Statistical literacy, or any literacy for that matter, requires hard work that is seen as a normal way of life. When machines do that hard work for us, it is no longer seen as a normal thing, but some unnecessary hard work (when we have cars, why walk 20 miles? And we have machines that do statistics).
Just like how those college kids saw my work as horrifically weird hard work, while I saw it as a normal thing.
My interpretation is how the risks (statistics) of those job functions are more known, people choose to avoid them. But the people that are-the-statistic don't necessarily agree with or understand those statistics.
For example, if OP is a coal miner that hasn't had health issues yet, they may choose to discount statistics that declare x% of coal miners have negative health outcomes.
That's a new one for the cyberpunk dystopia bingo card: poor people renting capacity in their brains to multinationals. Makes you stupider, and the DRM implants give you mood disorders, but have you seen how much apartments go for in 2036?!
> For the minority of customers who are flexible on dates/locations and willing to plan in advance - most airline/hotel programs have sweet spots at the more premium level.
What does this mean? I'm not clear what the sweet spot is - are you talking about buying points/miles/etc outright with cash rather than earning them as credit card rewards? Everything I've read is that these are almost always bad deals.
It means that the vast majority of redemptions are a bad deal, but every program has gaps in their earn/burn charts that lead to good values.
There is no one-size-fits-all answer.
If you do not have time to look into it, plan trips 6-12 months in advance, or have flexibility (will go anywhere thats a deal), then they aren't worth it.
This is an interesting thought experiment, though I generally come to opposite conclusions. I personally think that hunting a wild animal situates the hunter in the broader context of the natural world, in which organisms live by their wits and try to outrun others doing the same.
Conversely, farmed animals owe their existence as you say to our cultivating them. But where you see a moral release in that connection, I see a corruption of life into industrial inputs. A hunted animal many times will catch scent or sound and take flight, winning their life for another day. Livestock can't change their destiny by wit or will. Their entire existence is within the technological apparatus of our species.
The corruption becomes evident in evolution cleaved from the organism's interest and placed in service of our appetites. In turkeys with breasts too large to be able to balance standing up, let alone walk. Such animals can only reproduce by artificial insemination and only eat when food is placed directly in front of them.
Power dynamics such as these tempt us to tell just-so stories about lives well lived. Can we say for them that their lives are preferable to not existing at all? We're surely not neutral.
> hunting a wild animal situates the hunter in the broader context of the natural world, in which organisms live by their wits and try to outrun others doing the same.
It's not exactly a fair fight though. In modern hunting the hunter might not always win, but he never loses.
> Can we say for them that their lives are preferable to not existing at all?
I doubt it. But we don't have to breed animals for maximum meat production at lowest cost in the shortest time. For instance the largest chicken producer in Norway [1] has declared that in future it will only produce slow growing chicken.
Hunting a wild animal is not necessary in most cases. Especially if we have farming. You had no say in the existence of that wild animal, you have no claim on it unless you need it to survive. Say you get lost in the woods and need sustenance to survive, that is excusable sure.
Farmed animals exist purely because of their use to us. We enable their lived experience. Without us they wouldn't exist, they wouldn't experience sitting in the grass looking at a sunset, running around in the field or whatever.
And I did mention it depends on their lived experience. I was not talking about the bleak industrial warehouses animals that never see the light of day and sit in bleak conditions. They don't get much out of it. I am sure we can figure out a fair exchange without getting locked in philosophical conundrums about it.
Since we're riled up about the state of compulsory tipping, I'll throw in my bugbear: the calculated percentages are frequently based off the post-tax total! Tipping has historically been based on the pre-tax cost, but the rise of receipts and screens that do the math for you has smuggled the taxes into the tip umbrella. Infuriating.
But that's the trouble, Python has the slogan about only one way, but it's really not true in practice. Or maybe there's the one way that "should" be done, and then the half dozen other ways you'll encounter in the wild, as gp alluded.
Python is the language where in practice this is most untrue - maybe outside C++.
As an example, there are dicts, tuples, classes, NamedTuples, dataclasses, attr.s, Pydantic, and pretty much all of those solve similar problem (hold my data) but have slightly different properties and use cases.
the slogan came out when the alternative was Perl, and in Perl you could do the same thing in a million ways, and each of them was equally "idiomatic".
> There should be one-- and preferably only one --obvious way to do it. [1]
Note the `should` and the `obvious`. Is it not a strict rule about having a single way to do things. It is about the aspiration that, if you do something, there is single obvious way to do it, much better than the others.
(I agree though that not even this is true anymore, see how many different ways you have to interpolate strings).
Aren't LLMs a way to somehow extract the one way it should be done (or to be more precise, the more common way), over the half other ways? That correct way might be more difficult to extract from another languages that encourage multiple valid ways.
Also, if you trust the benchmarks, it seems that Python is, at the very least, decent enough for LLMs. There seems to be "no trouble" in practice, unless you show us better proof than "I feel like it must be bad for this and that".
This looks beautiful. While obviously a Mac keyboard, to what extent is it compatible with Linux?
Will there be documentation of its features beyond a standard Bluetooth HID, such that users could potentially develop software that utilizes the speaker and haptic feedback mechanisms?
https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?location...
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