DeepSeek and other Chinese companies. Not only do they publish research, they also put their resources where their mouth (research) is. They actually use it and prove it through their open models.

Most research coming out of big US labs is counter indicative of practical performance. If it worked (too) well in practice, it wouldn't have been published.

Some examples from DeepSeek:

https://arxiv.org/abs/2405.04434

https://arxiv.org/abs/2502.11089

Well it's cool that they released a paper, but at this point it's been 11 months and you can't download a Titans-architecture model code or weights anywhere. That would put a lot of companies up ahead of them (Meta's Llama, Qwen, DeepSeek). Closest you can get is an unofficial implementation of the paper https://github.com/lucidrains/titans-pytorch

Bytedance is publishing pretty aggressively.

Recently, my favorite from them was lumine: https://arxiv.org/abs/2511.08892

Here's their official page: https://seed.bytedance.com/en/research

Meta is also being pretty open with their stuff. And recently most of the Chinese competition.

> Is there any other company that's openly publishing their research on AI at this level? Google should get a lot of credit for this.

80% of the ecosystem is built on top of companies, groups and individuals publishing their research openly, not sure why Google would get more credit for this than others...

It was not always like this. Google was very secretive in the early days. We did not start to see things until the GFS, BigTable and Borg (or Chubby) papers in 2006 timeframe.

Working with 1M context windows daily - the real limitation isn't storage but retrieval. You can feed massive context but knowing WHICH part to reference at the right moment is hard. Effective long-term memory needs both capacity and intelligent indexing.

Every Google publication goes through multiple review. If anyone thinks the publication is a competitor risk it gets squashed.

It's very likely no one is using this architecture at Google for any production work loads. There are a lot of student researchers doing fun proof of concept papers, they're allowed to publish because it's good PR and it's good for their careers.

The author is listed as a "student researcher", which might include a clause that students can publish their results.

Here is a bit more information about this program: https://www.google.com/about/careers/applications/jobs/resul...

Arxiv is flooded with ML papers. Github has a lot of prototypes for them. I'd say it's pretty normal with some companies not sharing for perceived, competitive advantage. Perceived because it may or may not be real vs published prototypes.

We post a lot of research on mlscaling sub if you want to look back through them.

https://www.reddit.com/r/t5_3bzqh1/s/yml1o2ER33

lol you don't get it. If it's published it means it's not very useful

Maybe it's just misdirection - a failed approach ?

Given the competitive nature of the AI race, it's hard to believe any of these companies are really trying to help the competition.