This kinda does support the 'DeepSeek is the side project of a bunch of quants' angle.
Seems like the kind of mistake you would make if you are not used to deploying external client facing applications.
Seems like the kind of mistake you would make if you are not used to deploying external client facing applications.
[0] https://www.spiegel.de/international/business/we-know-where-...
You need a software first agile mentality from the leadership of the company on downwards and these legacy companies just dont have it.
Agile workflow for frequently updating non-critical software in devices that happen to be cars? Sure.
I can release a website with a list of known bugs. Do any govt allow release of cars with known bugs?
As long as you're reasonably confident that the bugs don't pose a safety issue I don't see the problem.
It's been an absolute disaster, with billions of dollars spent to produce delayed, buggy software.
https://venturebeat.com/offbeat/how-volkswagen-used-software...
The problem with software companies is they’re bad at hardware for the same reason.
User experience companies can be good at both. Maybe not as good at hardware as a hardware company, maybe not as good at software as software companies.
Apple’s the obvious example, but Google, Garmin, heck even Starbucks are also good examples. Start with the user experience, build hardware of software or whatever else is needed. Specializing in a tool has value, but limits you to that tool.
They build whatever hardware (in store) or software (mobile / back end) is necessary to give the user experience they want.
But you’re absolutely right — we can lump their mediocre coffee into hardware, or call it “goods” as a third category that you also don’t have to be the best at if you’re a UX company.
Safety-critical firmware is scrutinized fairly well (not because it's not a side project, but because of regulatory constraints combined with the small scope allowing the car manufacturers to treat it as a fungible good), but other software is not, even broken feedback loops interacting with that firmware.
If I could walk everywhere the rest of my life, I would.
Some organizations have some form of Enterprise Architecture group that governs technology and ensures that there is discipline though the maturity and scope varies. I would say most organizations are completely devoid of that type of supervision and oversight.
It's unfortunately far too counter to "move fast and break stuff" that startup space tends to be enamored of, because they tend to want you to do things safely and try to avoid a "Front page of the New York Times" type of security event.
I think they correctly believe security failures are at most a short term PR problem as far as the market is concerned.
https://news.ycombinator.com/item?id=41678840
The joke is these companies build systems that can tell them how to implement better security, they simply don't care.
I doubt it very much that it only was that and not massivly backed by the Chinese state in general.
As with OpenAI, much of this has to do with hype based speculation.
In the case of OpenAI they played with the speculations, that they might have AGI locked up in their labs already and fueled those speculations. The result, massive investment (now in danger).
And China and the US play a game of global hegemony. I just read articles with the essence of, see China is so great, that a small sideproject there can take down the leading players from the west! Come join them.
It is mere propaganda to me.
Now deepseek in the open is a good thing, but I believe the Chinese state is backing it up massivly to help with that success and to help shake the western world of dominance. I would also assume, the chinese intelligence services helped directly with Intel straight out of OpenAI and co labs.
This is about real power.
Many states are about to decide which side they should take, if they have to choose between West and East. Stuff like this heavily influences those decisions.
(But btw. most don't want to have to choose)
Alibaba has Qwen. Baidu, Huawei, Tencent, etc all have their own AI models. The Chinese government would most likely push one of these forward with their backing, not an unknown small company.
I don't claim it is all staged. The researchers seem genuine. But they can be good researchers and still said yes at some point to big government help, if smart chinese government employes recognized their potential.
# Please install OpenAI SDK first: `pip3 install openai`
from openai import OpenAI
client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")The client facing aspect isn’t the problem here. This linked article is talking about the backend having vulnerabilities, not the client facing application. It’s about a database that is accessible from the internet, with no authentication, with unencrypted data sitting in it. High Flyer, the parent company of Deep Seek, already has a lot of backend experience, since that is a core part of the technologies they’ve built to operate the fund. If you’re a quantitative hedge fund, you aren’t just going to be lazy about your backend systems and data security. They have a lot of experience and capability to manage those backend systems just fine.
I’m not saying other companies are perfect either. There’s a long list of American companies that violate user privacy, or have bad security that then gets exploited by (often Chinese or Russian) hackers. But encrypting data in a database seems really basic, and requiring authentication on a database also seems really basic. It would be one thing if exposure of sensitive info required some complicated approach. But this degree of failure raises lots of questions whether such companies can ever be trusted.
This is not fair. Is OpenAI, for example, including the CEO paycheck for the model training costs?
Neither end is terribly useful. Unfortunately, the $5.5M number is for the latter.
You're reciting a bunch of absolute numbers, without any sort of context at all. $5M isn't the same for every company. For example, in 2020, it seems High Flyer spent a casual $27M on a supercomputer. They later replaced that with a $138M new computer. $5.5M sounds like something that could be like a side-project for a company like that, whose blood and sweat is literally money.
> But this degree of failure raises lots of questions whether such companies can ever be trusted.
This, I agree with though. I wouldn't trust sending my data over to them. Using their LLMs though, on my own hardware? Don't mind if I do, as long as it's better, I don't really mind what country it is imported from.
From the mouth of Liang Wenfeng, co-founder of both High Flyer and DeepSeek, 18 months ago:
"Our large-model project is unrelated to our quant and financial activities. We’ve established an independent company called DeepSeek, to focus on this."
https://www.chinatalk.media/p/deepseek-from-hedge-fund-to-fr...
But the software? Absolute disaster.
When people say DeepSeek is a side project, this is what I assume they mean. It's different when a bunch of software engineers make something with terrible security because it's their main job. With bunch of academics (and no offense to academics), software is not their main job. You could be working on teaching them how to use version control.
Zero evidence that the above statement is true, and weak evidence (authors' claims) that it is false. Have you read their papers even?
https://arxiv.org/html/2412.19437v1#abstract https://arxiv.org/pdf/2501.12948
This includes salary for ~130 ML people + rest of the staff, company is 2 years old. They have trained DeepSpeek V1, V2, R1, R1-Zero before finally training V3, as well as a bunch of other less known models.
The final run of V3 is ~6M$ (at least officially...[1]), but that does not factor the cost of all the other failed runs, ablations etc. that always happen when developing a new model.
You also can't get clusters of this size with a 3 weeks commitment just to do your training and then stop paying for it, there is always a multi-month (if not 1 year) commitment because of demand/supply. Or, if it's a private cluster they own it's already a $200M-300M+ investment just for the advertised 2000 GPUs for that run.
I don't know if it really is $1B, but it certainly isn't below $100M.
[1] I personally believe they used more GPUs than stated, but simply can't be forthcoming about this for obvious reason. I have of course not proof of that, my belief is just based on scaling laws we have seen so far + where the incentives are for stating the # of GPUs. But even if the 2k GPUs figure is accurate, it's still $100M+
Is that true? No idea. But there isn't zero evidence.
I'm sure you were just mislead by all the people including Anthropic's Dario parroting this claim, but even Dario already said he was wrong to say that and semi analysis already clarified it was a misunderstanding of their claim, which was 50,000 H series, not 50,000 H100.
Can we stop with this nonsense ?
The list of author of the paper is public, you can just go look it up. There are ~130 people on the ML team, they have regular ML background just like you would find at any other large ML labs.
Their infra cost multiple millions of dollar per month to run, and the salary of such a big team is somewhere in the $20-50M per year (not very au fait of the market rate in china hence the spread).
This is not a sideproject.
Edit: Apparently my comment is confusing some people. Am not arguing that ML people are good at security. Just that DS is not the side project of a bunch of quant bros.
So maybe not a side project, but if you have ever worked with ML researchers before, lack of engineering/security chops shouldn't be that surprising to you.
The mythologizing around deepseek is just absurd.
"Deepseek is the tale of one lowly hedgefund manager overcoming the wicked American AI devils". Every day I hear variations of this, and the vast majority of it is based entirely in "vibes" emanating from some unknown place.
It's fascinating that a couple of years and a few competitors in, the DeepSeek moment parallels it so closely.
Very interesting! I'm sure you have a source for this claim?
This myth of DS being a side project literally started from one tweet. DeepSeek the company is funded by a company whose main business is being a hedge fund, but DeepSeek itself from day 1 has been all about building LLM to reach AGI, completely independent.
This is like saying SpaceX is the side-project of a few caremaking bros, just because Elon funded and manages both. They are unrelated.
Again, you can easily google the name of the authors and look at their background, you will find people with PhD in LLM/multimodal models, internships at Microsoft Research etc. No trace of background on quant or time series prediction or any of that.
From the mouth of the CEO himself 2 years ago: "Our large-model project is unrelated to our quant and financial activities. We’ve established an independent company called DeepSeek, to focus on this." [0]
It's really interesting to see how after 10 years debating the mythical 10x engineer, we have now overnight created the mythical 100x Chinese quant bro researcher, that can do 50x better models than the best U.S. people, after 6pm while working on his side project.
[0]: https://www.chinatalk.media/p/deepseek-from-hedge-fund-to-fr...
However, i'm not sure that them being LLM researchers compared to quant researchers changes the dynamic of their relaxed security posture.
It does not indeed, but that's not the part I was commenting on.
https://www.pekingnology.com/p/ceo-of-deepseeks-parent-high-...
TDLR Highflyer started very much as exclusive ML/AI focused quant investment firm, with a lot of compute for finance AI and mining. Then CCP cracked down on mining... then finance, so Liang probably decided to pivot to LLM/AGI, which likely started as side project, but probably not anymore now the DeepSeek has taken off and Liang just met with PRC premiere a few days ago. DeepSeek being independent company doesn't mean DeepSeek isn't Liang's side project using compute bought with hedge fund money that is primarily used for hedgefund work, cushioned/allowed to get by with low margins by hedgefund profits.
The point is, the team actually doing the DeepSeek work are working on this as their exclusive project, have been hired exclusively for this etc.
They aren't doing this on the side of their main quant job, and destroying U.S. researchers just as a hobby as the myth would have us believe.
This wasn't narrow minded folks doing this. Shit happens.
OP means to say public API and app being a side project, which likely it is, the skills required to do ML have little overlap to skills required to run large complex workloads securely and at scale for public facing app with presumably millions of users.
The latter role also typically requires experience not just knowledge to do well which is why experiences SREs have very good salaries.
Data breaches from unsecured or accidentally-public servers/databases are not unusual among much larger entities than DeepSeek.
We're not talking some poor college students here.
I certainly would not, or it would take me a significant amount of time to do properly. I have been a full stack dev for 10 years. Now take that one step further to someone whose only interaction with a development is numpy, pandas, julia, etc…
You are, in typical HN style, minimising the problem into insignificance.
This is /not/ a “stick it behind an aws load balancer and on one of their abstracted services that does 99% of the work for you” - that would be less difficult.
E: love how this is getting ratioed by egotistical self confessed x10 engineers no doubt. Some self reflection is needed on your behalf. Just because /you/ think you would be capable, does not mean that the plethora of others would be able to.
What likely happened here is an ingress rule was set up wrongly on iptables or equivalent.. something many of your fellow engineers would have no clue about. An open dev database is rather normal if you want something out of the door quickly, why would you worry about an internal accessible only tool’s security if you trust your 10 or so staff. Have a think about the startups you have worked in (everyone here is a startup pro, just like you are - remember!) and what dire situation your mvp was in behind its smoke and mirrors PowerPoint slide deck.
Yes this was disastrous for PR. No it is not a problem solved in its entirety entirely by learned engineering experts like yourself.
Oh here. A comment from ClickHouse saying there is a legitimate reason why this will have been configured this way and happened https://news.ycombinator.com/item?id=42873446
There are many in the software engineering field which could not satisfy a request of this nature, for any reasonable form of "asked them to".
I don’t know if you are in agreement with me or not
So we're good. :-)
There was a recent comment which said along the lines of “I used to watch figure skating, seeing them race around and spin, and think no big deal. It was only when I went on ice that I realised how difficult and impressive what they were doing was” - this is exactly the trap SWEs are most guilty of. — /this/ is what you learn as a staff level.
>An open dev database is rather normal
Not open to the internet it's not! Internal network, perhaps.
>someone whose only interaction with a development is numpy, pandas, julia, etc
This person should be aware of their limitations and give the task to someone who knows what they're doing.