The AIs have been trained on text written by all of those terrible writers. They produce something like the cultural average response to any prompt - a little bit of Stephen King, a little bit of Jane Austin, and a little bit of u/TikiUSA - "OK not great" is exactly what you should expect.

Almost anything reported in dollars is going to lookbe exponential because of inflation and population growth.

It is because the Boomers are exiting the workforce that SS revenue falls relative to expenses, causing that peak in assets.

It depends what you're trying to show. Wind speed vs power for a single turbine is just physics. Weight all of the local wind speeds by the number of turbines on the grid, and you'd get a more precise national estimate. Based on OP's comments, I'd guess that a lot of Germany's wind power comes from Bremen.

OP has produced a bunch of 'some kind of marker for windy day' against 'power from various sources.' The set lets you tell that wind substitutes for petroleum, presumably because gas and oil plants are more dynamic than nuclear or coal. It seems like he's picked a city that's reasonably representative and accessible to humans, rather than a complicated formula that might be more predictive but not useful to readers. It gives the impression that there's got to be a pretty good wind blowing before you get much out of wind.

Might be helpful to have a histogram of wind speed at the bottom, so reader can get some sense of how often wind power is a significant factor.

I'd like to see both median and mean for exactly that reason. My bias is that most of the compensation increase has gone to the top, and it'd be nice to see that bias tested. Top has definitely had larger gains than the middle and bottom, but the top is also a small fraction of the total.

A retirement planner is going to look at the amount of principal you need in order to sustainably generate annual spending. ie: not spend principal, but add to it for inflation.

TFA is just looking at how much gets spent. ie: spend all the principal in 15 years.

Still useful as a relative benchmark.

The scientific article isn't even about solar power, but about photodetectors.

The ustrend.us article reads like it was written by an AI.

As late as 2000, there was a note posted on the women's room of my uni's chemistry building reminding men that it's a co-ed campus (for 40 years) and men's rooms were 1 floor up or down - they'd swapped alternate floor restrooms rather than add women's rooms. The costs of increased enrollment and diversity don't show up in instruction, but in physical plant, construction, and elsewhere. So does the increasing luxury of campus accommodations. Compared to the 80s, every building now seems to have its own coffee shop; quad dorm rooms are virtually unheard of; exercise facilities; crafting/maker spaces; etc.

Those things definitely go into tuition, fees, and residence costs, which is why (I think) it's important to separate the actual cost of instruction. One might imagine, as powerpoint and smart boards have replaced overheads and chalk, that instructional costs would inflate to accommodate all the new technology, but that doesn't seem to be so. At least in the few places I could find instruction itemized. Faculty salaries (broadly) have just kept pace with inflation.

Growing enrollment has really allowed state governments to mask their slow but steady per capita defunding of higher education.

The state component is really important. The schools I've been able to find the data, the actual cost of instruction per student has risen very close to inflation since the 1980s. States have all increased their education budgets every year, because you can't decrease education spending, but not nearly as fast as inflation and increasing enrollment. Schools have to raise tuition to make up the difference.

Somewhere along the way, the political view of college changed from 'a well educated and highly skilled population benefits the whole state' to 'college education is a personal privilege.'

Stuff breaks. Given enough time, absolutely everything breaks, and delicate microprocessors break fairly quickly. The atoms may all still be there, but you need to be able to reconstruct the original molecular and physical structure, and that's often not possible, even on earth.

That's definitely differential absorption by grain. You can see a couple of staves with glossy/matte stripes, and I'm sure those are either xylem/phloem or different years. It may be impossible to 'fill up' those areas, because the oil can literally flow through to the other side of the top.

In my experience, oil finish on butcher block is not usually glossy. That is, I would interpret the glossy areas as places where you have not wiped enough of the oil off. But I've always used mineral oil (food-safe, non-curing) for that kind of countertop. If you're using a curing oil, or an oil-varnish, then gloss might be ok.

Most of the arguments I've seen for UBI replace ALL means-tested programs - Medicaid, EITC, Child tax credit, SNAP, etc - which come to around $800B. Some also propose it to replace non-means-tested programs - Social Security, Medicare - which add another $2,000B. $16,000 UBI for 250M adult Americans costs $4,000B/year, so it's kind of in the right ballpark, if you include SS/Medicare.

But this ignores that replacing current retiree benefits of ~$19,000 Social security plus $11,000 Medicare with just $16,000 UBI will be a huge burden on a very vulnerable population.

Try an incognito window.

They do have, about halfway down, maps adjusted for age distribution that I found pretty surprising. A big stripe up the east coast of Africa, through the Middle East, India, and Russia.

Certainly helps explain why there are so many +50% counties right next to -20% counties.

Eh. They chilled everyone until they started shivering, then warmed them until they stopped. Temps are going to depend on individual body shape, fat distribution, and who knows what else. I can see an argument where the average wouldn't be particularly informative, and might be easily misinterpreted as a special bathing temperature that triggers TG release. It'd be nice to know; it'd be nice to have core temperature records; but there's always improvements to offer after the fact.

"Not high quality" is undeserved.

This study was designed to maximize non-shivering thermogenesis, and any muscular activity is going to be a source of heat that reduces the drive for non-shivering thermogenesis. i.e.: you need to feel uncomfortably cold.

They couldn't/didn't bother to tell us what temperature they used, but their subjects were all lying in chilled water baths, adjusted to just above uncontrollable shivering. That probably means a core body temperature around 35 oC.

An AI identifying molecules with features similar to other known antibiotics is exactly what statistical models are good for. But it's a first pass before actually testing whether those molecules actually work. There are a lot of false positives, but that's OK, because they still greatly narrow the field to be tested.

An AI language model is also going to generate a lot of false positives - gibberish - that you can only tell by testing it. i.e.: by having someone knowledgeable in the field read it and possibly fact check it. That kind of defeats the point of a lot of AI writing applications.

Sounds more like a turbo encabulator generator than a science generator.

Do you have to clean bird remains from your window sills on the regular? Flying into windows kills about 2500x more birds every year than windmills.

https://www.statista.com/chart/15195/wind-turbines-are-not-killing-fields-for-birds/

Exactly. I've cancelled like six services in the last year. Some of them twice.