Ten years ago, we released Tutanota - now Tuta Mail. What's your wish for 2025?

With your help we've achieved a lot so far:

✅ Published all apps on F-Droid
✅ Made Tuta completely Google-free
✅ Released FREE desktop clients for Linux, Windows, macOS
✅ Made Tuta quantum-safe

And there's more to expect soon! 🎉

✅ Labels 😍
✅ Import 💪
✅ Calendar Widget 🥳

Which feature is your favorite?

Spotify is a creepy, and grossly unethical, platform at this point. it rips off musicians and rewards huge companies -- and itself. Apparently what it's doing is legal, however.

This is great reporting, from a new book by Liz Pelly. A compelling read.

harpers.org/archive/2025/01/th…

The Ghosts in the Machine, by Liz Pelly

Spotify’s plot against musicians

^{Liz Pelly (Harper's Magazine)}

Top #CWE reasons used in #curl #CVE reports. In the 161 CVEs we have published over 25+ years so far, we have used 59 different CWEs.

The graph shows all CWEs that have been used more than once.

With #Prusa turning from #openness with its new Core One model and other cases, there is a need to discuss alternative models to cultivate and sustain #opensource hardware. Although promising approaches exist already, it might be vital to identify the necessary patterns of #Commoning. Read my thoughts here: blog.opensourceecology.de/en/2…

#OpenHardware #CommunitySupportedIndustry @OSEGermany cc @GOSH @stargirl

Why Tech-Commons die | Open Source Ecology Germany

The introduction of a new, closed Prusa CORE One should come as little surprise, but there could be a remedy A guest article by Paul Jerchel Commons die without…

^{Timm (Open Source Ecology Germany)}

“The Ugly Truth About Spotify Is Finally Revealed”

honest-broker.com/p/the-ugly-t…

> In other words, Spotify has gone to war against musicians and record labels.

The Ugly Truth About Spotify is Finally Revealed

A year-long investigation by an indie journalist is a call to action

^{Ted Gioia (The Honest Broker)}

Although the big day for us as a family of 3 is of course Wednesday, the mother-in-law had her Christmas morning with us.

She got a new Kindle from us and a ridiculous amount of sweets and other nice things.

I have a nice new jumper and some lovely local cider to get into.

And the dog, well, she got her own sofa.

#DogsOfMastodon

POLITIQ upouští "X". Přidat si nás můžeš na sítích:
Facebook: facebook.com/MagazinPolitiq?ut…
Instagram: instagram.com/MagazinPolitiq?u…
Threads: threads.net/@MagazinPolitiq?ut…
Bluesky: bsky.app/profile/magazinpoliti…
Mastodon: bsky.app/profile/magazinpoliti…
linkedIn: linkedin.com/company/politiq?u…

#eXit #X #ByeByeElon #Twitter #Politika #SocialMedia #Politiq #Zpravy #Media

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Perceiving space's geometry lets me find interesting things. Perceiving space's vibes lets me discover them.

Travelling the world as a blind individual, I get to see many interesting and beautiful places. However, while I can navigate around quite well using human echolocation and my long cane, I still felt something was missing compared to my sighted times. I can use echolocation to perceive the geometry of the environment, but not so much its vibes, which often lie in subtle details. A silent, empty square feels completely different to a square full of people, music and life. In a similar fashion, a square in the middle of the day is something else to a night square, lit by colorful neons, full of flowers, statues, ancient or modern buildings.

I can discover a monument using echolocation, but there's little I can do to tell what it represents, what color does it have, whether it's old, new, in what condition. I can walk on the street and notice a restaurant with a terrace, but I don't get to see its visuals, decoration or style on my radar. I can observe buildings on a square, but don't get to admire the magnificence of their architecture.

Indeed, visuals are not the only medium for vibes, I can still get a lot from sounds, smells, activity. But it's a significant-one and I was thinking, whether I could make use of the large language models to fill this sensory gap. Before, my travel routine was to search for cool places on Google, and later find them in the environment. But with a good enough visual perception layer, perhaps it may be possible to do it the other way around. To visit a place, and discover interesting things on the walk. And get an even deeper connection with the space.

Thus I designed VScan 0.2 to research this approach, as well as address some other camera-related needs I experience on my adventures.

If you'd like to learn more, check out:
github.com/RastislavKish/VScan

Happy travelling!

GitHub - RastislavKish/VScan: A visual perception layer for the blind

A visual perception layer for the blind. Contribute to RastislavKish/VScan development by creating an account on GitHub.

^GitHub

I finally turned off GitHub Copilot yesterday. I’ve been using it for about a year on the ‘free for open-source maintainers’ tier. I was skeptical but didn’t want to dismiss it without a fair trial.

It has cost me more time than it has saved. It lets me type faster, which has been useful when writing tests where I’m testing a variety of permutations of an API to check error handling for all of the conditions.

I can recall three places where it has introduced bugs that took me more time to to debug than the total time saving:

The first was something that initially impressed me. I pasted the prose description of how to communicate with an Ethernet MAC into a comment and then wrote some method prototypes. It autocompleted the bodies. All very plausible looking. Only it managed to flip a bit in the MDIO read and write register commands. MDIO is basically a multiplexing system. You have two device registers exposed, one sets the command (read or write a specific internal register) and the other is the value. It got the read and write the wrong way around, so when I thought I was writing a value, I was actually reading. When I thought I was reading, I was actually seeing the value in the last register I thought I had written. It took two of us over a day to debug this. The fix was simple, but the bug was in the middle of correct-looking code. If I’d manually transcribed the command from the data sheet, I would not have got this wrong because I’d have triple checked it.

Another case it had inverted the condition in an if statement inside an error-handling path. The error handling was a rare case and was asymmetric. Hitting the if case when you wanted the else case was okay but the converse was not. Lots of debugging. I learned from this to read the generated code more carefully, but that increased cognitive load and eliminated most of the benefit. Typing code is not the bottleneck and if I have to think about what I want and then read carefully to check it really is what I want, I am slower.

Most recently, I was writing a simple binary search and insertion-deletion operations for a sorted array. I assumed that this was something that had hundreds of examples in the training data and so would be fine. It had all sorts of corner-case bugs. I eventually gave up fixing them and rewrote the code from scratch.

Last week I did some work on a remote machine where I hadn’t set up Copilot and I felt much more productive. Autocomplete was either correct or not present, so I was spending more time thinking about what to write. I don’t entirely trust this kind of subjective judgement, but it was a data point. Around the same time I wrote some code without clangd set up and that really hurt. It turns out I really rely on AST-aware completion to explore APIs. I had to look up more things in the documentation. Copilot was never good for this because it would just bullshit APIs, so something showing up in autocomplete didn’t mean it was real. This would be improved by using a feedback system to require autocomplete outputs to type check, but then they would take much longer to create (probably at least a 10x increase in LLM compute time) and wouldn’t complete fragments, so I don’t see a good path to being able to do this without tight coupling to the LSP server and possibly not even then.

Yesterday I was writing bits of the CHERIoT Programmers’ Guide and it kept autocompleting text in a different writing style, some of which was obviously plagiarised (when I’m describing precisely how to implement a specific, and not very common, lock type with a futex and the autocomplete is a paragraph of text with a lot of detail, I’m confident you don’t have more than one or two examples of that in the training set). It was distracting and annoying. I wrote much faster after turning it off.

So, after giving it a fair try, I have concluded that it is both a net decrease in productivity and probably an increase in legal liability.

Discussions I am not interested in having:

• You are holding it wrong. Using Copilot with this magic config setting / prompt tweak makes it better. At its absolute best, it was a small productivity increase, if it needs more effort to use, that will be offset.
• This other LLM is much better. I don’t care. The costs of the bullshitting far outweighed the benefits when it worked, to be better it would have to not bullshit, and that’s not something LLMs can do.
• It’s great for boilerplate! No. APIs that require every user to write the same code are broken. Fix them, don’t fill the world with more code using them that will need fixing when the APIs change.
• Don’t use LLMs for autocomplete, use them for dialogues about the code. Tried that. It’s worse than a rubber duck, which at least knows to stay silent when it doesn’t know what it’s talking about.

The one place Copilot was vaguely useful was hinting at missing abstractions (if it can autocomplete big chunks then my APIs required too much boilerplate and needed better abstractions). The place I thought it might be useful was spotting inconsistent API names and parameter orders but it was actually very bad at this (presumably because of the way it tokenises identifiers?). With a load of examples with consistent names, it would suggest things that didn't match the convention. After using three APIs that all passed the same parameters in the same order, it would suggest flipping the order for the fourth.

#GitHubCopilot #CHERIoT

Time to stop using codeql in the #curl project perhaps?

github.com/curl/curl/pull/1579…

GHA: drop codeql by bagder · Pull Request #15798 · curl/curl

We started using codeql for static code analysis in 7183f5a, June 2020. Since then, not a single commit has been merged into the source code repository citing codeql as source or reason. Yet, it ke...

^GitHub

Day 21 - #adventOfIOSAccessibility. There are a few accessibility settings you can check for, or get notifications in case these preferences change. This is especially important when developing custom components as they will mostly work with UIKit and SwiftUI controls.

#365DaysIOSAccessibility

Curl Drops Support For Hyper Rust HTTP Backend Citing Little Demand

The widely-used Curl project has removed support for its Rust-written Hyper HTTP back-end that they were experimentally shipping for several years. The removal of this Rust back-end comes from having little end-user and developer interest in this portion of the code...
phoronix.com/news/Curl-Drops-R…