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#research#publish#papers#startups#more#companies#paper#publishing#openai#published
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Discussion (84 Comments)Read Original on HackerNews
I contacted a professor from a university in the UK and he responded since he was working on similar work, then asked me if I wanted to meet with him. We talked for about an hour since we had overlapping results and different methods, specifically different assumptions.
I say all that to say, as a physics student getting my undergrad, simply doing independent research and speaking to experts about it enabled me to network with someone I otherwise likely wouldn’t know. For young people getting into any business, research is a great way to meet new people.
The first tried to publish novel results for 3 years in tier 1 journals before finally doing a preprint and telling the tier one publishers to jump in a fire.
The second, and ongoing, isn't publishing anything because of my experience with the first.
That and avoiding openAI and Anthropic copying our results and leaving us with nothing to show for six months of work. The papers only come with the pitch deck.
Isn't the POINT of publishing research because you want others to copy it?
Moreso if your current employer is a stealth AI startup which hasn't yet produced much notable.
It also can encourage employees to work for fewer wages... 'If you do great work you can publish and then get a $$$$$$ job offer at OpenAI, or you can stay here and get equity in a fast growing startup. If however your work doesn't do well, you walk away from a bankrupt startup with worthless shares and minimum wage'
In the paper, OpenAI is at the top of the chart for cumulative citations. MEGVII, Hugging Face, Waymo, Momenta, Preferred Netowkrs, Anthropic, Owkin, and Databricks, and Aibee follow (in that order). Yes, that is citations, not publications, but they explain that they're trying to use that as a proxy for significance, albeit an imperfect one.
Companies like Google aren't included because they aren't unicorn startups.
what makes them a top ai startup
The AI usage has mostly been getting it to explain error messages
We already arrived at that destination a decade ago.
Probably even further back tbh.
There's just a lot more people playing the game now, without the social indoctrination that made it more tolerable in some circles.
It's not that bad, though. September is annoying but you kind of miss the eternal renewal once you're out.
Traditional research publications are no angels. They gatekeep research, and also allow financial incentives to drive them to publish junk with their stamp on it.
But a flood of papers doesn’t actually mean more knowledge. In bypassing this route entirely, AI has swiftly lost the ability to engage with itself as a field. And the cost of that is only beginning to be felt.
The main difference is reproducibility and peer review process.
On the first, I mostly don’t care.
On the second, that’s mostly unavoidable if they want to keep their IP.
https://research.google/pubs/distilling-the-knowledge-in-a-n...
# LLM generated summary of the implied irony
Google may consider the standalone frontier-model arms race economically irrational, while still considering frontier-model capability strategically indispensable. Its longer game is probably not to avoid building the biggest models, but to build only enough of them to serve as capability factories—then turn that intelligence into a much larger population of cheap, purpose-built models.
(Human again) If Google knew what they were on to, why wouldn’t they make it their secret weapon from the start? I suspect it’s because they predicted there would be an arms race, and knew how to profit from it. They had a distillation paper published before “Attention is all you need”. In hindsight, is it ironic at all? Or is it obvious?
It was kind of like radiation science before WWII, it would be freely published because it wasn't potentially world changing yet. After it became a government interest, even people doing things unrelated to weapons would be much more apt to hold their work close.
50% of startups contributing to public research is actually a crazy good outcome. That’s far more than I had expected.
Also, there are simply too many AI papers that make peer-review publishing quite meaningless these days (e.g., AAAI this year got more than 50K submissions).
There should be a new ESG (Environmental, Social, and Governance) policy being pushed recognizing the important role this plays. Although ESG and all norms have been set aside in this grim new world it seems.
You are not. A disproportionate amount of value in the computing industry was created by <strike>geniuses</strike> decently smart people who worked together and who decided to just tell people how to do things instead of trying to capture the value of being the first person to figure out how to do those things.
This observation pre-dates the current wave of AI hype by a half century or so.
> driven by greed
I can only speak for myself.
For me it's exactly the opposite. If I want to explain how something works, I can just... do that. If I want to share an artifact demonstrating how to solve a particular type of problem, I can just... do that. If I want to mentor/teach, I can just... do that.
Doing those things within the confines of Academia Approved Institutions is exhausting and distracting.
To wit, and the actual point of this post: the term "Publishing Research" in this article doesn't mean "post it on a .html page and share the source code". It means engaging in a very specific and peculiar and extremely political modality of communication.
And it really only makes sense to do that specific and peculiar and political thing you're at a stage in your professional/personal development where you need to play that particular prestige game. (Which there's nothing wrong with, but it is a deeply cargo culted version of the actual scientific process.)
* A disproportionate amount of value in the computing industry was created by g̶e̶n̶i̶u̶s̶e̶s̶ decently smart people who worked together to do things that seemed impossible and who decided to just tell people how to do things instead of trying to capture the value of being the first person to figure out how to do those things.*
edit: edited.
There is some excellent publicly-funded research in there, but pivotal papers like Attention Is All You Need and the numerous pivotal OpenAI publications were privately funded.
OpenAI is at the top of the chart in the study.
I think you're bringing some assumptions into this conversation that aren't supported by the evidence.
A distinction should be made between the old nonprofit OpenAI and the current organization. They don't publish technical research anymore.
Like I said, I think you're bringing some assumptions to this conversation that aren't based on the how the industry came about.
Example: https://arxiv.org/abs/2607.24653
Exceptions to some like Deepmind, Nvidia, and Thinking Machines
Fortunately
[1] https://arstechnica.com/ai/2025/06/anthropic-destroyed-milli...
The discussion has been around, but it's flared significantly recently. Not sure if that's what the person you're responding to is specifically inflamed about.
Regardless, old/rare books are certainly being acquired and destroyed.
The scanning process destroys the book.
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If everyone holds back their publications, the whole sector moves slower. Yes, it's moving alarmingly fast according to many, but is it moving fast enough that the massive investments in data centres will actually pay off?
It's more game theory. Things may go well for one selfish company not publishing in a sea of altruists who publish, but perhaps not if everyone else is selfish too.
Think Renaissance Technologies or similar.
Companies can’t be expected to publish their confidential and proprietary information about their feature development, and academics should consider projects that would have higher impact.
If you’re taking up a seat in a PhD program tinkering with would-be feature ideas for an existing major tech company, you should really just get hired by that tech company, where the resources are abundant and the degree is not required.
(Not saying that's how it should be, but that's how it has been.)
More to the point, without determining how much work is “worthy” of a paper it is unclear how much this matters.
Most AI companies are either a product and marketing layer over a model or not meaningfully moving any dimension to be worthy of a paper.
Also, formal papers and blogs and “cards” are all being intertwined.
Even at work, I have come to realize if I simply horde my accumulated custom AI built tools and productivity boosting tricks for myself, I can make myself more competitive as an employee.
I think this is how you get hired now, not by having a good resume, but by making claims of having special processes and personal tooling design that gets massive productivity ROI.
https://arxiv.org/search/?searchtype=author&query=Magarshak%...
So I know that smart people in those companies can definitely publish. In fact, a whole team should probably be publishing like no tomorrow!
To be fair — from about half of the papers.
We're not racing towards anything. We've been going in circles for years.
We reached the NASCAR-racing equivalent of scientific research.