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Joined 1 year ago
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Cake day: June 12th, 2023

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  • That would run face first into proprietary info and corporate classified info.

    Behold all the fucks I do not give. If it’s that critical they lose all claim to being proprietary. It’s just like patent, there’s no such thing as a secret patent, so anything that safety critical doesn’t get to stay secret either.

    Regulation won’t detail what a company does to that level. They might say something like “fasteners shouldn’t come loose” but it wouldn’t have a torque spec.

    It doesn’t now but it’s utterly trivial to fix that. Just make the regulations say that components must meet the manufacturer specifications and require manufacturers to publish and maintain all the specifications of all safety critical components. If they want to keep it secret then that means it’s not safety critical and they’re responsible for any accidents resulting from its failure.



  • It’s because layering doesn’t really gain you anything so it only has downsides. It’s important to differentiate encryption and hashing from here on since the dangers are different.

    With hashing, layering different hashing algorithms can lead to increased collision chance and if done wrong a reduced entropy (for instance hashing a 256 bit hash with a 16 bit hashing algorithm). Done correctly it’s probably fine and in fact rehashing a hash with the same algorithm is standard practice, but care should be taken.

    With encryption things get much worse. When layering encryption algorithms a flaw in one can severely compromise them all. Presumably you’re using the same secret across them all. If the attacker has a known piece of input or can potentially control the input a variety of potential attack vectors open up. If there’s a flaw in one of the algorithms used that can make the process of extracting the encryption key much easier. Often times the key is more valuable than any single piece of input because keys are often shared across many encrypted files or data streams.


  • Banks usually have the absolute worst password policies. It’s typically because their backend is some crusty mainframe from the 80s that limits inputs to something absurdly insecure by today’s standards and they’ve kicked the upgrade can down the road for so long now that it’s a staggeringly monumental task to rewrite it all. Thankfully most of them have upgraded at this point, but every now and then you still find one that’s got ridiculous limits like a maximum password length of 8 and only alphanumeric characters (with no 2FA obviously).




  • A KDF is not reversible so it’s not encryption (a bad one can be brute forced or have a collision, but that’s different from decrypting it even if the outcome is effectively the same). As long as you’re salting (and ideally peppering) your passwords and the iteration count is sufficiently high, any sufficiently long password will be effectively unrecoverable via any known means (barring a flaw being found in the KDF).

    The defining characteristic that separates hashing from encryption is that for hashing there is no inverse function that can take the output and one or more extra parameters (secrets, salts, etc.) and produce the original input, unlike with encryption.






  • Ah yes, it’s…

    checks notes

    the US fault that Russia invaded Ukraine. Right, makes perfect sense, carry on.

    The only involvement the US or even most of the NATO countries have had in this complete shitshow has been to sell obsolete military hardware to Ukraine at a steep discount. It was probably cheaper to ship the stuff in bulk to Ukraine than it would cost to properly decommission it so might even have saved some money doing that.

    Russia desperately wants to make this a fight with NATO or even better the US so they look like less of a laughing stock for losing this badly.



  • CEOs have very little to do with the failure or success of most large companies. If they work very hard they can pull a company out of a death spiral, or start it down one, but failure or success takes years if not decades of steady improvement or decline. All the examples of “failures” given in the article are terrible and don’t demonstrate at all that those CEOs were bad.

    One of the worst problems with businesses in the US currently is this culture of fetishizing CEOs. They’re paid far too much for what they actually bring to companies, and people grossly exaggerate how much of an impact CEOs have on companies. If you want proof of his just take a look at literally any company Elon Musk is a CEO of. The fact that none of those companies (particularly Twitter) have filed for bankruptcy yet shows exactly how little a truly terrible CEO actually impacts things.



  • I seem to recall a big kerfuffle around a decade and a half back about Russia not actually knowing what became of a whole bunch of nuclear weapons in the aftermath of the USSR collapsing. There were also rumors of Soviet nukes being sold off to various unsavory groups. It really wouldn’t surprise me to find out there was some truth to that.

    I have also heard that ICBMs and the like require regular expensive and specialized maintenance in order to remain functional. Knowing what we now know about Russia what do you figure the odds are that some general or other decided those maintenance funds would be better used to line their pockets since the odds of actually using those nukes were so low?



  • LLMs are basically just really fancy search engines. The reason the initial code is garbage is that it’s cut and pasted together from random crap the LLM found on the net under various keywords. It gets more performant when you ask because then the LLM is running a different search. The first search was “assemble some pieces of code to accomplish X”, while the second search was “given this sample of code find parts of it that could be optimized”, two completely different queries.

    As noted in another comment the true fatal flaw of LLMs is that they don’t really have a threshold for just saying " I don’t know that" as they are inherently probabilistic in nature. When asked something they can’t find an answer for they assemble a lexically probable response from similar search results even in cases where it’s wildly wrong. The more uncommon and niche your search is the more likely this is to happen. In other words they work well for finding very common information, and increasingly worse the less common that information is.