>The system is what geologists call a fault-controlled non-volcanic geothermal feature.
These are quite common. Hot Springs National Park in Arkansas is a notable example. Most of the hot springs in Idaho are on fault lines, as are the hot springs along Highway 395 on the east side of the Sierras (though there is Quaternary volcanism in the region, it's not the source of heat), and through much of the rest of the Intermountain West.
This site seems to be unique for both the volume and the temperature of water, though. I'd be curious to know how far away the water originated, and how deep it goes before being heated. The crust in the area is not known to be particularly hot, as far as I know, unlike the Basin and Range of the western US where tectonic stretching and thinning of the crust has brought the hot mantle much closer to the surface and increased the geothermal gradient.
We're a century into it at least, even in nominal dollar terms, starting with Rockefeller as the first billionaire.
I don't know whether John Arnold is spread too thin or not, but he's certainly top caliber and does a lot to measure progress before/during investment in various causes (including education). He also seems to be more agnostic on what the most appropriate solution may be at the beginning of the process.
Maybe, just maybe, this is of obvious utility to the many people who have needs that are not yours?
I very regularly need to interact with my work through a python interpreter. My work is scientific programming. So the variables might be arrays with millions of elements. In order to debug, optimize, verify, or improve in any way my work, I cannot rely on any other methods than interacting with the code as it's being run, or while everything is still in memory. So if I want to really leverage LLMs, especially to allow them to work semi-autonomously, they must be able to do the same.
I'm not going to dump tens of GB of stuff to a log file or send it around via pipes or whatever. Why is there a nan in an array that is the product of many earlier steps in a code that took an hour to run? Why are certain data in a 200k-variable system of equations much harder to fit than others, and which equations are in tension with each other to prevent better convergence?
Are interpreters and pdb not great, previously-existing tools for this kind of work? Does a new tool that lets LLMs/agents use them actually represent some sort of hack job because better solutions have existed for years?
I use both gvim on linux and macvim on mac for a lot of things--not 'real' coding, typically, but opening and editing scripts and config files, writing in markdown, etc; I'm usually opening these from dolphin or finder. In the terminal, working on real code bases and not scripts, I use neovim. My configs for these have diverged a bit over the years but since the use cases are different, it doesn't bother me.
Thanks. I've got an OpenAI subscription and tried this in the past, and got a handful of results, but nothing comprehensive. Perhaps it is better now, or I could change the way I ask.
A few years later, the gravitational deflection of the Himalayas on a plumb line by Airy proved less than expected, which suggested that mountains have 'roots' that extend below them, displacing more dense rock--like icebergs more or less.
I used the gravitational force of the Longmenshan range to calculate the perturbations in the elastic stress field of the Earth's crust in Sichuan province, China, to estimate the tectonic forces in the region, which caused the 2008 Wenchuan earthquake: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/201...
There were no alphabets in the Americas before European contact. Mayan had written mathematics and hieroglyphics, and some Quechuan speaking peoples had string that had symbolic knots that had some mathematical representation (I don't know if it allowed arithmetic or was just record keeping).
Sequoia developed the Cherokee syllabary (where symbols represent syllables instead of vowels/consonants) in the 1800s after seeing white men reading, and figuring out what they were doing (he spoke little English and could not read it). This is the first real written indigenous language in the Americas.
The Skeena characters shown here are obviously derived from European characters, as was the Cherokee syllabary. I think most written forms of native languages in the Americas are similar.
The Cree have a script which is far from European characters but was nonetheless developed for the Cree by a missionary in the 1800s. The Inuit have modified it for their language.
I don't know much about indigenous languages in the rest of the world.
Rocks could be potential sources. Crystals that large are by no means rare, with feldspars being the most common on Earth and perhaps on most rocky planets (quartz is well known of course but I think would be rare without the magmatic fractionation that happens due to plate tectonics, which is perhaps unique to Earth in the solar system.)
Volcanic glass (eg obsidian) is also shiny and by no means rare in the solar system.
Many asteroids are also metallic, and perhaps metal crystals or fracture planes could produce reflectors of the right size.
Don't quote me on this but I think a lot of the change has to do with fire and flood suppression. Certainly on the Konza prairie and similar areas, small trees (post oaks and eastern red cedar) grew in natural fire breaks like bluffs, and individual trees would live for several hundred years. Floodplains would have large cottonwoods which can withstand seasonal inundation but wouldn't necessarily be thick forest otherwise. And the prodigious lightning storms and (throughout the Holocene) burning by native tribes for hunting kept trees off of the uplands.
Because it's for your kid's bed. At 3 AM the previous night, they peed the bed, so you got the other one out and put it on, throwing this one in the laundry room. Then, today you washed it but the one on the bed already is still in good shape.
Or, you have sheets of a few different colors, each paired to a comforter with a different weight that is changed seasonally, or biweekly, depending on the preferences of you and your bedmate.
This is evident in his description of programming in his later years:
Time and time again I would send my friend Dave Walker an email declaring that Javascript (or something else) was utterly broken, incapable of executing the simplest program without errors. Dave would ask to see the source code and I would present it to him with detailed notes proving that my code was perfect and Javascript was broken. He’d call me, we’d discuss it, and eventually he’d say something like, “Where did you terminate the loop beginning at line 563?” There would be a long silence, followed by the tiniest “Oh” from me. I’d thank him for his help and hang up. A week later, I’d be fuming again about another fundamental flaw in Javascript.
Many of us are stubborn and will work hard and long, without much positive external feedback, under the assumption that our vision is correct and the audience, if one even exists, is wrong. Much fundamental progress has been made this way: Faraday, Einstein, Jobs, etc. But of course many times one simply is wrong and refusing to see it means throwing years away, and whatever else with it (money, relationships, etc.). It's a hard balance, especially for the monomaniacal without much interest in balance. Finding out how to make solid (public, peer-reviewed, evidence-based, whatever) incremental progress towards the paradigm shift seems to be the way if one can manage.
Similar to the flood analysis others have mentioned, this can be used to create databases of buildings with the number of stories for each, which is important for understanding how each building will respond to various catastrophes (earthquakes, strong winds, etc.) in addition to various non-catastrophe administrative tasks. The other post about finding the depth of oil in oil tanks is actually super interesting to me because the amount of oil in the tank is a huge determinant of how it will respond to seismic ground motions. I had no idea the top sinks with the oil level and am skeptical that it does on all of the tanks but it's cool nonetheless.
Having read Eric Berger's Reentry about SpaceX and having a few friends who work at Tesla, my impression is that those organizations are not too dissimilar. They are also populated largely by millenial and gen Z people because older workers can't/won't deal with the hours and other working conditions.
Furthermore I think most blue collar American workers, and many white collar workers, are used to the concept of sudden and arbitrary termination.
The cuts aren't performance based. They're based on the ease of dismissal.
The voluntary resignations are what they are--I can't fault anyone for taking a good deal, and from what I have heard (married to someone in the government, with many friends as well) no one is being pressured inappropriately.
However, the other cuts are dominantly people who are 'probationary' which means that they are new to their positions, either by being recently hired or in some cases promoted. These people are, actually, on the whole harder workers than those who have been in their jobs for a long time, because they're still being competitive in order to move forward. The non-probationary employees have stronger civil service protections which means that they are harder to fire. This is the major discriminant used to decide who leaves and who goes.
rocksandwater.net