Article: https://proton.me/blog/deepseek
Calls it “Deepsneak”, failing to make it clear that the reason people love Deepseek is that you can download and it run it securely on any of your own private devices or servers - unlike most of the competing SOTA AIs.
I can’t speak for Proton, but the last couple weeks are showing some very clear biases coming out.
These guys are in the open source business themselves, they should know the answer to this question.
Has anyone actually analyzed the source code thoroughly yet? I’ve seen a ton of reporting on its open source nature but nothing about the detailed nature of the source.
FOSS only = safe if the code has been audited in depth.
A few of my friends who are a lot more knowledgeable about LLMs than myself are having a good look over the next week or so. It’ll take some time, but I’m sure they will post their results when they are done (pretty busy times unfortunately).
I’ll do my best to remember to come back here with a link or something when I have more info 😊
That said, hopefully someone else is also taking a look and we can get a few different perspectives.
I haven’t looked into Deepseek specifically so I could be mistaken, but a lot of times when a model is called “open-source” it really is just open weights. You can download it or train other models off of it, but you can’t actually view any kind of source code on how the model works.
An audit isn’t really possible.
It is open-weight, we dont have access to the training code nor the dataset.
That being said it should be safe for your computer to run Deepseeks models since the weight are .safetensors which should block any code execution from injected code in the models weight.
Then by default it should never be considered safe. Honestly, this “open” release… it makes me wonder about ulterior motives.
That’s not quite it either.
The model itself is just a giant ball of math. They made a thing that can transform an English through the collected knowledge of much of humanity a few dozen times and have it crap out a reasonable English answer.
The open source part is kind of a misnomer. They explained how they cooked the meal but not the ingredient list.
To complete the analogy, their astounding claim is that they managed to cook the meal with less fire than anyone else has by a factor of like 1000.
But the model itself is inherently safe. It’s not like it’s a binary that can carry a virus or do crazy crap. Even convincing it to do give planned nefarious answers is frankly beyond our capabilities so far.
The dangerous part that proton is looking at and honestly is a given for any hosted AI, is in the hosting server side of things. You make your requests to their servers and then their servers put the requests into the model and return you the output.
If you ask their web servers for information about tiananmen square they will block you.
You can, however, download the model yourself and run it yourself and there’s not any security issues there.
It will tell you anything that you need to know about tiananmen square.
What are the minimum system requirements to run something like deepseek on your own computer in some kind of firewall container?
We’re running it at work on a Mac mini with 64GB RAM (48GB for the GPU), and while it’s a little slow, it works fine.
There are plenty of ways and they are all safe. Don’t think of DeepSeek as anything more than a (extremely large, like bigger than a AAA) videogame. It does take resources, e.g disk space and RAM and GPU VRAM (if you have some) but you can use “just” the weights and thus the executable might come from another project, an open-source one that will not “phone home” (assuming that’s your worry).
I detail this kind of things and more in https://fabien.benetou.fr/Content/SelfHostingArtificialIntelligence but to be more pragmatic I’d recommend
ollamawhich supports https://ollama.com/library/deepseek-r1So, assuming you have a relatively entry level computer you can install
ollamathenollama run deepseek-r1:1.5band try.FWIW I did just try
deepseek-r1:1.5b(the smallest model available viaollamatoday) and … not bad at all for 1.1Gb!It’s still AI BS generating slop without “thinking” at all … but from the few tests I ran, it might be one of the “least worst” smaller model I tried.
Seems reasonable to think part of the motivation is disrupting American tech like openAI
They very much do not believe that open source means safe or private. They have a tons of articles talking about the hurdles they have gone through to try and ensure they are, and where and when they have failed to do so.
If I obfuscate my code such that it’s very difficult to understand then in practice it’s like proprietary software, even with an open source license.
Correct me if I’m wrong but looking at the code isn’t enough to understand what a neural network will do (if these “AI” are using that, maybe they’re not).
Deepseek’s R1 was built entirely on a multi-stage reinforcement learning process, and they pretty much open sourced that entire pipeline. By contrast, OpenAI has been giving us nothing but “look what we did” since GPT-3, and we’re supposed to trust them.