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.
Maybe you get reimbursed for half as long as there are no obvious hallucinations.
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!
> > 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.
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]
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.
https://hn.algolia.com/?dateRange=pastYear&page=0&prefix=tru...
https://hn.algolia.com/?dateRange=pastYear&page=0&prefix=tru...
This is a space that probably needs substantial reform, much like grad school models in general (IMO).
This is all pageantry.
"I know nothing but had an idea and did some work. I have no clue whether this question has been explored or settled one way or another. But here's my new paper claiming to be an incremental improvement on... whatever the previous state of understanding was. I wouldn't know, I haven't read up on it yet. Too many papers to write."
We removed the authorship of a a former co-author on a paper I'm on because his workflow was essentially this--with AI generated text--and a not-insignificant amount of straight-up plagiarism.
Didn't even open a single one of the papers to look at them! Just said that one is not relevant without even opening it.
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.
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.)
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 paper.
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 everyone's comfortable with that, but plenty of researchers treat computers as appliances lol.
Overleaf ensures that everyone looks at the same version of the document and processes the document with the same set of packages and options.
Any plans of having typst integrated anytime soon?
They’re quite open about Prism being built on top of Crixet.
You're right that something like Cursor can work if you're familiar with all the requisite tooling (git, installing cursor, installing latex workshop, knowing how it all works) that most researchers don't want to and really shouldn't have to figure out how to work for their specific workflows.
The earlier LLMs were interesting, in that their sycophantic nature eagerly agreed, often lacking criticality.
After reducing said sycophancy, I’ve found that certain LLMs are much more unwilling (especially the reasoning models) to move past the “known” science[1].
I’m curious to see how/if we can strike the right balance with an LLM focused on scientific exploration.
[0]Sediment lubrication due to organic material in specific subduction zones, potential algorithmic basis for colony collapse disorder, potential to evolve anthropomorphic kiwis, etc.
[1]Caveat, it’s very easy for me to tell when an LLM is “off-the-rails” on a topic I know a lot about, much less so, and much more dangerous, for these “tests” where I’m certainly no expert.
(See also: today’s WhatsApp whistleblower lawsuit.)
Perhaps, like the original PRISM programme, behind the door is a massive data harvesting operation.
I can't wait