- cross-posted to:
- technology@beehaw.org
- cross-posted to:
- technology@beehaw.org
Looks like it is not any smarter than the other junk on the market. The confusion that people consider AI as “intelligence” may be rooted in their own deficits in that area.
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware. Hurray! Progress!
It is open source, so it should be audited and if there are back doors they can be plugged in a fork
Looks like it is not any smarter than the other junk on the market. The confusion that people consider AI as “intelligence” may be rooted in their own deficits in that area.
Yep, because they believed that OpenAI’s (two lies in a name) models would magically digivolve into something that goes well beyond what it was designed to be. Trust us, you just have to feed it more data!
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware. Hurray! Progress!
That’s the neat bit, really. With that model being free to download and run locally it’s actually potentially disruptive to OpenAI’s business model. They don’t need to do anything malicious to hurt the US’ economy.
I’m tired of this uninformed take.
LLMs are not a magical box you can ask anything of and get answers. If you are lucky and blindly asking questions it can give some accurate general data, but just like how human brains work you aren’t going to be able to accurately recreate random trivia verbatim from a neural net.
What LLMs are useful for, and how they should be used, is a non-deterministic parsing context tool. When people talk about feeding it more data they think of how these things are trained. But you also need to give it grounding context outside of what the prompt is. give it a PDF manual, website link, documentation, whatever and it will use that as context for what you ask it. You can even set it to link to reference.
You still have to know enough to be able to validate the information it is giving you, but that’s the case with any tool. You need to know how to use it.
As for the spyware part, that only matters if you are using the hosted instances they provide. Even for OpenAI stuff you can run the models locally with opensource software and maintain control over all the data you feed it. As far as I have found, none of the models you run with Ollama or other local AI software have been caught pushing data to a remote server, at least using open source software.
It is progress in a sense. The west really put the spotlight on their shiny new expensive toy and banned the export of toy-maker parts to rival countries. One of those countries made a cheap toy out of jank unwanted parts for much less money and it’s of equal or better par than the west’s.
As for why we’re having an arms race based on AI, I genuinely dont know. It feels like a race to the bottom, with the fallout being the death of the internet (for better or worse)
With understanding LLM, I started to understand some people and their “reasoning” better. That’s how they work.
artificial intelligence
AI has been used in game development for a while and i havent seen anyone complain about the name before it became synonymous with image/text generation
It was a misnomer there too, but at least people didn’t think a bot playing C&C would be able to save the world by evolving into a real, greater than human intelligence.
Well, that is where the problems started.
The difference is that you can actually download this model and run it on your own hardware (if you have sufficient hardware). In that case it won’t be sending any data to China. These models are still useful tools. As long as you’re not interested in particular parts of Chinese history of course ;p
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware.
LLMs aren’t spyware, they’re graphs that organize large bodies of data for quick and user-friendly retrieval. The Wikipedia schema accomplishes a similar, abet more primitive, role. There’s nothing wrong with the fundamentals of the technology, just the applications that Westoids doggedly insist it be used for.
If you no longer need to boil down half a Great Lake to create the next iteration of Shrimp Jesus, that’s good whether or not you think Meta should be dedicating millions of hours of compute to this mind-eroding activity.
There’s nothing wrong with the fundamentals of the technology, just the applications that Westoids doggedly insist it be used for.
Westoids? Are you the type of guy I feel like I need to take a shower after talking to?
I think maybe it’s naive to think that if the cost goes down, shrimp jesus won’t just be in higher demand. Shrimp jesus has no market cap, bullshit has no market cap. If you make it more efficient to flood cyberspace with bullshit, cyberspace will just be flooded with more bullshit. Those great lakes will still boil, don’t worry.
Good. LLM AIs are overhyped, overused garbage. If China putting one out is what it takes to hack the legs out from under its proliferation, then I’ll take it.
Cutting the cost by 97% will do the opposite of hampering proliferation.
Possibly, but in my view, this will simply accelerate our progress towards the “bust” part of the existing boom-bust cycle that we’ve come to expect with new technologies.
They show up, get overhyped, loads of money is invested, eventually the cost craters and the availability becomes widespread, suddenly it doesn’t look new and shiny to investors since everyone can use it for extremely cheap, so the overvalued companies lose that valuation, the companies using it solely for pleasing investors drop it since it’s no longer useful, and primarily just the implementations that actually improved the products stick around due to user pressure rather than investor pressure.
Obviously this isn’t a perfect description of how everything in the work will always play out in every circumstance every time, but I hope it gets the general point across.
It’s not about hampering proliferation, it’s about breaking the hype bubble. Some of the western AI companies have been pitching to have hundreds of billions in federal dollars devoted to investing in new giant AI models and the gigawatts of power needed to run them. They’ve been pitching a Manhattan Project scale infrastructure build out to facilitate AI, all in the name of national security.
You can only justify that kind of federal intervention if it’s clear there’s no other way. And this story here shows that the existing AI models aren’t operating anywhere near where they could be in terms of efficiency. Before we pour hundreds of billions into giant data center and energy generation, it would behoove us to first extract all the gains we can from increased model efficiency. The big players like OpenAI haven’t even been pushing efficiency hard. They’ve just been vacuuming up ever greater amounts of money to solve the problem the big and stupid way - just build really huge data centers running big inefficient models.
No but it would be nice if it would turn back in the tool it was. When it was called machine learning like it was for the last decade before the bubble started.
What DeepSeek has done is to eliminate the threat of “exclusive” AI tools - ones that only a handful of mega-corps can dictate terms of use for.
Now you can have a Wikipedia-style AI (or a Wookiepedia AI, for that matter) that’s divorced from the C-levels looking to monopolize sectors of the service economy.
It’s been known for months that they were living on borrowed time: Google “We Have No Moat, And Neither Does OpenAI” Leaked Internal Google Document Claims Open Source AI Will Outcompete Google and OpenAI
Overhyped? Sure, absolutely.
Overused garbage? That’s incredibly hyperbolic. That’s like saying the calculator is garbage. The small company where I work as a software developer has already saved countless man hours by utilising LLMs as tools, which is all they are if you take away the hype; a tool to help skilled individuals work more efficiently. Not to replace skilled individuals entirely, as Sam Dead eyes Altman would have you believe.
LLMs as tools,
Yes, in the same way that buying a CD from the store, ripping to your hard drive, and returning the CD is a tool.
Interesting it won’t let you login or signup using a VPN, even set to the correct country
Aren’t VPNs illegal in China?
The best part is that it’s open source and available for download
So can I have a private version of it that doesn’t tell everyone about me and my questions?
Checkout ollama. https://ollama.com/library/deepseek-r1
Thank you very much. I did ask chatGPT was technical questions about some… subjects… but having something that is private AND can give me all the information I want/need is a godsend.
Goodbye, chatGPT! I barely used you, but that is a good thing.
Yes
Yep, lookup ollama
Yeah, but you have to run a different model if you want accurate info about China.
Unfortunately it’s trained on the same US propaganda filled english data as any other LLM and spits those same talking points. The censors are easy to bypass too.
Yeah but China isn’t my main concern right now. I got plenty of questions to ask and knowledge to seek and I would rather not be broadcasting that stuff to a bunch of busybody jackasses.
I agree. I don’t know enough about all the different models, but surely there’s a model that’s not going to tell you “<whoever’s> government is so awesome” when asking about rainfall or some shit.
Can someone with the knowledge please answer this question?
I watched one video and read 2 pages of text. So take this with a mountain of salt. From that I gathered that deepseek R1 is the model you interact with when you use the app. The complexity of a model is expressed as the number of parameters (though I don’t know yet what those are) which dictate its hardware requirements. R1 contains 670 bn Parameter and requires very very beefy server hardware. A video said it would be 10th of GPUs. And it seems you want much of VRAM on you GPU(s) because that’s what AI crave. I’ve also read 1BN parameters require about 2GB of VRAM.
Got a 6 core intel, 1060 6 GB VRAM,16 GB RAM and Endeavour OS as a home server.
I just installed Ollama in about 1/2 an hour, using docker on above machine with no previous experience on neural nets or LLMs apart from chatting with ChatGPT. The installation contains the Open WebUI which seems better than the default you got at ChatGPT. I downloaded the qwen2.5:3bn model (see https://ollama.com/search) which contains 3 bn parameters. I was blown away by the result. It speaks multiple languages (including displaying e.g. hiragana), knows how much fingers a human has, can calculate, can write valid rust-code and explain it and it is much faster than what i get from free ChatGPT.
The WebUI offers a nice feedback form for every answer where you can give hints to the AI via text, 10 score rating thumbs up/down. I don’t know how it incooperates that feedback, though. The WebUI seems to support speech-to-text and vice versa. I’m eager to see if this docker setup even offers programming APIs.
I’ll probably won’t use the proprietary stuff anytime soon.
Yes, you can run a downgraded version of it on your own pc.
Apparently phone too! Like 3 cards down was another post linking to instructions on how to run it locally on a phone in a container app or termux. Really interesting. I may try it out in a vm on my server.
I asked it about Tiananmen Square, it told me it can’t answer that because it can only respond with “harmless” responses.
That’s kind of normal, it was made in China after all and the developers didn’t want to end up in jail I bet.
That said, china is of course a crappy dictatorship.
Yes the online model has those filters. Some one tried it with one of the downloaded models and it answers just fine
This was a local instance.
Does the same thing on my local instance.
When running locally, it works just fine without filters
Yes but your server can’t handle the biggest LLM.
As a European, gotta say I trust China’s intentions more than the US’ right now.
Not really a question of national intentions. This is just a piece of technology open-sourced by a private tech company working overseas. If a Chinese company releases a better mousetrap, there’s no reason to evaluate it based on the politics of the host nation.
Throwing a wrench in the American proposal to build out $500B in tech centers is just collateral damage created by a bad American software schema. If the Americans had invested more time in software engineers and less in raw data-center horsepower, they might have come up with this on their own years earlier.
You’re absolutely right.
Two times zero is still zero
With that attitude I am not sure if you belong in a Chinese prison camp or an American one. Also, I am not sure which one would be worse.
They should conquer a country like Switzerland and split it in 2
At the border, they should build a prison so they could put them in both an American and a Chinese prison
Wait. You mean every major tech company going all-in on “AI” was a bad idea. I, for one, am shocked at this revelation.
So if the Chinese version is so efficient, and is open source, then couldn’t openAI and anthropic run the same on their huge hardware and get enormous capacity out of it?
Yes but have you considered that “china bad”?
OpenAI could use less hardware to get similar performance if they used the Chinese version, but they already have enough hardware to run their model.
Theoretically the best move for them would be to train their own, larger model using the same technique (as to still fully utilize their hardware) but this is easier said than done.
Just ask the ai to assimilate the model?
Not necessarily… if I gave you my “faster car” for you to run on your private 7 lane highway, you can definitely squeeze every last bit of the speed the car gives, but no more.
DeepSeek works as intended on 1% of the hardware the others allegedly “require” (allegedly, remember this is all a super hype bubble)… if you run it on super powerful machines, it will perform nicer but only to a certain extend… it will not suddenly develop more/better qualities just because the hardware it runs on is better
Didn’t deepseek solve some of the data wall problems by creating good chain of thought data with an intermediate RL model. That approach should work with the tried and tested scaling laws just using much more compute.
This makes sense, but it would still allow a hundred times more people to use the model without running into limits, no?
hence certain tech grifters going “oh shitt…”
It’s not multimodal so I’d have to imagine it wouldn’t be worth pursuing in that regard.
One of those rare lucid moments by the stock market? Is this the market correction that everyone knew was coming, or is some famous techbro going to technobabble some more about AI overlords and they return to their fantasy values?
Most rational market: Sell off NVIDIA stock after Chinese company trains a model on NVIDIA cards.
Anyways NVIDIA still up 1900% since 2020 …
how fragile is this tower?
It’s quite lucid. The new thing uses a fraction of compute compared to the old thing for the same results, so Nvidia cards for example are going to be in way less demand. That being said Nvidia stock was way too high surfing on the AI hype for the last like 2 years, and despite it plunging it’s not even back to normal.
How is the “fraction of compute” being verified? Is the model available for independent analysis?
Its freely availible with a permissive license, but I dont think that that claim has been verified yet.
And the data is not available. Knowing the weights of a model doesn’t really tell us much about its training costs.
If AI is cheaper, then we may use even more of it, and that would soak up at least some of the slack, though I have no idea how much.
My understanding is it’s just an LLM (not multimodal) and the train time/cost looks the same for most of these.
- DeepSeek ~$6million https://www.theregister.com/2025/01/26/deepseek_r1_ai_cot/?td=rt-3a
- Llama 2 estimated ~$4-5 million https://www.visualcapitalist.com/training-costs-of-ai-models-over-time/
I feel like the world’s gone crazy, but OpenAI (and others) is pursing more complex model designs with multimodal. Those are going to be more expensive due to image/video/audio processing. Unless I’m missing something that would probably account for the cost difference in current vs previous iterations.
The thing is that R1 is being compared to gpt4 or in some cases gpt4o. That model cost OpenAI something like $80M to train, so saying it has roughly equivalent performance for an order of magnitude less cost is not for nothing. DeepSeek also says the model is much cheaper to run for inferencing as well, though I can’t find any figures on that.
My main point is that gpt4o and other models it’s being compared to are multimodal, R1 is only a LLM from what I can find.
Something trained on audio/pictures/videos/text is probably going to cost more than just text.
But maybe I’m missing something.
The original gpt4 is just an LLM though, not multimodal, and the training cost for that is still estimated to be over 10x R1’s if you believe the numbers. I think where R 1 is compared to 4o is in so-called reasoning, where you can see the chain of though or internal prompt paths that the model uses to (expensively) produce an output.
I’m not sure how good a source it is, but Wikipedia says it was multimodal and came out about two years ago - https://en.m.wikipedia.org/wiki/GPT-4. That being said.
The comparisons though are comparing the LLM benchmarks against gpt4o, so maybe a valid arguement for the LLM capabilites.
However, I think a lot of the more recent models are pursing architectures with the ability to act on their own like Claude’s computer use - https://docs.anthropic.com/en/docs/build-with-claude/computer-use, which DeepSeek R1 is not attempting.
Edit: and I think the real money will be in the more complex models focused on workflows automation.
Yea except DeepSeek released a combined Multimodal/generation model that has similar performance to contemporaries and a similar level of reduced training cost ~20 hours ago:
Holy smoke balls. I wonder what else they have ready to release over the next few weeks. They might have a whole suite of things just waiting to strategically deploy
One of the things you’re missing is the same techniques are applicable to multimodality. They’ve already released a multimodal model: https://seekingalpha.com/news/4398945-deepseek-releases-open-source-ai-multimodal-model-janus-pro-7b
Remember to cancel your Microsoft 365 subscription to kick them while they’re down
Joke’s on them: I never started a subscription!
I don’t have one to cancel, but I might celebrate today by formatting the old windows SSD in my system and using it for some fast download cache space or something.
and it’s open-source!
how long do you think it’ll take before the west decides to block all access to the model?
They actually can’t. Being open-source, it’s already proliferated. Apparently there are already over 500 derivatives of it on HuggingFace. The only thing that could be done is that each country in the West outlaws having a copy of it, like with other illegal materials. Even by that point, it will already be deep within business ecosystems across the globe.
Nup. OpenAI can be shut down, but it is almost impossible for R1 to go away at this point.
It’s ridiculous to think that there would still be an alliance of “Western Countries”. The Greenland thing, the threats related to NATO, tariff threats, techbros weaponising the US government to escape regulation in Europe etc etc. China is the FAR more reliable partner for Europe and South America. Good luck blocking the Chinese software in the US, but I think you will find no friends with your new leader in place.
Yeah there is a lot of bro-style crap going on right now, but China is a brutal dictatorship.
Choose wisely.
- Helping 800 Million People Escape Poverty Was Greatest Such Effort in History, Says [UN] Secretary-General, on Seventieth Anniversary of China’s Founding
- China’s Energy Use Per Person Surpasses Europe’s for First Time
- At 54, China’s average retirement age is too low
- China overtakes U.S. for healthy lifespan: WHO data
- https://news.harvard.edu/gazette/story/2020/07/long-term-survey-reveals-chinese-government-satisfaction/
- Chinese Scientists Are Leaving the United States [for China]
Is there a way for me to download and run it locally, or does that require a super computer?
Check out ollama.com You can download a whole bunch of models for free. The way I rum ollama is on linux from the cli, but if you can’t do it that way try jan.ai
If you have a GPU with ray tracing hardware and at least 12gVRAM you should be able to run it albeit slowly at home
The funny thing is, this was unveiled a while ago and I guess investors only just noticed it.
Text below, for those trying to avoid Twitter:
Most people probably don’t realize how bad news China’s Deepseek is for OpenAI.
They’ve come up with a model that matches and even exceeds OpenAI’s latest model o1 on various benchmarks, and they’re charging just 3% of the price.
It’s essentially as if someone had released a mobile on par with the iPhone but was selling it for $30 instead of $1000. It’s this dramatic.
What’s more, they’re releasing it open-source so you even have the option - which OpenAI doesn’t offer - of not using their API at all and running the model for “free” yourself.
If you’re an OpenAI customer today you’re obviously going to start asking yourself some questions, like “wait, why exactly should I be paying 30X more?”. This is pretty transformational stuff, it fundamentally challenges the economics of the market.
It also potentially enables plenty of AI applications that were just completely unaffordable before. Say for instance that you want to build a service that helps people summarize books (random example). In AI parlance the average book is roughly 120,000 tokens (since a “token” is about 3/4 of a word and the average book is roughly 90,000 words). At OpenAI’s prices, processing a single book would cost almost $2 since they change $15 per 1 million token. Deepseek’s API however would cost only $0.07, which means your service can process about 30 books for $2 vs just 1 book with OpenAI: suddenly your book summarizing service is economically viable.
Or say you want to build a service that analyzes codebases for security vulnerabilities. A typical enterprise codebase might be 1 million lines of code, or roughly 4 million tokens. That would cost $60 with OpenAI versus just $2.20 with DeepSeek. At OpenAI’s prices, doing daily security scans would cost $21,900 per year per codebase; with DeepSeek it’s $803.
So basically it looks like the game has changed. All thanks to a Chinese company that just demonstrated how U.S. tech restrictions can backfire spectacularly - by forcing them to build more efficient solutions that they’re now sharing with the world at 3% of OpenAI’s prices. As the saying goes, sometimes pressure creates diamonds. Image Image Last edited 4:23 PM · Jan 21, 2025 · 932.3K Views
Thank you for bringing the text over, I won’t click on X.
Deepthink R1(the reasoning model) was only released on January 20. Still took a while though.
Hilarious that this happens the week of the 5090 release, too. Wonder if it’ll affect things there.
Apparently they have barely produced any so they will all be sold out anyway.
And without the fake frame bullshit they’re using to pad their numbers, its capabilities scale linearly with the 4090. The 6090 just has more cores, Ram, and power.
If the 4000-series had had cards with the memory and core count of the 5090, they’d be just as good as the 50-series.
By that point you will have to buy the Mico fission reactor addon to power the 6090. It’s like Nvidia looked at the power triangle of power / price and preformence and instead of picking two they just picked one and to hell with the rest.
Nah, they just made the triangle bigger with AI (/s)
Lol serves you right for pushing AI onto us without our consent
The determination to make us use it whether we want to or not really makes me resent it.
Tech bros learn about diminishing returns challenge (impossible)
I am extremely ignorant of all this AI thing. So please can somebody “Explain Like I’m 5” why can this new thing can wipe off over a trillion dollars in US stock ? I would appreciate it a lot if you can help.
Basically US company’s involved in AI have been grossly over valued for the last few years due to having a sudo monopoly over AI tech (companies like open ai who make chat gpt and nvidia who make graphics cards used to run ai models)
Deep seek (Chinese company) just released a free, open source version of chat gpt that cost a fraction of the price to train (setup) which has caused the US stock valuations to drop as investors are realising the US isn’t the only global player, and isn’t nearly as far ahead as previously thought.
Nvidia is losing value as it was previously believed that top of the line graphics cards were required for ai, but turns out they are not. Nvidia have geared their company strongly towards providing for ai in recent times.
woohoo for Nvidia losing, fuck those cunts
*pseudo
Sudo is a linux command-line tool.
Thanks.
"You see, dear grandchildren, your grandfather used to have an apple orchard. The fruits were so sweet and nutritious that every town citizen wanted a taste because they thought it was the only possible orchard in the world. Therefore the citizens gave a lot of money to your grandfather because the citizens thought the orchard would give them more apples in return, more than the worth of the money they gave. Little did they know the world was vastly larger than our ever more arid US wasteland. Suddenly an oriental orchard was discovered which was surprisingly cheaper to plant, maintain, and produced more apples. This meant a significant potential loss of money for the inhabitants of the town called Idiocracy. Therefore, many people asked their money back by selling their imaginary not-yet-grown apples to people who think the orchard will still be worth more in the future.
This is called investing, children, it can make a lot of money, but it destroys the soul and our habitat at the same time, which goes unnoticed by all these people with advanced degrees. So think again when you hear someone speak with fancy words and untamed confidence. Many a times their reasoning falls below the threshold of dog poop. But that’s a story for another time. Sweet dreams."
The best description of reddit’s WallstreetBets sub I’ve ever seen.
I shall pin this comment to the top of my curriculum vitae.
Fantastic, thanks.
deleted by creator
Makes sense thanks.






















