I expect it will be a net positive: they proved that you can both train and run inference against powerful models for way less compute than people had previously expected - and they published enough details that other AI labs are already starting to replicate their results.
I think this will mean cheaper, faster, and better models.
>An Yong: But DeepSeek is a business, not a nonprofit research lab. If you innovate and open-source your breakthroughs—like the MLA architecture innovation releasing in May—won’t competitors quickly copy them? Where’s your moat?
>Liang Wenfeng: In disruptive tech, closed-source moats are fleeting. Even OpenAI’s closed-source model can’t prevent others from catching up.
>Therefore, our real moat lies in our team’s growth—accumulating know-how, fostering an innovative culture. Open-sourcing and publishing papers don’t result in significant losses. For technologists, being followed is rewarding. Open-source is cultural, not just commercial. Giving back is an honor, and it attracts talent.
Personally this looks to me like an ego thing: the DeepSeek team are really, really good and their CEO is enjoying the enormous attention they are getting, plus the pride of proving that Chinese AI labs can take the lead in a field that everyone thought the USA was unassailable in.
Maybe they are true believers in building and sharing "AGI" with the world?
Lots of people see this as a Chinese government backed conspiracy to undermine the US AI industry. I'm not sure how credible that idea is.
I saw somewhere (though I've not confirmed it with a second source) that none of the people listed on the DeepSeek papers got educated at US universities - they all went to school in China, which further emphasizes how good China's home-grown talent pool has got.
> a Chinese government backed conspiracy to undermine the US AI industry
To me this sounds like describing Lockheed as a US government backed conspiracy to undermine the Tupolev Aerospace Design Bureau. It really stretches the normal connotations of words, and it presupposes that the center of the world is conveniently located very close to the speaker.
> none of the people listed on the DeepSeek papers got educated at US universities
"You have been educated at foreign universities / worked at foreign companies" is indeed an excuse they have used at least once to refuse a candidate. n=1 though so maybe that's just a convenient excuse. There's one guy who went to University of Adelaide (IIRC) on the paper.
It’s a bunch of known optimisations bundled together rather than any single revolutionary change.
More open than any other model (but still a bespoke licence) and bundles together a bunch of known improvements. There’s nothing to hide here honestly and without the openness it wouldn’t be as interesting.
'So are we close to AGI?
It definitely seems like it. This also explains why Softbank (and whatever investors Masayoshi Son brings together) would provide the funding for OpenAI that Microsoft will not: the belief that we are reaching a takeoff point where there will in fact be real returns towards being first.'
This may mean that $3k/task on some benchmarks published by OpenAI are now at slightly lower price tag.
It is possible however that OpenAI was using similar level acceleration in the first place, they’ve just not published the details. And a few engineers left and replicated (or even bested it) in a new lab.
Overall, it’s a good boost, modern software is getting a better fit into new generation of hardware and is performing faster. Maybe we should pay more attention when NVIDIA is publishing their N-times faster ToPS numbers, and not completely dismissing it as marketing.
I expect it will be a net positive: they proved that you can both train and run inference against powerful models for way less compute than people had previously expected - and they published enough details that other AI labs are already starting to replicate their results.
I think this will mean cheaper, faster, and better models.
This FAQ about it is very good: https://stratechery.com/2025/deepseek-faq/