One week with the iPhone Air. Setup, hand feel, thinness, drops, battery, VoiceOver, and all the ways it works (and doesn’t) when you actually live with it.
Friday.
Still no baby.
The painter's on her last day today. The shelves and TV brackets are all going back up tomorrow, ready for the new carpet on Tuesday.
Got the first of the new sofas moved up to the day after the carpet, which is quite handy. Baby really should be out by then!
Did I miss some blindy drama? I'm hearing people are locking their accounts.
I think this needs to be repeated, since I tend to be quite negative about all of the 'AI' hype:
I am not opposed to machine learning. I used machine learning in my PhD and it was great. I built a system for predicting the next elements you'd want to fetch from disk or a remote server that didn't require knowledge of the algorithm that you were using for traversal and would learn patterns. This performed as well as a prefetcher that did have detailed knowledge of the algorithm that defined the access path. Modern branch predictors use neural networks. Machine learning is amazing if:
- The problem is too hard to write a rule-based system for or the requirements change sufficiently quickly that it isn't worth writing such a thing and,
- The value of a correct answer is much higher than the cost of an incorrect answer.
The second of these is really important. Most machine-learning systems will have errors (the exceptions are those where ML is really used for compression[1]). For prefetching, branch prediction, and so on, the cost of a wrong answer is very low, you just do a small amount of wasted work, but the benefit of a correct answer is huge: you don't sit idle for a long period. These are basically perfect use cases.
Similarly, face detection in a camera is great. If you can find faces and adjust the focal depth automatically to keep them in focus, you improve photos, and if you do it wrong then the person can tap on the bit of the photo they want to be in focus to adjust it, so even if you're right only 50% of the time, you're better than the baseline of right 0% of the time.
In some cases, you can bias the results. Maybe a false positive is very bad, but a false negative is fine. Spam filters (which have used machine learning for decades) fit here. Marking a real message as spam can be problematic because the recipient may miss something important, letting the occasional spam message through wastes a few seconds. Blocking a hundred spam messages a day is a huge productivity win. You can tune the probabilities to hit this kind of threshold. And you can't easily write a rule-based algorithm for spotting spam because spammers will adapt their behaviour.
Translating a menu is probably fine, the worst that can happen is that you get to eat something unexpected. Unless you have a specific food allergy, in which case you might die from a translation error.
And that's where I start to get really annoyed by a lot of the LLM hype. It's pushing machine-learning approaches into places where there are significant harms for sometimes giving the wrong answer. And it's doing so while trying to outsource the liability to the customers who are using these machines in ways in which they are advertised as working. It's great for translation! Unless a mistranslated word could kill a business deal or start a war. It's great for summarisation! Unless missing a key point could cost you a load of money. It's great for writing code! Unless a security vulnerability would cost you lost revenue or a copyright infringement lawsuit from having accidentally put something from the training set directly in your codebase in contravention of its license would kill your business. And so on. Lots of risks that are outsourced and liabilities that are passed directly to the user.
And that's ignoring all of the societal harms.
[1] My favourite of these is actually very old. The hyphenation algorithm in TeX trains short Markov chains on a corpus of words with ground truth for correct hyphenation. The result is a Markov chain that is correct on most words in the corpus and is much smaller than the corpus. The next step uses it to predict the correct breaking points in all of the words in the corpus and records the outliers. This gives you a generic algorithm that works across a load of languages and is guaranteed to be correct for all words in the training corpus and is mostly correct for others. English and American have completely different hyphenation rules for mostly the same set of words, and both end up with around 70 outliers that need to be in the special-case list in this approach. Writing a rule-based system for American is moderately easy, but for English is very hard. American breaks on syllable boundaries, which are fairly well defined, but English breaks on root words and some of those depend on which language we stole the word from.
The pattern-matching is making Google searches more useful for me.
But I am entirely against referring to any of this stuff as ‘artificial intelligence’. It actually is not even an ATTEMPT to solve the problem of artificial intelligence. It is only mistaken for an attempt to solve that problem.
I have a simple proof of this: artificial intelligence cannot possibly be reached by ‘language models’ of any kind. Why not? Because a human is nearly the same as a language-less ape.
Everything that people mistake for ‘AI hallucinations’ and so forth are easily understood if you simply view all the ‘AI’ not as ‘AI’ but as pattern processing algorithms.
True artificial intelligence would be an entirely different problem. The people doing the pattern processing are probably incapable of understanding the difference between the two problems, however.
Apes truly are language-less BTW. People sometimes object. But true language has infinitely recursive structure. No animal has language in this sense.
And human intelligence MUST be a variant of ape intelligence. Therefore must have language only as an adjunct facility, not as a foundational one.
I expect LLMs never to be any good at mathematics. They claim otherwise, but what they demonstrate is only that it can solve high school math tests, which isn’t the same thing.
@hosford42 It could also be ‘visualization’.
Most mathematics is really geometry. Even non-geometric stuff is usually solved by converting it to geometry. Whathisface proved Fermat’s last theorem by geometry.
I'm not good at maths, I'm not good at thinking visual things like: a dice spread out as a plane. But when someone talks in metaphors I see the images in my head. 😅 I didn't know proprioception and math were linked. I would like to hear more about this!
I mean proprioception in the sense of navigation. Knowing left and right. That sort of thing. Which obviously fully healthy apes are very, very good at.
(I’m not so extremely healthy these days, but that’s partly because I am old now. If I turn rapidly, I’ll likely fall down. :) )
People may be better at mathematics than they realize. Teachers are very, very, VERY bad at teaching it.
> People may be better at mathematics than they realize. Teachers are very, very, VERY bad at teaching it.
I second this. I cringe every time my girls, who are both *very* good at math, say they hate the subject. It has everything to do with the teachers. I think the education program for teachers misses something that must be vital for effectively teaching math, especially in a way that makes kids feel competent and enjoy the subject. At least, that's how it is here in the US.
WHat the "anti-ai" people forget about is that humans also make mistakes, and each mistake has a price associated with it.
It's also worth remembering that some people would prefer cheap AI that sometimes makes mistakes over expensive but reliable humans, even in fields like law or healthcare.
The one thing AI is really bad at is being a scapegoat, and sometimes what you actually need is a scapegoat.
das schlimme ist, das ich wichtige mails verschicken wollte, aber bisher nicht konnte. Das finde ich gelinde gesagt, sehr beschi**en.
War bisher zufrieden mit euch, aber in den letzten monaten, bin ich nicht mehr so zufrieden. Hab auch an euren support eine mail geschickt, diese ist versendet worden ? Jedenfalls kam kein fehlermeldung.
Kann es sein, das mein account gesperrt wurde ?
Anyone using RPi Camera Viewer (apt.izzysoft.de/packages/ca.fr…)? Is it still working and useful? Its last release was made in 2019, and not even issues are replied to anymore since at least 2020 – so we wonder if we should remove the app from #IzzyOnDroid
„RPi Camera Viewer“ – IzzyOnDroid F-Droid Repository
play a raw H.264 stream from a Raspberry PiIzzyOnDroid Repo Browser
Linux users when they need to remember a simple command in the terminal:
⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️ Aha, there it is!
Story Credit: Steve Farmer
reshared this
Just released #Tusky 31.1
It reverts the media picker from Tusky 31 back to the one from 30 and makes it buildable for FDroid again.
You're welcome.
@fireborn some countries give non permit to drive driving licences which would be easy to do in the UK. Just give the DVLA a bit more money. I'd probably still have a passport as well (I can't drive for disability reasons) but a a more portable thing would be useful.
ID cards like proposed wouldn't fix the claimed problem and I don't trust any governments right now
I started thinking about when we should adapt #curl's progress meters to deal with > 63 bit download sizes (8192 Petabytes).
I'm thinking it might not be terribly far away when people can start downloading that. In particular when doing N super huge transfers in parallel.
Got me thinking about 128 bit math...
Štěpán Škorpil reshared this.
Every `cargo add` or `pip install` is a leap of faith that attackers exploit.
Supply chain attacks are escalating: from typosquatting campaigns to self-replicating worms like Shai-hulud (compromised 500 NPM packages) to the XZ Utils backdoor where an attacker spent 2+ years building their reputation.
But the ecosystem is working to make trust explicit and verifiable rather than assumed with cutting-edge defense, like Trusted Publishing.
Read the blog: blog.trailofbits.com/2025/09/2…
Supply chain attacks are exploiting our assumptions
Supply chain attacks exploit fundamental trust assumptions in modern software development, from typosquatting to compromised build pipelines, while new defensive tools are emerging to make these trust relationships explicit and verifiable.Brad Swain (The Trail of Bits Blog)
So refreshing to see actual thought-through improvements that are well designed as opposed to the general garbage of asking for your ID and assuming that just because the publisher knows your legal identity (or that of the ID card you stole/faked) nothing can go wrong.
The Open Source community is so far ahead in security compared to big tech like Google. It's both amazing and absurd.
Great work, thank you for improving security in tangible and logical ways :)
Muss das „Café Pförtner“ schließen?
Mit jedem Tag mehr schwinden die Chancen, dass die Kult-Kneipe bei den Uferhallen in ihrer jetzigen Form bestehen bleibt. Er hat es tatsächlich getan.Weddingweiser
@libreoffice@fosstodon.org I'm noticing that it seems to take disproportionately much longer to save an ODT document with tracked changes than one without. It's a difference between one or two seconds, or fifteen to twenty seconds of 100% utilization on one core.
Is this behavior (a) known, and (b) expected?
(I'm not completely certain that it's track-changes involved. It might also be a factor of having at some point been saved as .DOCX. I do not have a full history of all changes made to the relevant document.)
Swap: 0B 0B 0B
Ťažký týždeň 👔: O Slovákovi, Japoncovi a českých voľbách (27/2025) | Aktuality
📣 Hovorí sa, že keď je somárovi dobre, ide sa na ľad šmýkat. Ako dobre sa majú Česi - možno vôbec najúspešnejší postkomunistický národ - ukazujú mnohé štati...YouTube
Prodáváme nás Croozer, kdyby někdo měl zájem dám o 1000 Kč dolu. Za boost budu vděčný. 🙏
deti.bazos.cz/inzerat/20841283…
Croozer kid for one + odpružení Dogy - Ústí nad Labem
Inzerát č. 208412831: Croozer kid for one + odpružení Dogy, Cena: 5 000 Kč, Lokalita: Ústí nad LabemBazos.cz
Lots of data and neat graphs here illustrating the global problem of #inequality and how it is distributed across the world.
Puts into perspective quite a few often repeated myths. Have a look!
Work of the reknowned degrowth scholar Jason Hickel (who still has an inactive fedi account @jasonhickel )
What Apple is trying to pull in the EU is as embarrassing for Cupertino as it is for the EU and the tech press that have credulously repeated Apple's talking points. The only good news is that the EU declined to unilaterally disarm:
infrequently.org/2025/09/apple…
Apple's Antitrust Playbook
Apple wants to launder the consequences of its own anticompetitive, anti-user choices through a credulous tech press. The goal is to frame regulators for Apple's own deeds, and it's rotten to the core.Alex Russell
GOP lawmaker calls for Dem congresswoman to be executed for urging Trump protests
Arizona GOP Rep. John Gillette calls for hanging Democratic congresswoman over nonviolent protest remarksJerod MacDonald-Evoy (Arizona Mirror)
I just got an email from Guide Dogs for the blind where I have gotten my four Guide Dogs. They are following up on the announcement of the suit brought against Uber for its persistent ADA violations against those with disabilities, especially those with Guide Dogs. They urge all guide dog users to keep reporting ride refusals. They had a few helpful numbers I wanted to share along with the Department of justice website where you can register complaints. Here's what the last part of this email had to offer. Guide Dogs for the Blind remains steadfast in our support of everyone’s right to ride. We will continue to advocate as an organization and in concert with like-minded groups, and we encourage you to continue doing so as individuals.
To report violations, visit CivilRights.justice.gov. For ADA resources call the ADA Information Line at 800-514-0301 (TTY: 1-833-610-1264) or ada.gov
God help us
“A new report from Senate Democrats claims members of Elon Musk’s DOGE team have access to the Social Security Numbers of all Americans in a cloud server lacking verified security measures, despite an internal assessment of potential “catastrophic” risk. The report, released by Sen. Gary Peters (D-MI), cites numerous disclosures from whistleblowers, including one who said a worst-case scenario could involve having to re-issue SSNs to everyone in the country.
As outlined in the report, DOGE staffers moved a live copy of Americans’ personal information to a cloud server despite an internal risk assessment done by the Social Security Administration (SSA) that determined the impact could be “catastrophic” without the proper safeguards. The report notes that this information is considered “production data,” potentially allowing DOGE to “directly manipulate” it.”
#doge #tech #ssn #news #security #privacy
theverge.com/news/785706/doge-…
DOGE might be storing every American’s SSN on an insecure cloud server
A new report from Senate Democrats reveals that Elon Musk’s DOGE has moved sensitive information, including Social Security numbers, to a cloud server without verified security measures.Emma Roth (The Verge)
Mitch Hedburg
#UN #escalatorgate #TripleSabotage
youtube.com/shorts/tqOkWWV6a_U…
"An escalator can never break..." 🎤: Mitch Hedberg #shorts
Paramount+ is here! Stream all your favorite shows now on Paramount+. Try it FREE at https://bit.ly/3qyOeOf#CCStandUp #ComedyCentralYouTube
Also thank you to those who sent physical and virtual gifts. They are appreciated.
Today was a wonderful day.
Zach Bennoui reshared this.
Cleverson
in reply to Matt Campbell • • •James Henstridge
in reply to Matt Campbell • • •I imagine one of the reasons for the change was that the "centi-" prefix is commonly used to modify other units (most commonly centimetres). You've then got the question of whether "grade" is a unit.
Also, dividing something by a power of 10 is not that uncommon in countries using the metric system. Also, Fahrenheit is also defined by dividing a chosen temperature range into 100 parts, so it's not even unique to temperature units.