The “1 trillion” never existed in the first place. It was all hype by a bunch of Tech-Bros, huffing each other’s farts.
Almost like yet again the tech industry is run by lemming CEOs chasing the latest moss to eat.
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.
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.
Yep, lookup ollama
Yes
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 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.
Yes the online model has those filters. Some one tried it with one of the downloaded models and it answers just fine
You misspelled “lies”. Or were you trying to type “psyops tool”??
When running locally, it works just fine without filters
I tried the smaller models and it’s not fine. It’s hard coded.
This was a local instance.
Does the same thing on my local instance.
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Yes but your server can’t handle the biggest LLM.
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They’d need to do some pretty fucking advanced hackery to be able to do surveillance on you just via the model. Everything’s possible I guess, but … yeah perhaps not.
If they could do that, essentially nothing you do on your computer would be safe.
This just shows how speculative the whole AI obsession has been. Wildly unstable and subject to huge shifts since its value isn’t based on anything solid.
It’s based on guessing what the actual worth of AI is going to be, so yeah, wildly speculative at this point because breakthroughs seem to be happening fairly quickly, and everyone is still figuring out what they can use it for.
There are many clear use cases that are solid, so AI is here to stay, that’s for certain. But how far can it go, and what will it require is what the market is gambling on.
If out of the blue comes a new model that delivers similar results on a fraction of the hardware, then it’s going to chop it down by a lot.
If someone finds another use case, for example a model with new capabilities, boom value goes up.
It’s a rollercoaster…
There are many clear use cases that are solid, so AI is here to stay, that’s for certain. But how far can it go, and what will it require is what the market is gambling on.
I would disagree on that. There are a few niche uses, but OpenAI can’t even make a profit charging $200/month.
The uses seem pretty minimal as far as I’ve seen. Sure, AI has a lot of applications in terms of data processing, but the big generic LLMs propping up companies like OpenAI? Those seems to have no utility beyond slop generation.
Ultimately the market value of any work produced by a generic LLM is going to be zero.
It’s difficult to take your comment serious when it’s clear that all you’re saying seems to based on ideological reasons rather than real ones.
Besides that, a lot of the value is derived from the market trying to figure out if/what company will develop AGI. Whatever company manages to achieve it will easily become the most valuable company in the world, so people fomo into any AI company that seems promising.
Besides that, a lot of the value is derived from the market trying to figure out if/what company will develop AGI. Whatever company manages to achieve it will easily become the most valuable company in the world, so people fomo into any AI company that seems promising.
There is zero reason to think the current slop generating technoparrots will ever lead into AGI. That premise is entirely made up to fuel the current “AI” bubble
They may well lead to the thing that leads to the thing that leads to the thing that leads to AGI though. Where there’s a will
sure, but that can be said of literally anything. It would be interesting if LLM were at least new but they have been around forever, we just now have better hardware to run them
That’s not even true. LLMs in their modern iteration are significantly enabled by transformers, something that was only proposed in 2017.
The conceptual foundations of LLMs stretch back to the 50s, but neither the physical hardware nor the software architecture were there until more recently.
The market don’t care what either of us think, investors will do what investors do, speculate.
Language learning, code generatiom, brainstorming, summarizing. AI has a lot of uses. You’re just either not paying attention or are biased against it.
It’s not perfect, but it’s also a very new technology that’s constantly improving.
I decided to close the post now - there is place for any opinion, but I can see people writing things which are completely false however you look at them: you can dislike Sam Altman (I do), you can worry about China’s interest in entering the competition now and like that (I do), but the comments about LLM being useless while millions of people use it daily for multiple purposes sound just like lobbying.
The economy rests on a fucking chatbot. This future sucks.
On the brightside, the clear fragility and lack of direct connection to real productive forces shows the instability of the present system.
And no matter how many protectionist measures that the US implements we’re seeing that they’re losing the global competition. I guess protectionism and oligarchy aren’t the best ways to accomplish the stated goals of a capitalist economy. How soon before China is leading in every industry?
This conclusion was foregone when China began to focus on developing the Productive Forces and the US took that for granted. Without a hard pivot, the US can’t even hope to catch up to the productive trajectory of China, and even if they do hard pivot, that doesn’t mean they even have a chance to in the first place.
In fact, protectionism has frequently backfired, and had other nations seeking inclusion into BRICS or more favorable relations with BRICS nations.
Economy =/= stock market
That’s the thing: if the cost of AI goes down , and AI is a valuable input to businesses that should be a good thing for the economy. To be sure, not for the tech sector that sells these models, but for all of the companies buying these services it should be great.
Sure workers will reap a big chunk of that value right?
Right?.jpg
Only thanks to the PRC
Wow, China just fucked up the Techbros more than the Democratic or Republican party ever has or ever will. Well played.
It’s kinda funny. Their magical bullshitting machine scored higher on made up tests than our magical bullshitting machine, the economy is in shambles! It’s like someone losing a year’s wages in sports betting.
Just because people are misusing tech they know nothing about does not mean this isn’t an impressive feat.
If you know what you are doing, and enough to know when it gives you garbage, LLMs are really useful, but part of using them correctly is giving them grounding context outside of just blindly asking questions.
It is impressive, but the marketing around it has really, really gone off the deep end.
Democrats and Republicans have been shoveling truckload after truckload of cash into a Potemkin Village of a technology stack for the last five years. A Chinese tech company just came in with a dirt cheap open-sourced alternative and I guarantee you the American firms will pile on to crib off the work.
Far from fucking them over, China just did the Americans’ homework for them. They just did it in a way that undercuts all the “Sam Altman is the Tech Messiah! He will bring about AI God!” holy roller nonsense that was propping up a handful of mega-firm inflated stock valuations.
Small and Mid-cap tech firms will flourish with these innovations. Microsoft will have to write the last $13B it sunk into OpenAI as a lose.
Didn’t donald add like $500B for AI? Seems it’salmost enough to pay the -$600B nVidia lost…
Well… if there is one thing I have to commend CCP is they are unafraid to crack down on billionaires after all.
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?
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…”
Yes but have you considered that “china bad”?
It’s not multimodal so I’d have to imagine it wouldn’t be worth pursuing in that regard.
doesn’t deepseek work on that though with their janus models?
No surprise. American companies are chasing fantasies of general intelligence rather than optimizing for today’s reality.
That, and they are just brute forcing the problem. Neural nets have been around for ever but it’s only been the last 5 or so years they could do anything. There’s been little to no real breakthrough innovation as they just keep throwing more processing power at it with more inputs, more layers, more nodes, more links, more CUDA.
And their chasing a general AI is just the short sighted nature of them wanting to replace workers with something they don’t have to pay and won’t argue about it’s rights.
Also all of these technologies forever and inescapably must rely on a foundation of trust with users and people who are sources of quality training data, “trust” being something US tech companies seem hell bent on lighting on fire and pissing off the yachts of their CEOs.
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
Nvidia’s most advanced chips, H100s, have been banned from export to China since September 2022 by US sanctions. Nvidia then developed the less powerful H800 chips for the Chinese market, although they were also banned from export to China last October.
I love how in the US they talk about meritocracy, competition being good, blablabla… but they rig the game from the beginning. And even so, people find a way to be better. Fascinating.
You’re watching an empire in decline. It’s words stopped matching its actions decades ago.
Don’t forget about the tariffs too! The US economy is actually a joke that can’t compete on the world stage anymore except by wielding their enormous capital from a handful of tech billionaires.
Hello darkness my old friend
It’s knowledge isn’t updated.
It doesn’t know current events, so this isn’t a big gotcha moment
It’s still hilarious.
It’s somewhat enjoyable.
It continued like this though
Thanks for now. Bye.
What you trying to be on skynets good side or something?
We will have true AI once it is capable of answering “I don’t know” instead of making things up
Turns out, some people i know are apparently fake AI.
Which is actually something Deepseek is able to do.
Even if it can still generate garbage when used incorrectly like all of them, it’s still impressive that it will tell you it doesn’t “know” something, but can try to help if you give it more context. which is how this stuff should be used anyway.
Let’s tariff taiwan!
TSMC just finished building out a foundry in Arizona, so there’s a nativist argument that we don’t need the island’s original facilities anymore.
Only building outdated chips on an old fab process. And they’re having a hard time hiring Americans to work there.
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.
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.
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
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.
Emergence of DeepSeek raises doubts about sustainability of western artificial intelligence boom
Is the “emergence of DeepSeek” really what raised doubts? Are we really sure there haven’t been lots of doubts raised previous to this? Doubts raised by intelligent people who know what they’re talking about?
Ah, but those “intelligent” people cannot be very intelligent if they are not billionaires. After all, the AI companies know exactly how to assess intelligence:
Microsoft and OpenAI have a very specific, internal definition of artificial general intelligence (AGI) based on the startup’s profits, according to a new report from The Information. … The two companies reportedly signed an agreement last year stating OpenAI has only achieved AGI when it develops AI systems that can generate at least $100 billion in profits. That’s far from the rigorous technical and philosophical definition of AGI many expect. (Source)
