They're not saving money. They're retasking office workers who make $100+ per hour to do work they usually pay a lot less for.

OTOH, if it keeps customers from having bad experiences because the system is overwhelmed, it may be a good use of those expensive workers.

Nah. These are salaried workers being asked to do something during their normal work hours. It's basically not possible to avoid paying them.

Weekdays 10 am to 6 pm. That's normal work hours. Unless they're being forced to use vacation time, they're being paid.

More likely 100-200/hour, more if they're software engineers or similar highly-paid office workers. $30/hour is only $60k/year. There's no way Amazon white-collar workers in NYC are making that little.

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?

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.

This just raises the question of what it means to "know". The LLMs clearly have a large and fairly comprehensive model of the world, the things in it and the relationships between them. If they didn't, they couldn't produce output that makes sense in the context of the models we have of the world, the things in it and the relationships between them.

someone needs to step up and act like an adult!

2035 ??? are they for real?
Without major intervention now, by 2035 we're likely to breach ~1.6–1.8C warming, with escalating extreme weather, melting ice, and climate tipping risks.

To stay on a 1.5C trajectory, global emissions need to drop by ~57% by 2035—but current policies are headed in the opposite direction .

Yet the truth is that were already at ~1.6 C
The truth is we are already seeing mass displacement of people and multiple breadbasket failures just as was forecast in 2019 or earlier - yet .. still more time and energy wasted on studies and conferences that lead nowhere and only tell us what we already know .... Were basing government policy now on lies , propaganda and greenwash.....

Arctic sea ice is forecast to see glacierfree Septembers at least once by ~2035
Permafrost thaw, wildfire intensification (e.g., Canada’s record fires), and disruption of ocean currents are increasing faster than projections predicted .
climate “tipping points” (e.g., Greenland ice sheet melt, coral dieoff) may be reached between 1.5–2C, now increasingly likely before midcentury .

2035 my arse

That has nothing to do with the comment you replied to. I was talking about Trump's cluelessness what is needed to retain the dollar's status as the world's reserve currency which is at best weakly related to its valuation relative to other currencies.

Only if hedge fund managers don't understand how the Fed chairmanship works. Trump can't replace Powell until February 2026, when Powell's term expires. Not unless Trump can make the case that he needs to be removed for cause, which would require evidence of misconduct, not just policy disagreement.

Once again more evidence to suggest were in the final few years of this civilisation. Everything is going according to plan.

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.

Well, your buying power would be crippled.