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pure water at mean atmosphere pressure at sea level if we’re getting technical, but frankly human body temperature varies from 35.5C (95.9F) to 37.5C (99.5F) anyway, and that’s before considering when people are ill, so if we go down that route it falls apart quickly enough that the definition of 100 given above is clearly just as arbitrary
Are they identical objects?
Storage forensics can look into variations in charge to suggest “this used to be a 1” or “this used to be a 0”
To store more data that way, it’d have to be analog data in reality, as otherwise data loss due to charge decay would be immense so you’d need so much error checking you’d lose most of the storage savings
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.
The reason they have to manipulate the audience is because people look for validation and so feel good when other people react to things in the same way as them. If another equally funny show has a laugh track and you don’t, yours will likely be less enjoyable to watch unless it’s a specific form of humour which benefits from not having a laugh track.
Basically a laugh track can’t save a terrible show, but it can manipulate people into finding a mediocre show more enjoyable to watch, but a mediocre show will make people laugh organically at least a few times anyway.
It’s pretty common in Northern English and I think maybe also Australian:
https://www.journal-labphon.org/article/id/6239/
The fact it’s not only possible but regularly used when the expectation is that it’d be hard to do without choking is why it’s such a weird word
it’s very rare in any language, complexity at the start is not uncommon, but complexity at the end is, also the ordering of the consonant types and the fact there’s two fricatives in a row at the end, it’s not just a word that not only has no place existing, but also one that should be so unstable it’d change to something less complex in decades at most, yet it’s stayed pretty consistent for a while
It’s also actually 4 consonants as there’s an unwritten k in many accents, or ng is pronounced as ŋg in others, so stɹɛŋ(k|g|∅)θs
