Science is distributed. Lots of researchers at lots of different institutions research overlapping topics. That's part of its strength. In the U.S. most basic research is funded by federal grants. And as a results you'll find that research in pretty much any science area you can imagine is funded by federal grants going to multiple different institutions. In this case you're confusing things by bringing in NOAA which is a government agency (part of the Dept of Commerce). NCAR is a non-profit organization and competes for federal grant dollars with researchers at many other institutions (mostly universities). So in that sense there is a strong parallel here to Trump wanting to shut down Harvard (another non-profit organizations at which many different researchers work) and someone saying "doesn't Stanford do research on similar topics?" Yes, there is some conceptual overlap, but in detail there is not. The bigger difference is that Harvard has a big endowment and so can survive (at some level) if the federal grants it has been getting stop flowing. NCAR can't. Also, NCAR happens to have the experts and equipment (supercomputers) to do research that few other organizations can (none really in the U.S.). Harvard probably can't lay claim to that except in very narrow niches....
For perspective the annual budget for NCAR is about half the amount being spend on the new White House ballroom.
The multiple meanings of many of the words in this sentence make it really poor at communicating what the site is about. "Endeavour" (with a capital 'E') is a proper name I associate with a space shuttle, and 'stellar' can mean 'having to do with stars'. So a first read for me leads to the conclusion that this site has something to do with space flight. And 'system' could mean almost anything. Maybe this site will let me personalize my own star system? All I can take away is that I'm not sure what this is, but clearly I'm not the target audience. Which I'm fine with.....
Or more likely the 'whole' accesses the stable bit through some interface. The stable bit can happily keep doing it's job via the interface and the whole can change however it likes knowing that for that particular tasks (which hasn't changed) it can just call the interface.
Or it doesn't. Because "software as an organic thing" like all analogies is an analogy, not truth. Systems can sit there and run happily for a decade performing the needed function in exactly the way that is needed with no 'rot'. And then maybe the environment changes and you decide to replace it with something new because you decide the time is right. Doesn't always happen. Maybe not even the majority of the time. But in my experience running high-uptime systems over multiple decades it happens. Not having somebody outside forcing you to change because it suits their philosophy or profit strategy is preferrable.
If a hard drive sometimes fails, why would a raid with multiple hard drives be any more reliable?
"Do task x" and "Is this answer to task x correct?" are two very different prompts and aren't guaranteed to have the same failure modes. They might, but they might not.
At the very largest universities there is a really really wide variety of programs and courses. For example here's a course catalog where a search for 'intro' returns 3500 different courses.
https://classes.osu.edu/#/?q=intro&client=class-search-ui&ca...
You can see the variety, from "Introduction to the Army and Critical Thinking" to "Introductory Meat Science"
This breadth is typical of the very largest universities in the U.S.
Even in science there is not a 'requirement' that you have a controlled experiment in order to have evidence that a claim is true. Following your argument you can't substantiate that humans are the result of evolution because we can't take two groups of early primates, subject one to evolutionary forces and the other not and see what happens. Instead we can observe a chain of correlations with plausible mechanisms that indicate causation and say it's evidentiary. For example, data that indicates unvaccinated people died at a higher rate and data that indicates people who chose not to vaccinate self-report that the reason they made that choice was based on particular information that they believed. That would be evidence that helps substantiate the theory the information led to deaths. It's not 'proof'. We can't 'prove' that exposure to the information actually led to the decision (because people sometimes misattribute their own decisions) and it would be impractical to imagine we can collect vaccine-decision rationales from a large number of folks pre-death (though someone might have) and you can't attribute a particular death to a particular decision (because vaccines aren't perfectly protective) so you have to do statistics over a large sample. But the causal chain is entirely plausible based on everything I know and there's no reason to believe data around those correlations can't exist. And science isn't about 'proof'. Science is about theories that best explain a set of observations and in particular have predictive power. You almost never run experiments (in the 8th grade science fair sense) in fields like astronomy or geology, but we have strong 'substantiated' theories in those fields nonetheless.
The journal appears to be published by an office with 7 FTE's which presumably is funded by the money raised by presence of the paywall and sales of their journals and books. Fully-loaded costs for 7 folks is on the order of $750k/year.
https://www.kentstateuniversitypress.com/
Someone has to foot that bill. Open-access publishing implies the authors are paying the cost of publication and its popularity in STEM reflects an availability of money (especially grant funds) to cover those author page charges that is not mirrored in the social sciences and humanities.
Unrelatedly given recent changes in federal funding Johns Hopkins is probably feeling like it could use a little extra cash (losing $800 million in USAID funding, overhead rates potential dropping to existential crisis levels, etc...)
There are plenty of situations where someone visiting a page once and someone repeatedly looking at that page over a period of days (even if it is pulled from their browser cache) is an important difference. Obviously it depends on what you're using the data to try to understand.
Except if any of your pages are cached between eyeball and your server and so your server logs don't capture everything that is going on. You can get fancy with web server logs, but depending on what you're trying to understand it may not be the data you need.
<source: did fancy things with logs over the last 25 years, including running multiple tools on the same site in parallel to do comparisons (Analog, AWStats Urchin, GA, Omniture, homegrown, etc...)>
A simple reason would be if you're just using it as a proxy signal for bad bots and you want to reduce the load on your real servers and let them get rejected at the CDN level. Obvious SQL injection attempt = must be malicious bot = I don't want my servers wasting their time
Do they really use 90% less water cleaning the floors of women's restrooms than men's currently? Cause that's one implication of the 'new design will save cleaning' claim. Places with public restrooms that I'm familiar with seem to get their floors mopped with identical frequency (and similar apparent rigor) regardless of whether they have urinals or not.
Not if they hop to a different IP address every few requests. And they generally aren't bothered slow responses. It's not like they have to wait for one request to finish before they make another one (especially if they are making requests from thousands of machines).
The article says "...we can obtain a near real-time image of the server screen". Implying that what they have is an image file, not text. Getting keywords out of an image file would normally take an OCR step. A single API call to Claude does the trick without the extra tooling.
In my quick experiment (asking a question that would naturally lead to content on my own site) it is not doing a real time request to the site in question. Its answer included links back to my site (and relevant summaries), but there was no requests for those pages while it was generating its answer. So it's clearly drawing from info that has already been scraped at some earlier point. And given that I see Claudebot routinely (and politely) crawling the site I'd guess it's working from it's own scraped copies (because why use someone else's if you've got your own....)
7700/516 = just under 15 miles a day or around 100 miles per week. Typical mileage for any elite distance runner or even a decent D1 college runner (and low for an elite marathoner). But they often do it in one or two continuous sessions, often with significant intensity. The task of just covering the mileage in a day (without trying to do it in one go or trying do any of it fast) is nothing particularly exceptional. Heck as a slow 50-something dude I did 100 miles weeks during Covid when I had some free time. Health effects: assuming you were biomechanically inclined to do okay with lots of running and built up to it over a long enough time to avoid the usual overuse injuries it would almost certainly just make you healthier.
That's the 'vector search' people are talking about in this discussion. Use the LLM to generate an embedding vector that represents the 'meaning' of your query. Do the same for all the documents (or better with chunks of all the documents). Find the document vector that's closest to your query vector and you have a document that has a 'meaning' similar to your query. Obviously that's just a starting point. And lots of folks are doing hybrid where they combine bm25 search with some sort of vector search (e.g. run them in parallel and combine results, or do a bm25 and then use vector search to rerank the top results).
I'm no network guy so someone please explain why using 10.x.x.x. on a plane might "potentially cause routing issues"? It doesn't jive with what I understand about unrouteable address spaces. Is the 10.x.x.x space somehow different than the 192.168.x.x space that millions of people use VPN's out of every day (basically every WFH person on their cheap NAT'd home Wifi)?
There's a huge parallel to this mentioned in the next paragraph of the article. The 'research contract' is the foundational element of the National Science Foundation (which Bush brought into being) and is a core funding source for science in the U.S. ($9 billion last year).
Well, except the number of English speakers outside the US is much larger than inside the US (as per the wikipedia page you point to) by 5 to 1. Granted many folks are speaking it as their 2nd (or nth) language. But when you take into account the limited set of languages supported by ChatGPT one could reasonably assume English-speaking (typing) users of ChatGPT are from outside the U.S. as non-U.S. folks are in the majority of 'folks for whom english would be their first option when interacting with ChatGPT'. Even if you only count India, Nigeria and Pakistan.
Though of course OpenAI can tell (frequently, roughly) where folks are coming from geographically and could (does?) take that into account.
The color scale on this map distorts one's perception of where there are significant differences. There are sharp color boundaries at arbitrary points on a color scale and counter-intuitive gradations of color (while greens reflect the driest counties, the darkest green is actually the least dry of the greens). With a more continuous color scale this map would seem a lot less dramatic.