Kimi K1.5: Scaling Reinforcement Learning with LLMs
12 comments
·January 21, 2025cuuupid
diggan
It's not just Chinese labs that do this, lots of companies upload a README to a GitHub repository then link that repository from the website, I guess so they can have a GitHub icon somewhere on the website?
Submission is basically a form for requesting access to their closed API (which ironically is called "OpenPlatform" for some reason).
rfoo
> which ironically is called "OpenPlatform" for some reason
This is pretty weird, the original text is 开放平台, but it basically is another name for "API" in China.
Not sure who started this, but it's really popular, for example, WeChat has an "Open Platform": https://open.weixin.qq.com/. AliPay too: https://open.alipay.com/. And peak strangeness, Alibaba Cloud (whose API is largely an AWS clone): https://open.aliyun.com/
diggan
Same thing in English, you have huge enterprises which basically operate on the complete opposite end of the spectrum, and end up calling themselves things like "OpenAI".
It even bleeds into marketing pages, go to the Llama website and you see "open source model" plastered all over the place, completely misusing both the "open" and "source" parts of it.
v3ss0n
How about OpenAI?
visarga
That is unfortunate but they do present some theoretical insights about scaling context length and probably a more efficient way to do RL. Even knowledge about it can have an effect on next iterations from other labs.
NitpickLawyer
Really unfortunate timing with Deepseek-R1 and the distills coming out at basically the same time. Hard for people to pay attention to, and plus open source > API, even if the results are a bit lower.
zurfer
Is it fair to say that 2 of the 3 leading models are from Chinese labs? It's really incredible how fast China has caught up.
asah
The set of math/logic problems behind AIME 2024 appears to be... https://artofproblemsolving.com/wiki/index.php/2024_AIME_I_P...
Impressive stuff! But unclear to me if it's literally just these 15 or if there's a large problem set...
abubakkarth
[dead]
beredis
[flagged]
I really, really dislike when companies use GitHub to promote their product by posting a "research paper" and a code sample.
It's not even an SDK, library, etc., it's just advertising.
I've noticed a number of China-based labs do this; they will often post a really cool demo, some images, and then either an API or just nothing except advertising for their company (e.g. model may not even exist). Often they will also promise in some GitHub issue that they will release the weights, and never do.
I'd love to see some sort of study here, I wonder what % of "omg really cool AI model!!!" hype papers [1] never provide an API, [2] cannot be reproduced at all, and/or [3] promise but never provide weights. If this was any other field, academics would be up in arms about likely fraud, false advertising, etc.