From my perspective as a journal editor and a reviewer these kinds of tools cause many more problems than they actually solve. They make the 'barrier to entry' for submitting vibed semi-plausible journal articles much lower, which I understand some may see as a benefit. The drawback is that scientific editors and reviewers provide those services for free, as a community benefit. One example was a submission their undergraduate affiliation (in accounting) to submit a paper on cosmology, entirely vibe-coded and vibe-written. This just wastes our (already stretched) time. A significant fraction of submissions are now vibe-written and come from folks who are looking to 'boost' their CV (even having a 'submitted' publication is seen as a benefit), which is really not the point of these journals at all.

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.

Anybody else notice that half the video was just finding papers to decorate the bibliography with? Not like "find me more papers I should read and consider", but "find papers that are relevant that I should cite--okay, just add those".

This is all pageantry.

I remember, something like a month ago, Altman twit'n that they were stopping all product work to focus on training. Was that written on water?

Seems like they have only announced products since and no new model trained from scratch. Are they still having pre-training issues?

Previously, this existed as crixet.com [0]. At some point it used WASM for client-side compilation, and later transitioned to server-side rendering [1][2]. It now appears that there will be no option to disable AI [3]. I hope the core features remain available and won’t be artificially restricted. Compared to Overleaf, there were fewer service limitations: it was possible to compile more complex documents, share projects more freely, and even do so without registration.

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.

[0] https://crixet.com

[1] https://www.reddit.com/r/Crixet/comments/1ptj9k9/comment/nvh...

[2] https://news.ycombinator.com/item?id=42009254

[3] https://news.ycombinator.com/item?id=46394937

This seems like a very basic overleaf alternative with few of its features, plus a shallow ChatGPT wrapper. Certainly can’t compete with using VS Code or TeXstudio locally, collaborating through GitHub, and getting AI assistance from Claude Code or Codex.

I’ve been “testing” LLM willingness to explore novel ideas/hypotheses for a few random topics[0].

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.

Not an academic, but I used LaTeX for years and it doesn’t feel like what future of publishing should use. It’s finicky and takes so much markup to do simple things. A lab manager once told me about a study that people who used MS Word to typeset were more productive, and I can see that…

With a tool like this, you could imagine an end-to-end service for restoring and modernizing old scientific books and papers: digitization, cleanup, LaTeX reformatting, collaborative or volunteer-driven workflows, OCR (like Mathpix), and side-by-side comparison with the original. That would be useful.

This does way less than i'd expect. Converting images to tikz is nice but some of the other applications demonstrated were horrible. This is no way anyone should be using AI to cite.

Very unfortunately named. OpenAI probably (and likely correctly) estimated that 13 years is enough time after the Snowden leaks to use "prism" for a product but, for me, the word is permanently tainted.

I postulate 90% of the reason openai now has "variants" for different use cases is just to capture training data...

That's is probably one good usage of LLMs. LaTeX was a relief to deal with after using LLM. I have been using LaTeX for years before but it was not any easy. Aside of making LLM write the text, it is very good grammar and typo checker.

Even on overleaf and browser default spell checker, my Thesis feedback contained a few typos from my Advisor each time I sent him for review.

BTW: Overleaf added LLM integration which help solving LaTeX errors but you pay for it separately. But I feel like overleaf with their good docs on LaTeX something positive for science and hope they manage to adapt with this nee competition.

The quality and usefulness of it aside, the primary question is: are they still collecting chats for training data? If so, it limits how comfortable, and sometimes even permitted, people would with working on their yet-to-be-public work using this tool.

What's the goal here?

There was an idea of OpenAI charging commission or royalties on new discoveries.

What kind of researcher wants to potentially lose, or get caught up in legal issues because of a free ChatGPT wrapper, or am I missing something?

Check out MonsterWriter if you are concerned about the recent acquisition of this.

It also offers LaTeX workspaces

see video: https://www.youtube.com/watch?v=feWZByHoViw

It's interesting how quickly the quest for the "Everything AI" has shifted. It's much more efficient to build use-case specific LLMs that can solve a limited set of problems much more deeply than one that tries to do everything well.

I've noticed this already with Claude. Claude is so good at code and technical questions... but frankly it's unimpressive at nearly anything else I have asked it to do. Anthropic would probably be better off putting all of their eggs in that one basket that they are good at.

All the more reason that the quest for AGI is a pipe dream. The future is going to be very divergent AI/LLM applications - each marketed and developed around a specific target audience, and priced respectively according to value.

Very underwhelming.

Was this not already possible in the web ui or through a vscode-like editor?

in the end we're going to end up with papers written by AI, proofread by AI .....summarized for readers by AI. I think this is just for them to remain relevant and be seen as still pushing something out

All your papers are belong to us

"Accelerating science writing and collaboration with AI"

Uhm ... no.

I think we need to put an end to AI as it is currently used (not all of it but most of it).

> Introducing Prism Accelerating science writing and collaboration with AI.

I thought this was introduced by the NSA some time ago.