makes it approximately 8% slower. It's not great, but getting within 10% with a few evening's work is still a pretty good result. Especially since, and I'm speculating here, std::sort has seen a lot more optimization work than std::stable_sort because it is used more.

For heavy duty number crunching this would be way too slow. But for moderate data set sizes the performance difference might be insignificant for many use cases.

Note that all of these are faster (note: did not measure) than libc's qsort because it requires an indirect function call on every comparison i.e. the comparison method can not be inlined.

Where does the time go?

Valgrind will tell you that quite easily.

This picture shows quite clearly why big O notation can be misleading. Both quicksort (the inner loop of introsort) and heapsort have "the same" average time complexity but every call to heapsort takes approximately 4.5 times as long.

Trevor Milton, the pardoned founder of Nikola, is seeking $1 billion for AI-powered autonomous planes through a new venture called SyberJet. The Tech Buzz reports: "Autonomous planes will be 10 times harder than Nikola ever was," Milton told the Wall Street Journal in a rare interview. It's a remarkable admission from someone whose last venture collapsed under the weight of securities fraud charges after he overstated the capabilities of Nikola's electric and hydrogen-powered trucks. Milton was convicted in 2022 on three counts of fraud for misleading investors about Nikola's technology, including staging a video that made it appear a truck prototype was driving under its own power when it was actually rolling downhill. The conviction sent him to prison and turned Nikola into a cautionary tale about startup hype culture. His pardon, which came earlier this year, sparked immediate controversy in venture capital and legal circles. Now he's betting that AI and autonomous aviation represent a clean slate. SyberJet appears focused on developing artificial intelligence systems capable of piloting aircraft without human intervention - a technical challenge that's stumped even well-funded players like Boeing and Airbus. [...] Milton hasn't detailed SyberJet's technical approach or revealed who's backing the venture. The company's website remains sparse, and aviation industry sources say they haven't seen concrete demonstrations of the technology. That opacity echoes the early days of Nikola, when Milton made sweeping claims about revolutionary trucks that existed mostly in renderings and promotional videos. If you need a quick refresher on the Nikola saga, here's a timeline of key events: June, 2016: Nikola Motor Receives Over 7,000 Preorders Worth Over $2.3 Billion For Its Electric Truck December, 2016: Nikola Motor Company Reveals Hydrogen Fuel Cell Truck With Range of 1,200 Miles February, 2020: Nikola Motors Unveils Hybrid Fuel-Cell Concept Truck With 600-Mile Range June, 2020: Nikola Founder Exaggerated the Capability of His Debut Truck September, 2020: Nikola Motors Accused of Massive Fraud, Ocean of Lies September, 2020: Nikola Admits Prototype Was Rolling Downhill In Promo Video September, 2020: Nikola Founder Trevor Milton Steps Down as Chairman in Battle With Short Seller October, 2020: Nikola Stock Falls 14 Percent After CEO Downplays Badger Truck Plans November, 2020: Nikola Stock Plunges As Company Cancels Badger Pickup Truck July, 2021: Nikola Founder Trevor Milton Indicted on Three Counts of Fraud December, 2021: EV Startup Nikola Agrees To $125 Million Settlement September, 2022: Nikola Founder Lied To Investors About Tech, Prosecutor Says in Fraud Trial

Read more of this story at Slashdot.

An anonymous reader quotes a report from TechCrunch: The FBI has resumed purchasing reams of Americans' data and location histories to aid federal investigations, the agency's director, Kash Patel, testified to lawmakers on Wednesday. This is the first time since 2023 that the FBI has confirmed it was buying access to people's data collected from data brokers, who source much of their information -- including location data -- from ordinary consumer phone apps and games, per Politico. At the time, then-FBI director Christopher Wray told senators that the agency had bought access to people's location data in the past but that it was not actively purchasing it. When asked by U.S. Senator Ron Wyden, Democrat of Oregon, if the FBI would commit to not buying Americans' location data, Patel said that the agency "uses all tools ... to do our mission." "We do purchase commercially available information that is consistent with the Constitution and the laws under the Electronic Communications Privacy Act -- and it has led to some valuable intelligence for us," Patel testified Wednesday. Wyden said buying information on Americans without obtaining a warrant was an "outrageous end-run around the Fourth Amendment," referring to the constitutional law that protects people in America from device searches and data seizures.

Read more of this story at Slashdot.

Two years have passed since I last shared my Friday app icon sketches, but the sketching itself hasn't stopped.

For me, it's the best way to figure out the right metaphors before we move to final pixels. These sketches are just one part of the GNOME Design Team's wider effort to keep our icons consistent and meaningful—it is an endeavor that’s been going on for years.

If you design a GNOME app following the GNOME Design Guidelines, feel free to request an icon to be made for you. If you are serious and apply for inclusion in GNOME Circle, you are way more likely to get a designer's attention.

Previously

Cloudflare is appealing a 14.2 million-euro fine from Italy for refusing to comply with its "Piracy Shield" law, which requires blocking access to websites on its 1.1.1.1 DNS service within 30 minutes. The company argues the system lacks oversight, risks widespread overblocking, and could undermine core Internet infrastructure. Ars Technica's Jon Brodkin reports: Piracy Shield is "a misguided Italian regulatory scheme designed to protect large rightsholder interests at the expense of the broader Internet," Cloudflare said in a blog post this week. "After Cloudflare resisted registering for Piracy Shield and challenged it in court, the Italian communications regulator, AGCOM, fined Cloudflare... We appealed that fine on March 8, and we continue to challenge the legality of Piracy Shield itself." Cloudflare called the fine of 14.2 million euros ($16.4 million) "staggering." AGCOM issued the penalty in January 2026, saying Cloudflare flouted requirements to disable DNS resolution of domain names and routing of traffic to IP addresses reported by copyright holders. Cloudflare had previously resisted a blocking order it received in February 2025, arguing that it would require installing a filter on DNS requests that would raise latency and negatively affect DNS resolution for sites that aren't subject to the dispute over piracy. Cloudflare co-founder and CEO Matthew Prince said that censoring the 1.1.1.1 DNS resolver would force the firm "not just to censor the content in Italy but globally." Piracy Shield was designed to combat pirated streams of live sports events, requiring network operators to block domain names and IP addresses within 30 minutes of receiving a copyright notification. Cloudflare said the fine should have been capped at 140,000 euros ($161,000), or 2 percent of its Italian earnings, but that "AGCOM calculated the fine based on our global revenue, resulting in a penalty nearly 100 times higher than the legal limit." Despite its complaints about the size of the fine, Cloudflare said the principles at stake "are even larger" than the financial penalty. "Piracy Shield is an unsupervised electronic portal through which an unidentified set of Italian media companies can submit websites and IP addresses that online service providers registered with Piracy Shield are then required to block within 30 minutes," Cloudflare said. Cloudflare is pushing for the law to be struck down, arguing that it is "incompatible with EU law, most notably the Digital Services Act (DSA), which requires that any content restriction be proportionate and subject to strict procedural safeguards." In addition to appealing the fine, Cloudflare says it will continue to challenge Piracy Shield in Italian courts, engage with EU officials, and seek full access to AGCOM's Piracy Shield records.

Read more of this story at Slashdot.

With today's latest Stitch updates, Google is trying to make "vibe design" happen, reports The Verge's Jay Peters. The AI-native design platform encourages users to describe goals, feelings, or inspiration in "natural language," rather than starting with traditional blueprints. In a blog post, Google Labs Product Manager Rustin Banks says that Stitch can turn those inputs into interactive prototypes, automatically map user flows, and support real-time iteration. It introduces voice capabilities that allow users to "speak directly to [the] canvas" for feedback or changes. Tools like DESIGN.md also help users create reusable design systems across various projects.

Read more of this story at Slashdot.

Longtime Slashdot reader UnknowingFool writes: Users of Samsung PCs are reporting the inability to access the C: drive after the Windows 11 February update. The bug seems to be in connection with the Samsung Galaxy Connect app, which allows Samsung phones and tablets to connect to Windows machines. [A previous stable version of the app has been re-released to prevent this problem from spreading.] This parody explains the situation with humor. The issue stems from update KB5077181 and is impacting Samsung PCs running Windows 11 25H2 or 24H2. Microsoft and Samsung have confirmed the issue and published a workaround, but as PCWorld notes, it will take some time. The workaround "requires removing the Samsung application, then asking Windows to repair the drive permissions and assigning a new owner, then restoring the Windows default permissions, including patching in some custom code that Microsoft wrote."

Read more of this story at Slashdot.

It’s clear LLMs are one of the biggest changes in technology ever. The rate of progress is astounding: recently due to a configuration mistake I accidentally used Claude Sonnet 3.5 (released ~2 years ago) instead of Opus 4.6 for a task and looked at the output and thought “what is this garbage”?

But daily now: Opus 4.6 is able to generate reasonable PoC level Rust code for complex tasks for me. It’s not perfect – it’s a combination of exhausting and exhilarating to find the 10% absolutely bonkers/broken code that still makes it past subagents.

So yes I use LLMs every day, but I will be clear: if I could push a button to “un-invent” them I absolutely would because I think the long term issues in larger society (not being able to trust any media, and many of the things from Dario’s recent blog etc.) will outweigh the benefits.

But since we can’t un-invent them: here’s my opinion on how they should be used. As a baseline, I agree with a lot from this doc from Oxide about LLMs. What I want to talk about is especially around some of the norms/tools that I see as important for LLM use, following principles similar to those.

On framing: there’s “core” software vs “bespoke”. An entirely new capability of course is for e.g. a nontechnical restaurant owner to use an LLM to generate (“vibe code”) a website (excepting hopefully online orderings and payments!). I’m not overly concerned about this.

Whereas “core” software is what organizations/businesses provide/maintain for others. I work for a company (Red Hat) that produces a lot of this. I am sure no one would want to run for real an operating system, cluster filesystem, web browser, monitoring system etc. that was primarily “vibe coded”.

And while I respect people and groups that are trying to entirely ban LLM use, I don’t think that’s viable for at least my space.

Hence the subject of this blog is my perspective on how LLMs should be used for “core” software: not vibe coding, but using LLMs responsibly and intelligently – and always under human control and review.

Agents should amplify and be controlled by humans

I think most of the industry would agree we can’t give responsibility to LLMs. That means they must be overseen by humans. If they’re overseen by a human, then I think they should be amplifying what that human thinks/does as a baseline – intersected with the constraints of the task of course.

On “amplification”: Everyone using a LLM to generate content should inject their own system prompt (e.g. AGENTS.md) or equivalent. Here’s mine – notice I turn off all the emoji etc. and try hard to tune down bulleted lists because that’s not my style. This is a truly baseline thing to do.

Now most LLM generated content targeted for core software is still going to need review, but just ensuring that the baseline matches what the human does helps ensure alignment.

Pull request reviews

Let’s focus on a very classic problem: pull request reviews. Many projects have wired up a flow such that when a PR comes in, it gets reviewed by a model automatically. Many projects and tools pitch this. We use one on some of my projects.

But I want to get away from this because in my experience these reviews are a combination of:

• Extremely insightful and correct things (there’s some amazing fine-tuning and tool use that must have happened to find some issues pointed out by some of these)
• Annoying nitpicks that no one cares about (not handling spaces in a filename in a shell script used for tests)
• Broken stuff like getting confused by things that happened after its training cutoff (e.g. Gemini especially seems to get confused by referencing the current date, and also is unaware of newer Rust features, etc)

In practice, we just want the first of course.

How I think it should work:

• A pull request comes in
• It gets auto-assigned to a human on the team for review
• A human contributing to that project is running their own agents (wherever: could be local or in the cloud) using their own configuration (but of course still honoring the project’s default development setup and the project’s AGENTS.md etc)
• A new containerized/sandboxed agent may be spawned automatically, or perhaps the human needs to click a button to do so – or perhaps the human sees the PR come in and thinks “this one needs a deeper review, didn’t we hit a perf issue with the database before?” and adds that to a prompt for the agent.
• The agent prepares a draft review that only the human can see.
• The human reviews/edits the draft PR review, and has the opportunity to remove confabulations, add their own content etc. And to send the agent back to look more closely at some code (i.e. this part can be a loop)
• When the human is happy they click the “submit review” button.
• Goal: it is 100% clear what parts are LLM generated vs human generated for the reader.

I wrote this agent skill to try to make this work well, and if you search you can see it in action in a few places, though I haven’t truly tried to scale this up.

I think the above matches the vision of LLMs amplifying humans.

Code Generation

There’s no doubt that LLMs can be amazing code generators, and I use them every day for that. But for any “core” software I work on, I absolutely review all of the output – not just superficially, and changes to core algorithms very closely.

At least in my experience the reality is still there’s that percentage of the time when the agent decided to reimplement base64 encoding for no reason, or disable the tests claiming “the environment didn’t support it” etc.

And to me it’s still a baseline for “core” software to require another human review to merge (per above!) with their own customized LLM assisting them (ideally a different model, etc).

FOSS vs closed

Of course, my position here is biased a bit by working on FOSS – I still very much believe in that, and working in a FOSS context can be quite different than working in a “closed environment” where a company/organization may reasonably want to (and be able to) apply uniform rules across a codebase.

While for sure LLMs allow organizations to create their own Linux kernel filesystems or bespoke Kubernetes forks or virtual machine runtime or whatever – it’s not clear to me that it is a good idea for most to do so. I think shared (FOSS) infrastructure that is productized by various companies, provided as a service and maintained by human experts in that problem domain still makes sense. And how we develop that matters a lot.

An anonymous reader quotes a report from Reuters: Britain plans to consider requiring labels on AI-generated content to protect consumers from disinformation and deepfakes, the government said on Wednesday, as it outlined other areas of focus to tackle the evolving global challenge. Technology minister Liz Kendall stressed the need to strike the right balance between protecting the creative industries and allowing the AI sector to innovate, saying in a statement that the government would take time to "get this right." The next phase of the government's work on copyright and AI would also look at the harms posed by digital replicas without consent, ways for creators to control their work online and support for independent creative organizations, she said. [...] Louise Popple, a copyright expert at law firm Taylor Wessing, noted that the government had not ruled out a broad exception that would allow AI developers to train on copyright works. "That's a subtle difference of approach and could be interpreted to mean that everything is still up for grabs" she said. "It feels very much like the hard issues are being kicked down the road by the government." In 2024, Britain proposed easing copyright rules to let developers train models on lawfully accessed material, with creators able to reserve their rights. On Wednesday, Kendall said that having engaged with creatives, AI firms, industry bodies, unions and academics, the government had concluded it "no longer has a preferred option." "We will help creatives control how their work is used. This sits at the heart of our ambition for creatives – including independent and smaller creative organizations -- to be paid fairly," she said.

Read more of this story at Slashdot.

Meta is shutting down its VR social platform Horizon Worlds, which was once a key piece of the pivot to the metaverse. The company said the app will be taken off the Quest store at the end of March, and fully removed from Quest headsets by June 15. After that date, it will shift to a standalone "mobile-only experience." CNBC reports: The shift for Horizon Worlds, which was once a central part of the company's push into virtual reality, comes weeks after Meta cut over 1,000 employees from Reality Labs, the unit responsible for the metaverse. [...] The social platform has never drawn more than a couple hundred thousand active users a month, CNBC previously reported. The virtual 3D social network where avatars could interact and play games with other users officially launched in late 2021. It operated exclusively on the Quest VR platform until Meta launched a mobile app version in September 2023. The mobile version of Horizon Worlds was built to provide an entry point for users without VR headsets, functioning similarly to Roblox.

Read more of this story at Slashdot.

Longtime Slashdot reader internet-redstar writes: Nearly a trillion dollars has been wiped from software stocks in 2026, with hedge funds making billions shorting Salesforce, HubSpot, and Atlassian. At FOSDEM 2026, cURL maintainer Daniel Stenberg shut down his bug bounty program after AI-generated slop overwhelmed his team. A new article on HackerNoon argues that most commercial SaaS could inevitably become OpenSource, not out of ideology but economics. The author points to Proxmox replacing VMware at enterprise scale and startups like Holosign replicating DocuSign at $19/month flat as evidence. The catch, the article claims, is that maintainers who refuse to embrace AI tools risk being forked, or simply replicated from scratch, by those who do.

Read more of this story at Slashdot.

Dave Knott shares a report from the New York Times: On Wednesday, the Association for Computing Machinery, the world's largest society of computing professionals, said Drs. Charles Bennett and Gilles Brassard had won this year's Turing Award for their work on quantum cryptography and related technologies. The Turing Award, which was introduced in 1966, is often called the Nobel Prize of computing, and it includes a $1 million prize, which the two scientists will share. [...] The two met in 1979 while swimming in the Atlantic just off the north shore of Puerto Rico. They were taking a break while attending an academic conference in San Juan. Dr. Bennett swam up to Dr. Brassard and suggested they use quantum mechanics to create a bank note that could never be forged. Collaborating between Montreal and New York, they applied Dr. Bennett's idea to subway tokens rather than bank notes. In a research paper published in 1983, they showed that their quantum subway tokens could never be forged, even if someone managed to steal the subway turnstile housing the elaborate hardware needed to read them. This led to quantum cryptography. After describing their new form of encryption in a research paper published in 1984, they demonstrated the technology with a physical experiment five years later. Called BB84, their system used photons -- particles of light -- to create encryption keys used to lock and unlock digital data. Thanks to the laws of quantum mechanics, the behavior of a photon changes if someone looks at it. This means that if anyone tries to steal the keys, he or she will leave a telltale sign of the attempted theft -- a bit like breaking the seal on an aspirin bottle.

Read more of this story at Slashdot.

Version:next-20260318 (linux-next) Released:2026-03-18

n8n (CVE-2025-68613) is an open-source automation tool used to connect APIs, databases, and SaaS apps into workflows. It is commonly used to move data between systems, trigger jobs, and tie services together, and in many environments, it also holds credentials and access to internal services.