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Botch Frivarg
deetwenty@todon.nl
Another one from the archives!
#FursuitFriday #Fursuit #Furry #Inflatable #Photography
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miifox
miifoxPhoto by @deetwenty
It is a photo of Bob falling of…
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miifox
miifoxThe debrie sept combined the basic functions of a modern dslr (shooting photo's and shooting video's) with 5 other functions that you might not expect:
- put a lamp behind it and it could become a slide projector or a movie projector
- of course that also meant you could use it as an enlarger
- you could use it to make duplicates (contact prints) of your photo's and video's thanks to two extra slits in the body (which of course, makes positives out of your negatives)
- and of course you could use it for burst mode shooting, and they did not cheap out on bulb mode either.
It combined all this in a relatively small, albeit heavy, package. Interestingly it predated our "modern" 35mm film cartridges so instead it had these proprietary cartridges which would hold about 250 photo's or 17 seconds of video. And thanks to it's simple but reliable mechanism, it's surprising versability, and the french ability to mass-produce the original italian design with good french lenses; it saw a relative success in a pre-leica era, with an estimated 10 000 units build.
Anyways i gotto admit the camera is neat, and seeing how many units are still ticking after 100 years of usage makes me wonder what the world will look like 100 years from now.
https://cameracollector.net/debrie-sept/
https://www.kinocameras.com/apparatus/sept
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DanCrescentWolf
dancrescentwolf@pounced-on.meI loove how they look next to each other so far OwO
#pride #pridecore #lgbtq #LGBWithTheT #furry #furryart
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Clep-Karb @ 🏠
karb@bark.lgbt"Summer might be over, but that doesn't stop these fancy Foxes to have a great time lounging in the pool."
Kelix, on the left, is owned by https://bsky.app/profile/asreyhyena.bsky.social.
🎨 Artwork drawn by https://www.furaffinity.net/user/seibear
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LunaticWorkshop
LunaticWorkshop@meow.socialCommission for Azzu! I'm SO happy with how this turned out! ^^
https://www.patreon.com/user?u=2743472 - https://t.me/+3MKWYwE7-0ljZmNh - https://discord.gg/C3mVG7c
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David Chisnall (*Now with 50% more sarcasm!*)
david_chisnall@infosec.exchangeI 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.
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Jeff Geerling
geerlingguy@mastodon.social
Any bets on how long until yt-dlp will have to switch to a full browser automation stack (ala selenium, playwright, etc.) to snag YT videos? https://github.com/yt-dlp/yt-dlp/issues/14404
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DanCrescentWolf
dancrescentwolf@pounced-on.meAnd finished piece for @barrenform :D 
#furry #furryart #transgender #TransRightsAreHumanRights #LGBWithTheT
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LawyerDog
LawyerDog@yiff.life
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Foone🏳️⚧️
foone@digipres.clubman when people were telling me that smart TVs are a privacy nightmare, I thought that was because they recorded what you watched using their built in media-player OS.
NOPE! Apparently Roku TV's will give you popups based on what DVDs you're watching through them, because they screenshot the HDMI-in and compare it to a database.
that's a few steps creepier than I was expecting from a garden variety privacy invasion
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Koko
ic5146@meow.socialI would like to make people aware that the Class 91 electric locomotives in the UK had a cab on their "blunt" end until it was removed afaict due to low usage. That is all :3
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Botch Frivarg
deetwenty@todon.nlShow content
Got this beautiful pinup by Skiaskai (https://bsky.app/profile/@skiaskai.bsky.social)
On a related note does anyone know where I could get a latex suit kinda like this in real life (something with sleeves would also be fine to be honest)?
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miifox
miifoxSomehow this came out better than I was expecting. Featuring me as the diva in fursuit, and the lovely @deetwenty sitting still for longer on the ICF Eira than I should admit.
https://todon.nl/@deetwenty/115204191398001952
#analogPhotography #yesThisWasAPainInTheAssToMakeYetI'llDefinitlyDoItAgainOnceIGetBetterFilters
It is a fursuiter fennec girl o…
It is a wolf fursuiter riding a…
It is the same fennec girl as e…
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Qasim Rashid, Esq.
QasimRashid@mastodon.socialHey by the way South Koreans are now reporting they were put in chains and treated like animals for 7 days after ICE raided the multi-billion dollar plant they were setting up for the benefit of 8500 high paying American jobs.
They had valid visas.
They were here legally.
They did everything right.
Trump still treated them like animals.
It was NEVER about "legal" immigration. It was always about banning non-white immigration.
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