As a European, gotta say I trust China’s intentions more than the US’ right now.
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
Two times zero is still zero
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.
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.
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.
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.
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.
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
The market don’t care what either of us think, investors will do what investors do, speculate.
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.
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
Almost like yet again the tech industry is run by lemming CEOs chasing the latest moss to eat.
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 economy rests on a fucking chatbot. This future sucks.
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?
Only thanks to the PRC
Right?.jpg
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
I’d argue this is even worse than Sputnik for the US because Sputnik spurred technological development that boosted the economy. Meanwhile, this is popping the economic bubble in the US built around the AI subscription model.
All of this deepseek hype is overblown. Deepseek model was still trained on older american Nvidia GPUs.
Your confidence in this statement is hilarious the fact that it doesn’t help your argument at all. If anything, the fact they refined their model so well on older hardware is even more remarkable, and quite damning when OpenAI claims it needs literally cities worth of power and resources to train their models.
AI is overblown, tech is overblown. Capitalism itself is a senseless death cult based on the non-sensical idea that infinite growth is possible with a fragile, finite system.
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?
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”?
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?
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?
One Tera Newton? That’s a huge force!
Tech bros learn about diminishing returns challenge (impossible)
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.
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
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.
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.
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.
