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A headland with a small lighthouse...
#meermittwoch #photography #ocean #lighthouse #France #landscape #ship
hypebot
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@sebsauvage C'est un fingerprint spécifique à la paire (profil du titulaire, profil du contact) ou bien purement spécifique au profil du contact ?
1. C'est con, on ne peut pas voir son propre fingerprint. 🙃
Si c'est bien spécifique au profil, et si l'info de profil est dans le lien / QR code (j'ai pas vérifié…), alors ça pourrait servir de confirmation d'identité, à la façon d'une empreinte PGP, non ?
@aaribaud
Je pense que permettre la vérification aisée des fingerprints, ça serait une évolution bienvenue de DeltaChat. (Un peu comme Signal le fait dans l'option "Afficher le numéro de sécurité")
d@nny disc@
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They played political, religious, social, and eco- nomic groups against each other and seized power while these groups struggled against each other.
#fascism #uspol #history #propaganda
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Live your life so that people will donate to a charity close to your heart when you die, not a charity you would have hated as an act of spite.
"slop" is such a good fucking word. the vibe of sellout but now it's a fucking suffix. just heard some music that was clearly edmslop and i understood what i was feeling when i heard that shit before. praise be to slop
@niklasnisbeth @david_chisnall @kevin the consumer software experience in 2026 is an iterative exploration of just how shitty you can get away with making your software
@davidgerard @niklasnisbeth @david_chisnall @kevin and again least in the UK with no effective functioning safety regulations or consumer rights enforcement left everything else too
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I'll quote us directly once again:
We truly value the partnership with @openstreetmap
Every year through our Lifetime Fundraiser, we back organizations that are making a real difference.
On top of this, funds are allocated from each year's Fundraiser in order to support past beneficiaries.
See you for the next one...
https://blog.openstreetmap.org/2026/08/21/thanking-proton-our-newest-platinum-sponsor/
🇨🇳 China’s hackers use DeepSeek for attacks, researchers say
“DeepSeek is the AI of choice for Chinese hackers because it’s relatively powerful with very low cyber guardrails,” said Charles Li, chief analyst at Team T5. “Western models are highly sought-after but their guardrails are much more strict and require a lot more effort to bypass.”
https://www.japantimes.co.jp/news/2026/08/25/asia-pacific/crime-legal/china-hackers-deepseek/
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Mozilla CEO writes about "AI":
"In a world where companies are forcing AI on users, the most compelling thing Firefox can do is stick with what we do best: give users choice and agency."
No. The best thing you can do is build a browser that works best for the user, that does not alienate them from the Internet and the people building it. This is a dumb attempt to do more "Mozilla does the good AI" PR. But there is no "good AI". And translations are not what people talk about when they say "AI" which that guy knows.
He didn't learn shit from the backlash. This is just "we will do more AI, good AI, until you like it".
#koreader people: any of you using simpleUI or ZenUI/OS plugins? General wisdom about improving UI welcome.
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Safety loaf
Our 7th Annual OpenUK Awards, Young Person category nominations sponsored by Kioko 💫 are now open until 6 September. Nominate yourself or a colleague here: https://openuk.uk/awards/
A short list of up to 3 finalists will be shared by our Judges on 15 September.
Shortlisted nominees will be invited to our Gala Awards Ceremony and Dinner, where the winners will be revealed.
#opensource #opensourcesoftware #openukawards #opensourceai #opensourcetalent
😆 😆 😆
not so funny now huh?!
wow this peach iced tea is really nice - oh 48g sugar will do that
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Been working on Dandelion BASIC today.
I printed Dick Whipple's ATmega1280 code, which is a direct interpreter.
It is about 3400 lines of code, and printed on A4 paper, it comes to just over 50 pages.
From this code I am going to glean the transposed Intel 8080 ISA onto the AVR ISA with GCC # define directives.
I can also deal with the very tricky INSERT routine, which deals with adding, deleting, and replacing BASIC program lines.
I actually like machine learning when applied to the right category of problem. The core requirement for machine learning to be useful is that a correct answer is very useful and the cost of an incorrect answer is low.
My go-to example of this is what I did in my PhD: data prefetching. If you prefetch the data you’re about to need, great, you don’t sit with the CPU idle when it could be doing useful work. If you prefetch the wrong thing (and have a sensible eviction policy) then it’s no worse than doing nothing. That’s pretty much the ideal shape for these things. The same applies to branch prediction: predict a branch correctly and you keep the pipeline busy, predict it incorrectly and you’ve wasted a bit of power. Branch prediction has always been some form of machine learning (with the exception of the static ‘forward branch not taken, backwards branch taken’ policies).
Beyond that, there are two other properties that make problems particularly good fits for machine learning. The first is that the problem changes rapidly but you have a bunch of examples. When I was at Microsoft, Project Silica was doing archival storage by using lasers to create tiny bubbles in glass. The exact shape of these varied depending on how they configured the lasers. It took a couple of weeks to write a new rules-based recogniser, whereas a machine-learning one could be trained with the samples from a test run. But, beyond that, they discovered that the shapes also changed slightly depending on the particular piece of glass that they used. After writing to a piece of glass, they knew what the written data was, so they could fine-tune the parameters of the model and etch the fine tuning information onto the side. You absolutely wouldn’t want to have to write a modified version of a reader program for every disk in your disk robot.
The property where machine learning is a good fit is where you don’t have the theory. People since Plato have been trying to describe how humans recognise objects. A few thousand years later, we still don’t have a set rules that you can apply to determine if an image contains a bicycle (bicycles are a really hard problem for computer vision because the rims of the wheels don’t look connected while it’s in motion and important parts of the shape are often occluded). But we do have a lot of pictures that contain bicycles and a lot more that don’t. The same applies to a bunch of other pattern-recognition tasks.
I think the last one is where you object but it’s not so much giving up on theory building, it’s admitting that theory building hasn’t worked yet. If you come up with a set of rules for defining the pattern that you’re looking for / wanting to generate (a lot of ML techniques are reversible, so these end up being the same problem) then you can often build a much more efficient rule-based system. But if decades trying have failed to build one, a ML system that works some of the time might be more useful than the idea of a rule-based system that would work better in the future.
My problem with the current ‘AI’ push is that very few of the problems that tools being marketed as ‘AI’ address fit into these categories. This is particularly true of LLMs. The overlap between problems where a bad answer has no consequences and the problems where the solution involves generating text is tiny.
@david_chisnall @kevin for me the fundamental problem is for most things it's the wrong tool. There is an old joke that if all you own is a hammer everything looks like a nail.
I don't want an automated drunk Reddit shitposter telling me 'the answer is X' as my search result, I want an automated version of the good librarian who doesn't just sigh and say back 3 shelves downstairs but 'you might also want to look in X and the statistical collection has .. '
RE: https://aus.social/@Sinusoidal/117160796106027692
I’d seen this but not watched it and it wasn’t what I expected and it has absolutely ended me.
I was raised by someone who taught people to read: me, other kids, kids in schools, random adults who couldn’t, everyone. It was her core faith, that reading would protect us all.
