I just think it's silly to obsess over words like that. There are many words that take on different meanings in different contexts and can be associated with different events, ideas, products, time periods, etc. Would you feel better if they named it "Polyhedron"?
You may say it's "silly to obsess", but it's like naming a product "Auschwitz" and saying "it's just a city name" -- it ignores the power of what Geffrey N. Leech called "associative meaning" in his taxonomy of "Seven Types of Meaning" (Semantics, 2nd. ed. 1989): speaking that city's name evokes images of piles of corpses of gassed undernourished human beings, walls of gas chambers with fingernail scratches and lamp shades made of human skin.
[2] https://prism-pipeline.com/
[6] https://www.graphpad.com/features
[7] https://www.prismsoftware.com/
I am not sure you can make an argument of "other people are doing it too". Lots of people do things that it is not in their interest (ex: smoking, to pick the easy one).
As others mentioned, I did not have the negative connotation related to the word prism either, but not sure how could one check that anyhow. It is not like I was not surprised these years about what some other people think, so who knows... Maybe someone with experience in marketing could explain how it is done.
If they claim in a private meeting with people at the NSA that they did it as a tribute to them and a bid for partnership, who would anyone here be to say they didnt? even if they didnt... which is only relevant because OpenAI processes an absolute shitton of data the NSA would be interested in
https://en.wikipedia.org/wiki/Prism_(optics)
I remember the NSA Prism program, but hearing prism today I would think first of Newton, optics, and rainbows.
Most ordinary users won’t recognize the smaller products you listed, but they will recognize OpenAI and they’ll recognize Snowden/NSA adjacent references because those have seeped into mainstream culture. And even if the average user doesn’t immediately make the connection, someone in their orbit on social media almost certainly will and they’ll happily spin it into a theory for engagement.
(I expect a much higher than average share of people in academia also part of these spaces.)
Most people don't even remember Snowden at this point.
They're of course free to choose this name. I'm just also surprised they would do so.
Large scale technology projects that people are suspicious and anxious about. There are a lot of people anxious that AI will be used for mass surveillance by governments. So you pick a name of another project that was used for mass surveillance by government.
Altso, nazism. But different context, years ago, so whatever I guess?
Hell, let's just call it Hitler. Different context!
Given what they do it is an insidious name. Words matter.
Coming from a company involved with sharing data to intelligence services (it's the law you can't escape it) this is not wise at all. Unless nobody in OpenAI heard of it.
It was one of the biggest scandal in tech 10 years ago.
They could call it "Workspace". More clear, more useful, no need to use a code-word, that would have been fine for internal use.
The extreme examples are an analogy that highlight the shape of the comparison with a more generally loathed / less niche example.
OpenAI is a thing with lots and lots of personal data that the consumers trust OpenAI not to abuse or lose. They chose a product name that matches a us government program that secretly and illegal breached exactly that kind of trust.
Hitler vegetarians isn't a great analogy because vegetarianism isn't related to what made hitler bad. Something closer might be Exxon or BP making a hairgel called "Oilspill" or Dupont making a nail polish called "Forever Chem".
They could have chosen anything but they chose one specifically matching a recent data stealing and abuse scandal.
Have you ever seen the comment section of a Snowden thread here? A lot of users here call for Snowden to be jailed, call him a russian asset, play down the reports etc. These are either NSA sock puppet accounts or they won't bite the hand that feeds them (employees of companies willing to breach their users trust).
Edit: see my comment here in a snowden thread: https://news.ycombinator.com/item?id=46237098
Someone once said "Religion is opium for the people." - today, give people a mobile device and some doom-scrolling social media celebrity nonsense app, and they wouldn't noticed if their own children didn't come home from school.
For me the problem was not surveillance, the problem is addiction focused app building (+ the monopoly), and that never seem to be a secret. Only now there are some attempts to do something (like Australia and France banning children - which am not sure is feasible or efficient but at least is more than zero).
Protesting is a poor proxy for American political engagement.
Child neglect and missing children rates are lower than they were 50 years ago.
And they did manage to get the word out. They are both relatively free now, but it is true, they both paid a price.
Idealism is that you follow your principles despite that price, not escaping/evading the consequences.
(And he is also the reason why Snowden ended up in Russia. Though it's possible that the flight plan they had was still the best one in that situation.)
I am increasingly wondering what there remains of the supposed superiority of the Western system if we're willing to compromise on everything to suit our political ends.
The point was supposed to be that the truth is worth having out there for the purpose of having an informed public, no matter how it was (potentially) obtained.
In the end, we may end up with everything we fear about China but worse infrastructure and still somehow think we're better.
What if he simply decided that the information he obtained is worth having out there no matter the source? It seems to me that you're simply upset that he dared to do so and are trying very hard to come up with a rationalization for why he's a Bad Guy(tm) for daring to turn the tables. It's a transparent and rather lackluster attempt to shift the conversation from what to who.
It was Russia, or vanish into a black site, never to be seen or heard from again.
https://en.wikipedia.org/wiki/Lie#:~:text=citation%20needed%...
Even if what you say is completely untrue (and who really knows for sure).... it creates that mental association. It's a horrible product name.
[1]: https://openai.com/index/openai-appoints-retired-us-army-gen...
Yes, imho, there is a great deal of ignorance of the actual contents of the NSA leaks.
The agitprop against Snowden as a "Russian agent" has successfully occluded the actual scandal, which is that the NSA has built a totalitarian-authoritarian apparatus that is still in wide use.
Autocrats' general hubris about their own superiority has been weaponized against them. Instead of actually addressing the issue with America's repressive military industrial complex, they kill the messenger.
There's a good chance they just asked GPT5.2 for a name. I know for a fact that when some of the OpenAI models get stuck in the "weird" state associated with LLM psychosis, three of the things they really like talking about are spirals, fractals, and prisms. Presumably, there's some general bias toward those concepts in the weights.
(full disclosure, yes they will be handin in PII on demands like the same kinda deals, this is 'normal' - 2012 shows us no one gives a shit)
We haven’t forgotten… it’s mostly that we’re all jaded given the fact that there has been zero ramifications and so what’s the use of complaining - you’re better off pushing shit up a hill
It's a horrible name for any product coming out of a company like OpenAI. People are super sensitive to privacy and government snooping and OpenAI is a ripe target for that sort of thinking. It's a pretty bad association. You do not want your AI company to be in any way associated with government surveillance programs no matter how old they are.
I personally associate Prism with [Silverlight - Composite Web Apps With Prism](https://learn.microsoft.com/en-us/archive/msdn-magazine/2009...) due to personal reasons I don't want to talk about ;))
If it was part of their adtech systems and them dipping their toe into the enshittification pool, it would have been a legendarily tone deaf project name, but as it is, I think it's fine.
On the other hand, Overleaf appears to be open source and at least partially self-hostable, so it’s possible some of these ideas or features will be adopted there over time. Alternatively, someone might eventually manage to move a more complete LaTeX toolchain into WASM.
[1] https://www.reddit.com/r/Crixet/comments/1ptj9k9/comment/nvh...
I do self-host Overleaf which is annoying but ultimately doable if you don't want to pay the $21/mo (!).
I do have to wonder for how long it will be free or even supported, though. On the one hand, remote LaTeX compiling gets expensive at scale. On the other hand, it's only a fraction of a drop in the bucket compared to OpenAI's total compute needs. But I'm hesitant to use it because I'm not convinced it'll still be around in a couple of years.
a lot of academics aren't super technical and don't want to deal with git workflows or syncing local environments. they just want to write their fuckin' paper (WTFP).
overleaf lets the whole research team work together without anyone needing to learn version control or debug their local texlive installation.
also nice for quick edits from any machine without setting anything up. the "just install it locally" advice assumes everyones comfortable with that, but plenty of researchers treat computers as appliances lol.
The visual editor in Overleaf isn't true WYSIWIG, but it's close enough. It feels like working in a word processor, not in a code editor. And the interface overall feels simple and modern.
(And that's just for solo usage -- it's really the collaborative stuff that turns into a game-changer.)
Overleaf ensures that everyone looks at the same version of the document and processes the document with the same set of packages and options.
Then: The LaTeX distribution is always up-to-date; you can run it on limited resources; it has an endless supply of conference and journal templates (so you don't have to scavenge them yourself off a random conference/publisher website); Git backend means a) you can work offline and b) version control comes in for free. These just off the top of my head.
You can even export ZIP files if you like (for any cloud service, it's not a bad idea to clone your repo once in a while to avoid begin stuck in case of unlikely downtime).
I have both a hosted instance (thanks to Overleaf/ShareLaTeX Ltd.) and I'm also paying user for the pro group license (>500€/year) for my research team. It's great - esp. for smaller research teams - to have the maintenance outsourced to a commercial provider.
On a good day, I'd spend 40% in Overleaf, 10% in Sublime/Emacs, 20% in Email and 10% in Google Scholar/Semantics Scholar and 10% in EasyChair/OpenReview, the rest in meetings.
Any plans of having typst integrated anytime soon?
To end up with yet another shitty (because running inside a browser, in particular its interface) web app ?
Why not focus efforts into making a proper program (you know, with IBM menu bars and keyboard shortcuts), but with collaborative tools too ?
I have occasionally lost a paragraph just by accidental marking a few lines and pressing [Backspace].
But at the moment, there is no better option than Overleaf, and while I encourage you to write what you propose if you can, Overleaf will be the bar that any such system needs to be compared against.
[0]: https://typst.app
They’re quite open about Prism being built on top of Crixet.
Also yes, LaTeX being source code it's much easier to get an AI to genere LaTeX than integrate into MS Word.
I don't think any particular word alone can be used as an indicator for LLM use, although certain formatting cues are good signals (dashes, smileys, response structure).
We were offended, but kept quiet to get the article accepted, and we changed some instances of some words to appease them (which thankfully worked). But the wrong accusation left a bit of a bad aftertaste...
...no?
Just one Google search for "latex editor" showed more than 2 in the first page.
It's not that different from using a markdown editor.
Maybe we'll need to go back to some sort of proof-of-work system, i.e. only accepting physical mailed copies of manuscripts, possibly hand-written...
I actually think Prism promotes a much more responsible approach to AI writing than "copying from chatgpt" or the likes.
Exactly, and I think this is good news. Let's break it so we can fix at last. Nothing will happen until a real crisis emerges.
And you think the indians will not hand write the output of LLMs ?
Not that I have a better suggestion myself..
Mini paper: that future isn’t the AI replacing humans. its about humans drowning in cheap artifacts. New unit of measurement proposed: verification debt. Also introduces: Recursive Garbage → model collapse
a little joke on Prism)
This appears to just be the output of LLMs itself? It credits GPT-5.2 and Gemini 3 exclusively as authors, has a public domain license (appropriate for AI output) and is only several paragraphs in length.
I feel like this means that working in any group where individuals compete against each other results in an AI vs AI content generation competition, where the human is stuck verifying/reviewing.
Not a dig on your (very sensible) comment, but now I always do a double take when I see anyone effusively approving of someone else's ideas. AI turned me into a cynical bastard :(
Also, in a world where AI output is abundant, we humans become the scarce resource the "tools" in the system that provide some connectivity to reality (grounding) for LLM
"Human Verification as a Service": finally, a lucrative career where the job description is literally "read garbage all day and decide if it's authentic garbage or synthetic garbage." LinkedIn influencers will pivot to calling themselves "Organic Intelligence Validators" and charge $500/hr to squint at emails and go "yeah, a human definitely wrote this passive-aggressive Slack message."
The irony writes itself: we built machines to free us from tedious work, and now our job is being the tedious work for the machines. Full circle. Poetic even. Future historians (assuming they're still human and not just Claude with a monocle) will mark this as the moment we achieved peak civilization: where the most valuable human skill became "can confidently say whether another human was involved."
Bullish on verification miners. Bearish on whatever remains of our collective attention span.
I'm not sure I'm convinced of the benefit of lowering the barrier to entry to scientific publishing. The hard part always has been, and always will be, understanding the research context (what's been published before) and producing novel and interesting work (the underlying research). Connecting this together in a paper is indeed a challenge, and a skill that must be developed, but is really a minimal part of the process.
I'm not sure what the final state would be here but it seems we are going to find it increasingly difficult to find any real factual information on the internet going forward. Particularly as AI starts ingesting it's own generated fake content.
> The amount of energy needed to refute bullshit is an order of magnitude bigger than that needed to produce it.
Not actually contradictory. Verification is cheap when there's a spec to check against. 'Valid Sudoku?' is mechanical. But 'good paper?' has no spec. That's judgment, not verification.
... for NP-hard problems.
It says nothing about the difficulty of finding or checking solutions of polynomial ("P") or exponential ("EXPTIME") problems.
I don't doubt the AI companies will soon announce products that will claim to solve this very problem, generating turnkey submission reviews. Double-dipping is very profitable.
It appears LLM-parasitism isn't close to being done, and keeps finding new commons to spoil.
I've seen this complaint a lot of places, but the solution to me seems obvious. Massive PRs should be rejected. This was true before AI was a thing.
HN Search: curl AI slop - https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
If I submitted this, I'd have to punch myself in the face repeatedly.
I can get behind this. This assumes a tool will need to be made to help determine the 1% that isn't slop. At which point I assume we will have reinvented web search once more.
Has anyone looked at reviving PageRank?
I have heard from people here that Kagi can help remove slop from searches so I guess yeah.
Although I guess I am DDG user and I love using DDG as well because its free as well but I can see how for some price can be a non issue and they might like kagi more.
So Kagi / DDG (Duckduckgo) yeah.
DDG used to be meta-search on top of Yahoo, which doesn't exist anymore. What do Gabriel and co-workers use now?
DDG is Bing.
Very rarely is there anything about WHAT these agents are producing and why it's important and valuable.
Now that the code is cheaper (not free quite yet) skills further up the abstraction chain become more valuable.
Programming and design skills are less valuable. However, you still have to know what to build: product and UX skills are more valuable. You still have to know how to build it: software architect skills are more valuable.
No one, at all levels, wants to do notes.
You could argue that not writing down everything provides a greater signal-noise ratio. Fair enough, but if something seemingly inconsequential is not noted and something is missed, that could worsen medical care.
I'm not sure how this affects malpractice claims - It's now easier to prove (with notes) that the doc "knew" about some detail that would otherwise not have been note down.
So I was not amused about this announcement at all, however easy it may make my own life as an author (I'm pretty happy to do my own literature search, thank you very much).
Also remember, we have no guarantee that these tools will still exist tomorrow, all these AI companies are constantly pivoting and throwing a lot of things at the wall to see what sticks.
OpenAI chose not to build a serious product, as there is no integration with the ACM DL, the IEEE DL, SpringerNatureLink, the ACL Anthology, Wiley, Cambridge/Oxford/Harvard University Press etc. - only papers that are not peer reviewed (arXiv.org) are available/have been integrated. Expect a flood of BS your way.
When my student submit a piece of writing, I can ask them to orally defend their opus maximum (more and more often, ChatGPT's...); I can't do the same with anonymous authors.
Maybe you get reimbursed for half as long as there are no obvious hallucinations.
In other words, such a structure would not dissuade bad actors with large financial incentives to push something through a process that grants validity to a hypothesis. A fine isn't going to stop tobacco companies from spamming submissions that say smoking doesn't cause lung cancer or social media companies from spamming submissions that their products aren't detrimental to the mental health.
That's not the right threat model. The existing peer review process is already weak to high-effort but conflicted research.
Instead, the threat model is closer one closer to that of spam, where the submitting authors don't care about the content of their submission at all but need X publications in high-impact outlets for their CV or grant application. Predatory journals exploit this as part of a pay-to-play problem, but the low reputation of those journals limits their desirable impact factor.
This threat model relies on frequent but low-quality submissions, and a submission fee would make taking multiple kicks at the can unviable.
Plus, the t in me from submission to acceptance/rejection can be long. For cutting edge science, you can't really afford to wait to hear back before applying to another journal.
All this to say that spamming 1,000 journals with a submission is bad, but submitting to the journals in your field that are at least decent fits for your paper is good practice.
Suppose you are an independent researcher writing a paper. Before submitting it for review to journals, you could hire a published author in that field to review it for you (independently of the journal), and tell you whether it is submission-worthy, and help you improve it to the point it was. If they wanted, they could be listed as coauthor, and if they don't want that, at least you'd acknowledge their assistance in the paper.
Because I think there are two types of people who might write AI slop papers: (1) people who just don't care and want to throw everything at the wall and see what sticks; (2) people who genuinely desire to seriously contribute to the field, but don't know what they are doing. Hiring an advisor could help the second group of people.
Of course, I don't know how willing people would be to be hired to do this. Someone who was senior in the field might be too busy, might cost too much, or might worry about damage to their own reputation. But there are so many unemployed and underemployed academics out there...
While well-intentioned, I think this is just gate-keeping. There are mountains of research that result in nothing interesting whatsoever (aside from learning about what doesn't work). And all of that is still valuable knowledge!
Maybe something like a "hierarchy/DAG? of trusted-peers", where groups like universities certify the relevance and correctness of papers by attaching their name and a global reputation score to it. When it's found that the paper is "undesirable" and doesn't pass a subsequent review, their reputation score deteriorates (with the penalty propagating along the whole review chain), in such a way that:
- the overall review model is distributed, hence scalable (everybody may play the certification game and build a reputation score while doing so) - trusted/established institutions have an incentive to keep their global reputation score high and either put a very high level of scrutiny to the review, or delegate to very reputable peers - "bad actors" are immediately punished and universally recognized as such - "bad groups" (such as departments consistently spamming with low quality research) become clearly identified as such within the greater organisation (the university), which can encourage a mindset of quality above quantity - "good actors within a bad group" are not penalised either because they could circumvent their "bad group" on the global review market by having reputable institutions (or intermediaries) certify their good work
There are loopholes to consider, like a black market of reputation trading (I'll pay you generously to sacrifice a bit of your reputation to get this bad science published), but even that cannot pay off long-term in an open system where all transactions are visible.
Incidentally, I think this may be a rare case where a blockchain makes some sense?
But it should also fair. I once caught a team at a small Indian branch of a very large three letter US corporation violating the "no double submission" rule of two conferences: they submitted the same paper to two conferences, both naturally landed in my reviewer inbox, for a topic I am one of the experts in.
But all the other employees should not be penalized by the violations of 3 researchers.
Anyway, how will universities check the papers? Somone must read the preprints, like the current reviewers. Someone must check the incoming preprints, find reviewers and make the final decition, like the current editors. ...
(no snark)
For developers, academics, editors, etc... in any review driven system the scarcity is around good human judgement not text volume. Ai doesn't remove that constraint and arguably puts more of a spotlight on the ability to separate the shit from the quality.
Unless review itself becomes cheaper or better, this just shifts work further downstream and disguising the change as "efficiency"
In education, understanding is often best demonstrated not by restating text, but by presenting the same data in another representation and establishing the right analogies and isomorphisms, as in Explorable Explanations. [1]
Or the providers of the models are capable of providing accepted/certified guarantees as to the quality of the output that their models and systems produce.
"which is really not the point of these journals at all"- it seems that it very much is one of the main points? Why do you think people publish in journals instead of just putting their work on the arxiv? Do you think postdocs and APs are suffering through depression and stressing out about their publications because they're agonizing over whether their research has genuinely contributed substantively to the academic literature? Are academic employers poring over the publishing record of their researchers and obsessing over how well they publish in top journals in an altruistic effort to ensure that the research of their employees has made the world a better place?
I also don't understand your second paragraph at all.
That is an interesting philosophical question, but not the question we are confronted with. A lot of LLM assisted materials have the _signals_ of novel research without having its _substance_.
To me, this is directly relevant to the issue of democratization of science. There seems to be a tool that is inconveniently resulting in the "wrong" people accelerating their output. That is essentially the complaint here rather than any criticism inherent to LLMs (e.g. water/resource usage, environmental impact, psychological/societal harm, etc.). The post I'm responding to could have been written if LLMs were replaced by any technology that resulted in less experienced or capable researchers disproportionately being able to submit to journals.
To be concrete, let's just take one of prism's capabilities- the ability to "turn whiteboard equations or diagrams directly into LaTeX". What a monstrous thing to give to the masses! Before, those uneducated cranks would send word docs to journals with poorly typeset equations, making it a trivial matter to filter them into the trash bin. Now, they can polish everything up and pass off their chicken scratch as respectable work. Ideally, we'd put up enough obstacles so that only those who should publish will publish.
My objection is not that they are the "wrong people". They are just regular people with excellent tools but not necessarily great scientific ideas.
Yes, it was easier to trash the crank's work before based on their unLaTeXed diagrams. Now, they might have a very professional looking diagram, but their work is still not great mathematics. Except that now the editor has a much harder time finding out who submitted a worthwhile paper
In what way do you think the feature of "LaTeXing a whiteboard diagram" is democritizing mathematics? I do not think there are many people who have exceptional mathematical insights but are not able to publish them because they are not able to typeset their work properly.
Being against this is essentially to be in favor of a form of discrimination by proxy- if you can't typeset, then likely you can't do research either. And wouldn't it be really annoying if those people who can't research could magically typeset. It's a fundamentally undemocratic impulse: Since those who cannot typeset well are unlikely to produce quality mathematics, we can (and should) use this as an effective barrier to entry. If you replace ability to typeset with a number of other traits, they would be rather controversial positions.
But LLMs are not really helping. With all the beautifully typeset papers with immaculate prose, Ramanujan's papers are going to be buried deeper!
To some extent, I agree with you that it is a "discrimination by proxy", especially with the typesetting example. But you could think of examples where cranks could very easily fool themselves into thinking that they understand the essence of the material without understanding the details. E.g, [I understand fluid dynamics very well. No, I don't need to work out the differential equations. AI can do the bean counting for me.]
https://scottaaronson.blog/?p=304
By far the easiest quality signal is now out of the window.
Plenty of researchers hate writing and will only do it at gunpoint. Or rather, delegate it all to their underlings.
I don't see an issue with generative writing in principle. The Devil is in the details, but I don't see this as much different from "hey grad student, write me this paper". And generative writing already exists as copy-paste, which makes up like 90% of any random paper given the incrementality of it all.
I was initially a little indignated by the "find me some plausible refs and stick them in the paper" section of the video but, then again, isn't this what most people already do? Just copy-paste the background refs from the colleague's last paper introduction and maybe add one from a talk they saw in the meantime, plus whatever the group & friends produced since then.
My experience is most likely skewed (as all are), but I haven't met a permanent researcher that wrote their own papers yet, and most grad students and postdocs hate writing. Literally the only times I saw someone motivated to write papers (in a masochistic way) were just before applying to a permanent position or while wrapping up their PhD.
Onto your point, though, I agree this is somewhat worrisome in that, by reaction, the barrier to entry might rise by way of discriminating based on credentials.
I also am not sure why so many people are vehemently against this. I would bet that at least 90% of researchers would agree that the writing up is definitely not the part of the work they prefer (to stay polite). As you mentioned, work is usually relegated to students, and those students already had access to LLMs if they wanted to generate the work.
In my opinion, most of those tools become problematic when people use them without caution. Unfortunately, even in sciences, people are not as careful and pragmatic as we would like to imagine they are and a lot of people are cutting corners, especially in those "lesser" areas like writing and presenting your work.
Overall, I think this has the potential to reshape the publication system, which is long overdue.
A good tool would encourage me, help me while I am writing, and maybe set up barriers that keep me from taking shortcuts (e.g. pushing me to re-read the relevant paragraphs of a paper that I cite).
Prism does none of these things - instead it pushes me towards sloppy practices, such as sprinkling citations between claims. Why won't ChatGPT tell me how to build a bomb but Prism will happily fabricate fake experimental results for me?
This is still a good step in a direction of AI assisted research, but as you said, for the moment it creates as many problems as it solves.
On the other hand, the world is now a different place as compared to when several prominent journals were founded (1869-1880 for Nature, Science, Elsevier). The tacit assumptions upon which they were founded might no longer hold in the future. The world is going to continue to change, and the publication process as it stands might need to adapt for it to be sustainable.
The whole process should be made more transparent and open from the start, rather than adding more gatekeeping. There ought to be openness and transparency throughout the entire research process, with auditing-ability automatically baked in, rather than just at the time of publication. One man’s opinion, anyway.
> > who are looking to 'boost' their CV
Ultimately, this seems like a key root cause - misaligned incentives across a multi-party ecosystem. And as always, incentives tend to be deeply embedded and highly resistant to change.
This is a space that probably needs substantial reform, much like grad school models in general (IMO).
the early years of LLMs (when they were good enough to correct grammar but not enough to generate entire slop papers) were an equalizer. we may end up here but it would be unfortunate.
why would it be upon them to submit in English, when instead reviewers and readers can themselves use a LLM translator to read the paper ?
For whom? For OpenAI these tools are definitely the solutions. They are developing by throwing various AI-powered stuff at the wall to see what sticks. These tools also demonstrate to the investors that innovation did not stall and to show that AI usage is growing.
Same with Microsoft: none of the AI stuff they are shoving down the users' throats were actually designed for the users. All this stuff is only for the token usage to grow for the shareholders to see.
Similar with Google although no one can deny real innovation happening there.
These acts just must have consequences so people stop doing them. You can use AI if you are doing it well but if you are wasting everyones time you should just be excluded from the discourse altogether.
https://hn.algolia.com/?dateRange=pastYear&page=0&prefix=tru...
https://hn.algolia.com/?dateRange=pastYear&page=0&prefix=tru...
It was already a problem 25 years ago when I did my Ph.D., and I don't think things changed that much since then.
This encourages researchers to publish barely valuable results, or to cut one articles into multiple ones with small variations to increase their number of publications. Also publishers creating more conferences and more journals to respond to the need that researchers have to publish.
I remember many experienced professors telling me cynically about this, about all the techniques they had to blow up one small finding into many articles.
Anyway - research slop started way before AI. It's probably going to make the problem worse, but the root issue have been there for a long time.
If I can't have that, the next best thing is a helper while I'm at the keyboard my damn self.
>Why LaTeX is the bottleneck: scientists spend hours aligning diagrams, formatting equations, and managing references—time that should go to actual science, not typesetting
This is supposed to be only a temporary situation until people recover from the cutbacks of the 1970's, and a more comprehensive number of scientists once again have their own secretary.
Looks like the engineers at Crixet were tired of waiting.
If you're not a Zotero user, I can't recommend it enough.
They probably wanted: "... that I should read?" So that this is at least marketed to be more than a fake-paper generation tool.
The target audience of this tool is not academics; it's OpenAI investors.
So yes, you use it to write the paper but soon it is public knowledge anyway.
I am not sure if there is much to learn from the draft of the authors.
I'd also like to share what I saw. Since GPT-4o became a thing, everyone who submits academic papers I know in my non-english speaking country (N > 5) has been writing papers in our native language and translating them with GPT-4o exclusively. It has been the norm for quite a while. If hallucination is such a serious problem it has been so for one and half a year.
[1]: https://statmodeling.stat.columbia.edu/2026/01/26/machine-le...
This could be considered in degrees.
Like when you only need a single table from another researcher's 25-page publication, you would cite it to be thorough but it wouldn't be so bad if you didn't even read very much of their other text. Perhaps not any at all.
Maybe one of the very helpful things is not just reading every reference in detail, but actually looking up every one in detail to begin with?
>slop papers will start to outcompete the real research papers.
This started to rear its ugly head when electric typewriters got more affordable.
Sometimes all it takes is faster horses and you're off to the races :\
"Grok" was a term used in my undergrad CS courses in the early 2010s. It's been a pretty common word in computing for a while now, though the current generation of young programmers and computer scientists seem not to know it as readily, so it may be falling out of fashion in those spaces.
> Groklaw was a website that covered legal news of interest to the free and open source software community. Started as a law blog on May 16, 2003, by paralegal Pamela Jones ("PJ"), it covered issues such as the SCO-Linux lawsuits, the EU antitrust case against Microsoft, and the standardization of Office Open XML.
> Its name derives from "grok", roughly meaning "to understand completely", which had previously entered geek slang.
I would note that Overleaf's main value is as a collaborative authoring tool and not a great latex experience, but science is ideally a collaborative effort.