The article is vague about the companies in the paper, for some reason.

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.

As far as I can tell, the paper never actually mentions the companies who aren't publishing papers. Open AI, Anthropic, and hugging face are all specifically mentioned as companies that do publish papers. Just FYI for anyone else who reads "AI's top startups" and immediately assumes OpenAI and Anthropic.

Perhaps I'm imagining it but the entire industry was build on public research, this "AI wave" is at odds with that and seems to be driven by greed (although they'll claim some arms race or something to help themselves sleep at night).

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.

Yet none of them would have been here if Google hadn't published "Attention is all you need", the irony.

I’m not sure why this is so surprising? AI company does not automatically mean research company. The vast majority of new startups popping up over the last few years have commercial motivations, and use models built by someone else. Why are you expecting them to publish scientific papers?

50% of startups contributing to public research is actually a crazy good outcome. That’s far more than I had expected.

What the blogificafion of AI research has done is allowed all kinds of claims and terminology related to AI to be introduced and taken up in a manner replicating social media dynamics. And that is simply not healthy. We’re fast reaching a place where any claim can be backed up with a set of numbers from a number of experiments run in some gamified environment or the other, with little concern for if it all adds up to anything. It’s a vicious loop, because this same junk then goes in to train the next models which help spit out the next set of models AND blogs/papers. The net effect is not dissimilar to setting termites loose in a library.

Once something goes commercial, academics have to consider what progress would be research-worthy, rather than a half-baked prototype for a product or feature.

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.

The age of the dark forest is upon us

Do startups in other fields constantly publish their research?

Trade secrets are back, baby!

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.

All startups barely publish their research, because doing that would be incredibly stupid for the most part, because they want to sell the stuff they invent not give it away for free.

gate keepers of antiquated practice decry people realizing they they dont need to get past the gate

Funny, as ONE PERSON with Claude, I've been on a tear when it comes to publishing my own research:

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!

> “If we were racing forward on cancer-curing AI, I would be like, ’Fantastic, full steam ahead,’” she says. “But that’s not what we’re racing toward, right?”

We're not racing towards anything. We've been going in circles for years.

That’s because most of its slop, and not reproducible