Rodents chewing through cables is a problem even in latitudes closer to the equator, where it can get hot enough that they don't (need to) seek an engine for its warmth.
This is precisely why well-designed enterprise-grade storage systems disable the drive cache and rely upon some variant of striping to achieve good I/O performance.
Are you writing this from experience? If so, is this from experience as a boss, as a low (maybe even average) performer, or a high performer? How do you know that your statement is true?
Not OP. But we all have different motivating factors each with their own level of efficacy.
As someone with ADHD (and who knows what else), I've found it very helpful to have some sort of colleague or peer or "boss"-type supervision or nudging, and I say this as a "high performer" if we want to use that term. This kind of motivation is almost non-existent in a WFH context as check ins and other such regular interactions are very high-pressure.
My point is that one cannot make blanket statements about "low performers performing better under supervision". I say this as someone who prefers to work from an office at least 4 days a week.
You're right, each of us have differing motivations. That doesn't give anyone license to promote their own point of view and tar everyone else with the same brush.
This comment isn't intended as an opinion on RTO, but one of the things that's helped me with ADHD has been to go for frequent walks after short bursts of work – I've actually thrived at remote work for that reason. We've all had to learn our own techniques to get our brains to cooperate with our goals.
How would we know that the AI didn't hallucinate when it translated a tablet? In other words, how could one trust the translation? A human translator can still provide some justification for their interpretation.
Also, "acquired" could simply mean that the museum paid money to a third party to, well, acquire the piece(s) in question while not inquiring too deeply into how said third party came into possession of the objects that they sold.
I remember a time team episode where they found some Ogham script on a stone in an early Christian church now on a fairway on the isle of Mann.
They got photos to the leading professor in Ogham who translated it for them.
I happened to mention this on HN a few months ago in relation to something or other, and a commenter replied to me to explain that that translation was no longer sound, and the current understanding was that the tablet said something completely different instead!
If it wasn't an LLM that found the professor's mistake then the point I think you're trying to make is, well, missing the point: a human made a mistake, and humans found out and corrected it. The question is what happens when LLMs make mistakes. Will people still be careful enough to catch and correct them, as often as we find and correct the mistakes we make ourselves? Or will our ability to do so be overwhelmed by the extreme rate at which LLMs can generate text?
My point was more meta - the experts don’t have a fixed opinion on the translations of rare ancient texts in the first place, ergo there is nothing to train the llma on.
Thanks for clarifying. But note that the same applies to modern translations. There is no agreement between experts (translators) what it means for a translation to be "good" or "bad", or anything in between.
So the done thing in translation is to choose some existing translation as a "gold standard" and use that one, without any assumptions of how good or bad it is. Sometimes there's an attempt to rate translations by polling humans but that can not be easily done at scale and certainly not at web-scale, as in LLMs (the modern de facto standard for automatic translation as far as I can tell; I haven't been watching the field closely lately).
The same logic is applied to metrics like BLEU and ROUGE scores, used to measure the goodness of a translation. The general idea is that you choose a translation to be the "gold standard" and then compare the n-grams in the gold standard, and the automatic translation, for overlap.
It's a very crude and imperfect measure and it's one reason why, in practice, we have no idea how good automatic translations are especially now that automatic translation systems are deployed and working every day with millions of input and output texts that nobody can reasonably be expected to evaluate.
In any case just because there's no fixed opinion on what is a good translation, doesn't mean an LLM can't be used to produce one. It probably will. Assuming I understand your point better now, I agree that this is going to cause trouble down the line.
This is the same thing as trusting its translation though. Or worse, since there's more "interpretation" happening (as it's basically a summary rather than a whole text, and you can't trust either of those steps).
It's like using a classifier to sort biopsies from most-likely to least-likely to be Really Bad News. A human will get to them all eventually, but you can at least fast-track the ones that are almost certainly Really Bad News.
(I think I just said "triage" in a lot more words, to be honest).
Sure, as long as one has some means of predicting the probability of false positives as well as false negatives. Until then, colour me unconvinced of the (f)utility of this approach :)
LLMs do a pretty darn good job of translating other languages, even preserving inflection and tone and rhyme in some cases. Same when translating programming languages. If the training pool is large enough, they should be quite good at it.
No problem marking them as machine translated and keeping track of which have been spot-checked by experts either.
I think "if the training pool is large enough" is a real issue here. We're not talking about living languages with large, properly attested and annotated corpuses.
Indeed, one of the thing you'd probably like the translators to do is identify rare or unique words that can be added to our existing knowledge of these languages.
> I think "if the training pool is large enough" is a real issue here.
It would be really neat to set up something like a wiki populated with the existing translations and machine translations done via LLM, and to periodically re-train the LLM on all the newly manually verified translations and automatically re-run the machine translations after. The whole thing could move incrementally toward high quality output.
It should be possible to achieve the same end by forcing management to use the "hardware of the people", getting them to do nontrivial on-call duty frequently, and making them dogfood what they make.
The real fucking assholes are the ones that enable the fucking assholes you refer to.
Erm, the concepts that you're referring to are independent of the language being used. The author is free to use whatever language they want. The GP (I think) was merely trying to make a point about making the article accessible to a wider audience that is capable of appreciating the concepts involved.
If you can't understand the code snippets in this post, the concepts will most likely be lost on you, no matter what other language would be used for the code.
Isn't that precisely the point that the GP was trying to make, about the accessibility of the article?
Edit: Eytzinger layout, Cache lines, SIMD, et cetera are independent of the particular language used in the article. They're just as valid in C, for example. I don't understand your point about them being tied to Rust.
I think you mean "a lot of people in the USA" :) In most of the other parts of the world, people would either see the wisdom of this approach because they understand good government, or not bat an eyelid because they're used to bad government (and consequently overreach).
Yeah in the Netherlands most young people don't smoke anymore. In Spain a lot of them do and people even smoke in clubs etc while this is banned EU wide.
Any system can, and will, be abused by the powers that be. Any system that can be abused, will be abused by people with power. There is a clear disparity in power between an IC and a manager.
The "oh, I totally deserved my PIP, so all PIPs must be fair" stories assume that all corporate actions are taken in good faith.
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