#technology

8057 posts · Last used 49s

Data center gear is being hijacked in transit to the tune of hundreds of millions — grand-theft-GPU thieves hack accounts, perform hit-and-runs, spoof GPS signals, and funnel hardware to China.
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As we creep up on the end of the year, I'm creating an #introduction post because .. apparently I didn't have one :) I'm Dawgeth aka Matt. I'm a husband, dad, software architect, engineering manager, tinkerer, gamer, and generally curious person who has a hard time leaving well enough alone. A few things you'll find me talking about: #Technology - Software architecture, engineering, automation, and figuring out how things work. #Linux - Self-hosting, homelabs, open source, and running services just because I can. #Gaming - Steam, GOG, Xbox, and more .. I bounce around a lot! #Programming - Building little projects, experimenting with new ideas, and occasionally turning a five-minute problem into a weekend project. #Politics - Hanging out on the left, progressive, interested in local government, civic engagement, and making things a little better for everyone. #Community - Building spaces where people feel welcome, whether that's online, in the neighborhood, or around a table. #Makers - Small business adventures, creative projects, crafting, and supporting people who make things with their hands. #Gardening - Growing food, learning as I go, and maintaining the illusion that I know what I'm doing in the garden. #Family - A big family, a busy household, and plenty of reasons to appreciate the little things. I'm a firm believer that curiosity is a pretty good way to spend a life. I have too many interests, too many projects, and probably too many browser tabs open. Happy to meet new people, exchange ideas, talk shop, or just enjoy the occasional bit of internet nonsense. Here's to another year of figuring things out!
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Pulley's Shutdown Announcement: Founders, what is your next move? The announcement that equity management platform Pulley is shutting down operations on December 8, 2026, has left thousands of founders scrambling to migrate their cap tables. Beyond the logistical friction of finding a new home for equity data before the platform goes dark, this situation highlights an important structural reality about startup governance and data sovereignty: Where does your system of record actually live? Source: x.com/BusinessInsider/status/2099948911301411075
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Boosted by @fedicat@pc.cafe
#lispyGopherClimate #lisp #technology #weekly #live #podcast #climate On #peertube at 0UTC (aka Tuesday-night-in-the-Americas, basically now.): https://toobnix.org/w/s7sKUP8qXMppDHLVk3uksY I had the flu this past week ! - This great thread of floating point arithmetic quotes: https://mathstodon.xyz/@dougmerritt/117514297690238051 Otherwise, we will be joined by the @kentpitman@climatejustice.socialhttps://compbio.hms.harvard.edu/people/kent-pitman/ and maybe others ! @ramin_hal9001@fe.disroot.org @jhlagado@defcon.social#liveChat in #lambdaMOO #VR as always. https://lambda.moo.mud.org Happy MOOnniversary!
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AI Video Generators: Is Better Control More Important Than Visual Quality? I’ve been looking into how AI video tools fit into actual content production, and one question keeps coming up: how much does creative control matter compared with visual quality? A generated clip can look impressive but still be difficult to use. The camera might move in the wrong direction, a character’s appearance can change, or the action may not match the original idea. Features such as reference images and keyframe guidance are interesting because they aim to give creators more control over these details. I’m involved in promoting Kling 4.0, which describes reference-guided generation and multi-keyframe controls. I haven’t independently benchmarked its results, so I’m especially interested in experiences from people using similar workflows. For those creating AI videos regularly: Do references noticeably reduce the number of revisions? Is character consistency still your biggest problem? Would you rather have better-looking first attempts or more precise control over the final result? I’d be interested in hearing what actually works in production, not just what looks impressive in demos.
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The exponential time hypothesis is false cross-posted from: lemmy.world/post/53647234 OpenAI (and allegedly anthropic?) had models prove that the ETH is false. The proof is short, relatively easy to read, and the construction is not esoteric: I believe this is very likely correct. The Exponential Time Hypothesis (ETH) is the conjecture that it takes exponential time to solve 3-SAT. 3-SAT (short for satisfiability) asks how long it takes a computer to find a solution to a boolean equation of the form (A or not B or C) and (not A or D or E) and (F or not C or D) … where there are $n$ boolean variables and $m$ clauses. It was believed that this should take, essentially, $(4/3)^n$ time for the fastest algorithm (roughly equivalent to brute forcing all possible boolean values for the variables). But it is possible to do much better. They give a divide-and-conquor algorithm based on polynomial interpolation that runs in roughly $2^{n/log(n)}$ time (which grows slower than $b^n$ for any $b>1$). This implementation isn’t useful for SAT instances smaller than the universe, so internet security is fine. But often these algorithms get improved. This is shocking; it was pretty widely believed that ETH was the reason that P!=NP. It has fallen; will any other barrier survive? (I acknowledge that folks do not like AI solving open questions. This problem is not like most problems; this is closer to curing cancer than painting a picture. ETH has consequences, and if this approach has a shred of improvement over existing SAT solvers (which it does, or a human would have published this earlier), it will save energy, lives, and resources for humanity for awhile to come.)
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