aria-label and aria-labelledby aren’t permitted on these elements. They are intended for interactive elements (buttons, links, form controls) and landmark regions.

The author provides the HTML elements that are not allowed to have an aria-label or aria-labelledby.

VoiceOver generally announce the contents of the aria-label. That aria-label “works” on generic elements in VoiceOver is a nonstandard remediation of noncompliant code, not an endorsement of a technique working as intended.

The author provides multiple HTML patterns to avoid the use of aria-label in the first place! Great!

• Was the Label Addressing a Problem Worth Solving in the First Place?
• Use visible text
• Use Visually-Hidden Text
• Use More Semantically Applicable Elements
• Add an Applicable Role

First results of Germany's trial on work time reduction.

I have money and I have a URL, how do I send money to the publisher of that URL?

The Payment Request API is too technical.

Linking to payment methods in the page.

Podcasting 2.0 RSS has a <podcast:funding> tag.

Flattr but the solution is not so great.

Brave.

...

Maybe a <meta property="financial-support" content="https://...."

Entre les États-Unis et l'Inde

Les entreprises ITSM-NG avec XWiki et
ITSM-NG, en lient avec Opensource Experts.

Un audit d'accessibilité peut être réalisé avec l'outil Ara

Basé sur la dernière version du référentiel général d’amélioration de l’accessibilité (RGAA 4.1), avec Ara vous pouvez :
– Faire un état des lieux (audit partiel de 25 ou 50 critères)
– Faire un audit complet, dit de conformité (106 critères)
– Générer votre rapport d’audit et votre déclaration d’accessibilité

Working with SemVer leads to two observations:

• only two version numbers are sufficient: there's no real difference between patch and minor.
• deprecate than remove cycle: using a major version only leads to the removal of deprecation warnings and their associated feature. It means bumping for 1 to 2 should works, if the version 1 does not throws warnings anymore.

how to judge the semver approach? Either describe the thing actually behaves (descriptivist) or describe about the right and wrong ways to use a particular tool (prescriptivist).

Another instance of this pattern playing out I’ve noticed are log levels. You can get very philosophical about the difference between error, warn and info. But what helps is looking at what they do:

• error pages the operator immediately.
• warn pages if it repeats frequently.
• info is what you see in the prog logs when you actively look at them.
• And debug is what your developers see when they enable extra logging.

Le financement immoral des compteurs Linky au détriment des consommateurs.

Why research needs free open source softwares.

It shows two things:

• Science must not use commercial software
• Science is underpaid if it has to use pirated software

(via https://nicolas-delsaux.hd.free.fr/Shaarli/shaare/eptdLQ)

Découverte d'alternatives libres et d'outils de protection contre le pistage facile à installer.

The official definition of MIME types

• 3D flow diagram for relationships and connections
• Card Diagram to highlight and select information or data in relation to its surrounding data and information
• Pyramid graph: Being great at showing two categories of information and comparing them horizontally, they are an alternative to typical horizontal or vertical bar graphs.
  Pyramid graph
• Sankey Flow Diagram: show the progression and the journey of information and data and how they are connected in relation to their data value.
• Stream graph: a great way to show the data and how it relates to the other data
• Tree map: It’s a great way to show the data spatially and how the data value relates, in terms of size, to the rest of the data.
• Waterfall chart: showing the data and how it relates in a vertical manner to the range of data values.
• Doughnut chart: show the data against the other data segments, and value within a range of data.
• Lollipop chart: excellent method to demonstrate percentage values that also integrates the label and data value well.
• Bubble Chart: illustrate data values in terms of size and sub-classification in relation to the surrounding data.

Taylor Swift a encore trouvé un moyen d'innover, et de manière remarquable.

I shortened my sentences. I used keywords that Google could identify easily. I wrote in a way that allowed Google to understand our content, following a set of nebulous rules laid out by the overlords. The rules were never expressly stated, but trial and error from millions of people that came before our blog seemed to point to a common path. And that path was “Juicy Info Nuggets”.

In September of 2023 Google started rolling out what it called its “Helpful Content Update“. The stated goal of this update to search results was to reduce the amount of spam and AI-generated crap that littered the internet. The actual result? The destruction of small publishers, blogs, and the Rise of Reddit.

And where does that leave bloggers, small publishers, and the like? Well, after years of training online publishers to write in a fashion that Google web crawlers could easily identify, in easily digestible nuggets of information, Google will be taking those nuggets and giving them away for free. Because hey, when you’re a huge monopoly you can do whatever you want.

A list of things to avoid

Trois startups proposent trois solutions::

1. Une horloge atomique miniaturisée de la taille d'un boîtier ATX horizontal par Infleqtion et son système Tiqker. Cette boîte vient de décrocher le jackpot avec 11 millions de dollars du Département de la Défense américain. Matthew Kinsella, leur CEO, l’explique simplement : “Si vous connaissez votre point de départ, vos changements de vitesse et de direction, et que vous disposez d’une mesure du temps ultra-précise, vous savez exactement où vous êtes. Et ça, c’est impossible à pirater !”
2. SandboxAQ utilise des capteurs quantiques pour détecter les variations du champ magnétique terrestre, comme les oiseaux migrateurs.
3. Rendre les capteurs quantiques plus sûrs via https://q-ctrl.com/

La pourriture de cerveau (brain rot): Détérioration supposée de l'état mental ou intellectuel d'une personne, notamment considérée comme le résultat d'une surconsommation de contenu (aujourd'hui particulièrement en ligne) considéré comme insignifiant ou non stimulant »

La merdification (enshittification) est le terme désignant la détérioration progressive d'un service ou d'un produit, en particulier d'une plateforme en ligne, provoquée par une réduction de la qualité du service fourni résultant de la recherche de profit.

(in the context of big tech companies)

the priority of a project is to ship!

But it’s really important that one person on the project has an end-to-end understanding of the whole thing: how it hangs together technically, and what product or business purpose it serves.

You only know you’ve shipped when your company’s leadership acknowledge you’ve shipped.

you have to get clear on what the company is looking to get out of the project. [...] Align your work and communication accordingly!

Second, no matter the project goal, your leadership team will always have basically zero technical context about the project. They will rely on you for estimates, to answer technical questions, and to anticipate technical problems. Maintaining that trust should be your top priority.

How?

• track record of having shipped in the past.
• project confidence
• project competence
• communicate professionally and concisely. Share updates.

Then getting to production! Often a key detail is missing. Sometimes the user documents are stored in memcached and are MB large, or the data stored are unexpectedly sensitive legally sensible.

Can we ship right now?

Bring up the feature to as many eyes as possible!

If you want to ship, you need to do the exact opposite: you need to deploy as much as you can as early as possible, and you need to do the scariest changes as early as you can possibly do them.

A good example comes from looking towards the impact of incorporating AI into search engines such as Google. A single generative AI query could use 4 to 5 times more energy than a regular search engine query. Others found that average energy consumption per search could be 6.9–8.9 Wh, compared to 0.3 Wh for a standard Google search. This gives us an enormous range of 4-30 times larger. Whichever end of the scale the figures land, it’s a significant increase.

Does the result quality increases at the same rate?

The report is available on the green web foundation

C'est toujours compliqué de détecter les messages générés par IA, mais il y a ici une tendance: les messages générés augmentent.

Are hCaptcha not accessible to screen readers?