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Joined 2 years ago
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Cake day: June 9th, 2023

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  • This is Rust not Python

    They’re both optimised out by the compiler. If you disable compiler optimisations, they’re identical in machine code anyway, unless you introduce a second loop, in which case the first will be more memory efficient as the memory used in the first loop can be reused in the second loop, whereas if you declare the variable outside the loop it can’t (again, without compiler optimisations, which make the whole comparison pointless).




  • 1rre@discuss.tchncs.detoMemes@lemmy.mlTank engine
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    1 month ago

    I was under the impression it was the intersection of the venn diagram of communists and imperialists, as long as imperialist means imperialist (defined as using economic, military, diplomatic and cultural power to influence countries around you in a way that is beneficial to you, and may be either beneficial, inconsequential or detrimental to them) and not just “western and capitalist”




  • I get it’s a big jump, but I’ve been clear I’m restricting it to the most popular types of beer and explained why US bred and grown hops had the good fortune to be the most aromatic disease resistant hops, so I still don’t think it’s unreasonable

    Again, none of this applies for styles beyond 3-7% golden beer fermented with yeast only, and even then there’s a few exceptions for certain styles where the aromatics are different (eg bitter, which is less about the aromatic hops and more about the earthy notes of the bittering hops), but for the most popular lagers and pale ales I think it holds


  • So there’s obviously a split between objective fact and opinion and conjecture, but:

    • Outbreaks of powdery mildew in the early 20th century meant it became somewhat infeasible to grow most aromatic and flavoursome hops, leading to research and breeding programmes to produce disease resistant hops with other desired characteristics
    • Most of the mildew-resistant hops were wild and from the US and Canada
    • Hop breeding and research started in the UK but ended in the 2000s
    • Oregon State University has been breeding hops for almost 100 years
    • The USDA also has their hop research center in Oregon
    • The US is responsible for 40% of hop production, of which over 98% is in Oregon, Washington and Idaho
    • Cascade hops, from the USDA research center in Oregon, started the craft beer movement due to the combination of high flavour and disease tolerance
    • German hop research started in 1926, but only had any real success after the 1980s

    So essentially, the US has just got very lucky when it comes to hop production with good soils and disease resistance, while German beermaking was set back leading other styles to become and remain popular, such as very lightly hopped wheat beers, sour beers where the acidity comes from the fermentation instead of hops, and more recently Belgian style beers that are stronger abv so the stronger alcohol taste substitutes for some of the strength of the hops

    There probably are also studies, but they tend to look into mechanisms/variations whereas this is more of a series of coinciding factors which don’t really need much research to make sense


  • That’s why I said average at best - average beer is going to taste way better than bad beer and also perfectly acceptable, I don’t mean it in a negative way, just that in the standard 3-7% golden beer fermented with only yeast category, Cascadian & New Zealand hops provide the best and widest array of tastes regardless of what you’re after, as that’s where the soil is best and where the breeding is generally done




  • 1rre@discuss.tchncs.detoMemes@lemmy.mlCultural enrichment
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    2 months ago

    Thanks for proving my point that you reject even being offered evidence because you don’t want to see something that challenges your worldview.

    I could’ve spent time compiling a list, but you’d either ignore it or say it’s a biased source because it’s non-chinese or something.


  • 1rre@discuss.tchncs.detoMemes@lemmy.mlCultural enrichment
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    2 months ago

    incontrovertible

    The issue is, genocide deniers are very keen to dispute any readily available facts - Holocaust, Armenian Genocide, Holodomor, etc deniers, along with flat earthers and other far-fetched conspiracy believers are willing to reject swathes of evidence and released documents that show intent and execution; I could link you interviews with Uyghurs saying they were forceably steralised or reeducated from respected sources (and am happy to) but it seems like you’ve already made your mind up so will just be selectively blind when reading them








  • As someone who works in advertising, that is partially true, but also not the complete story…

    Data brokers want you to believe that the more data you have the more likely your ads are to be successful, but in reality it’s not about the amount of data but the quality of the data. If you have someone who has looked at reviews of gym shoes/different models on different stores, then that data is pretty valuable as you can focus on getting them to buy from your store or try and advertise models at the top of their budget, which will likely lead to a higher ROI than just advertising on fitness forums (note it is super hard to get the balance between tipping people over the line to buy and advertising them something they were already going to buy/had already decided against - Google particularly are absolutely terrible at this, but also do evaluation in house, so they’ll misrepresent to advertisers that your ad which showed up one link above your non-sponsored link made 100% of the difference in getting the purchase). Similarly, if you have data that someone is active on a car audio forum and recently bought a specific model of car, you can advertise kits/speakers specifically to that car, which is better than just advertising “hey, we make audio upgrade kits for [specific car/cars in general] on a forum/related site”.

    This also makes advertising one of the few situations where using ML actually makes sense - there’s huge amounts of data (way more than a person can consider) to come in, and patterns which lead to good results (someone purchasing something) or bad results (someone not purchasing something). It’s not worth a human targeting every single microcategory, but if an ML model can pick up that advertising to (eg) people who have recently purchased cameras who are interested in triathlons and often visit areas with with high rainfall makes them more likely to buy your specific aftermarket lens hood, then it makes buying the ads so much more worth it and also lets you extrapolate onto other microcategories which may also have similar results, and if they don’t then that updates the model.

    Generally data is less useful for awareness campaigns (ie “next time you’re in the supermarket/in the business for x, buy our brand” type of campaign), especially if it’s already on a relevant site, but it’s still somewhat useful if someone is reading on a (trustworthy) news site or watching an ad-supported streaming service, however purchase data & activity data is still useful for showing more relevant ads, as while 90%+ of people on a fitness forum are going to be into fitness, I don’t think 90%+ of general site visitors or tv show viewers are going to be into anything specific enough to make it worth it to advertise it.