The Devil: This is where you will spend eternity winding the clock
Me: Akshually I'll be winding the frequency standard; it requires additional mechanism to keep time
The Devil:
The Devil: You know that's why you're here, right?
Good point. An army that sees all others as subhuman and sees only the next death is one that has to keep fighting. It has no choice. It's the only thing it knows. It can keep conquering more territory outwards, or it can slaughter its own government inwards. History shows those are your two options.
Whether or not Russia conquers Ukraine, it will attack other countries - vast numbers of bored, underpaid soldiers would seek entertainment elsewhere if they didn't.
This is what I'm going by:
The report said that in December 2018, the US Federal Aviation Administration issued a special airworthiness information bulletin based on reports from operators of model 737 planes that the fuel control switches were installed with the locking feature disengaged.
The airworthiness concern was not considered an unsafe condition that would warrant an airworthiness directive – a legally enforceable regulation to correct unsafe conditions.
The same switch design is used in Boeing 787-8 aircraft, including Air India’s VT-ANB, which crashed. The report added: “As per the information from Air India, the suggested inspections were not carried out as the SAIB was advisory and not mandatory.”
Most of the world's oil technology was developed using coal power
Most of the world's coal technology was developed using wood power
Most of the world's wood technology was developed using driftwood and animal technology
and so on and so on. These gotcha-memes never really stand up to examination of any kind, much less close examination.
1. Were the safety guards, which were optional, installed?
2. We know investigators are looking into the computer system, does this mean the computer can also set the switch settings?
If the answers are "no" and "no" respectively, it was likely an accidental bump.
If the answers are "yes" and "no", then one of the pilots lied.
If the answer to the second one is yes, then regardless of the answer to the first, I'd hope the investigation thoroughly checks whether the software can be triggered into doing so through faulty data or the existence of software defects.
... remember to read the headlines of currently posted stories before starting work. It doesn't take long and forgetting to do it does not help repair the tarnished reputation of the Slashdot editorial crew.
Is this "during work hours, for the hours you're paid, instead of doing the job you normally do, do some warehouse work"?
Or is it "on top of all your regular work, come and volunteer to do additional unpaid work"?
If the former, then, whatever, this is no big deal.
If the latter, then, damn, Amazon needs to get the hell sued out of it. Not that that would happen in our current world.
What, in your argument, is the difference between LLM copy-edited text, and for-hire human copy-edited text. The editorial services I have seen *sometimes* try to find editors that are kinda-sorta near the correct field of expertise, but there's no guarantee you'll get someone who even has a passing level of familiarity with your field, and for some services, all they have is a degree in English.
So, again, what's the difference between linguistic polishing by machine and linguistic polishing by semi-qualified human?
Yeah, no one reads their product names before launch any more.
Following up on that idea, there are various copy-editing services that many non-native English speakers use, and are encouraged to use, to help improve their writing. The main difference from the perspective of forensic detection with AI-copy-edited text is that there are a very small number of such styles compared to the likely thousands of copy-editors' individual styles, making automated copy-editing easier to detect. I'll bet dollars to donuts that if you trained an LLM on the output of a single human copy-editor, you'd be able to identify all papers that used their services.
We use AI to help with paper writing in my lab, mostly because there are only two native English speakers, and it relieves me, the lab head (and one of the two native speakers), of having to do extensive copy-editing in order to make stilted English more readable. I still read every word that gets published from the lab, but using AI for copy-editing is no different from using a human-based writing service to fix poor language. It's just cheaper and orders of magnitude faster.
So, for us, the response would be a big, "so what?" to this report.
But, if people are starting to use AI to write entire papers, that's a different story. My experience is that current models hallucinate ideas and, especially, references, at far, far to high a rate to be seriously useful as anything other than a tool that requires full, manual verification. I half-jokingly say that if a paper is hallucinated, that means the AI was unable to find the right citation, and it represents a gap in the field's knowledge that we could address. The amazing thing about the hallucinations is how convincingly real they sound: the right authors, the right titles, the right journals. These are publications that *should* exist, but don't, at least in my experience.
As a most recent example, when writing a grant application, I tried to find citations using an LLM for an idea that is widely-held in the field. Everyone knows it to be true. It's obvious that it should be true. And, yet, there have been no publications as of yet that have actually discussed the idea, so the LLM dutifully hallucinated a citation with exactly the author list you would expect to have studied the question, a title that hits the nail on the head, and a journal exactly where you might expect the paper to appear. I've told my staff that we need to get that paper written and submitted, immediately, to fill that obvious gap, before someone else does. It will likely be cited widely.
Universities here are starting to tell CS and STEM students "you are on your own" when they get Macs. Because, as it turns out, a lot of stuff is more difficult on a Mac. For example, there are massive issues to get VMs runnign reliably for the students. Yes, I had one student with a Mac in my IT security class that just used GCC and GDB for the buffer overflow analysis on the Mac commandline and while the results were a bit different, they were fine and we discussed the differences. But 4 others did not manage. And that is a serious problem. Apple is doing way too much "different for the sake of being different" and that just does not cut it in quite a few scenarios.
I'm not a CS type, but I work in STEM, and having tried numerous times to bring obscure scientific stuff over from Unix or Linux and get it to build on MacOS, I absolutely agree with what you just said above. That sort of stuff is better left to experienced developers who focus on MacOS. I do use Linux, Windows and MacOS every workday, but I don't use Windows on weekends. I'd pick a Mac laptop 10 times out of 10 for general use, presuming I had access to networked Linux systems.
"Seven Fingers of Death."
It's almost certainly because you didn't do enough programming in college.
I agree entirely. I teach an intro to programming course at one of the well-known universities. It is a lab course with 2 hours of teaching contact time per week, 2 hours of reading time per week, and 8 hours of expected programming time per week. The students learn by doing.
Aw, c'mon. Basic is a horrible, horrible language that teaches poor habits and has almost no translation to serious programming.
If you want to have kids learn something easy that at least teaches good organization and thought processes, then teach them Scheme.
Parkinson's Law: Work expands to fill the time alloted it.
