DeepSeek launched a free, open-source large language model in late December, claiming it was developed in just two months at a cost of under $6 million.
That’s generally how tech goes though. You throw hardware at the problem until it works, and then you optimize it to run on laptops and eventually phones. Usually hardware improvements and software optimizations meet somewhere in the middle.
Look at photo and video editing, you used to need a workstation for that, and now you can get most of it on your phone. Surely AI is destined to follow the same path, with local models getting more and more robust until eventually the beefy cloud services are no longer required.
The problem for American tech companies is that they didn’t even try to move to stage 2.
OpenAI is hemorrhaging money even on their most expensive subscription and their entire business plan was to hemorrhage money even faster to the point they would use entire power stations to power their data centers. Their plan makes about as much sense as digging your self out of a hole by trying to dig to the other side of the globe.
Hey, my friends and I would’ve made it to China if recess was a bit longer.
Seriously though, the goal for something like OpenAI shouldn’t be to sell products to end customers, but to license models to companies that sell “solutions.” I see these direct to consumer devices similarly to how GPU manufacturers see reference cards or how Valve sees the Steam Deck: they’re a proof of concept for others to follow.
OpenAI should be looking to be more like ARM and less like Apple. If they do that, they might just grow into their valuation.
China really has nothing to do with it, it could have been anyone. It’s a reaction to realizing that GPT4-equivalent AI models are dramatically cheaper to train than previously thought.
It being China is a noteable detail because it really drives the nail in the coffin for NVIDIA, since China has been fenced off from having access to NVIDIA’s most expensive AI GPUs that were thought to be required to pull this off.
It also makes the USA gov look extremely foolish to have made major foreign policy and relationship sacrifices in order to try to delay China by a few years, when it’s January and China has already caught up, those sacrifices did not pay off, in fact they backfired and have benefited China and will allow them to accelerate while hurting USA tech/AI companies
I don’t think this is the primary reason behind Nvidia’s drop. Because as long as they got a massive technological lead it doesn’t matter as much to them who has the best model, as long as these companies use their GPUs to train them.
The real change is that the compute resources (which is Nvidia’s product) needed to create a great model suddenly fell of a cliff. Whereas until now the name of the game was that more is better and scale is everything.
China vs the West (or upstart vs big players) matters to those who are investing in creating those models. So for example Meta, who presumably spends a ton of money on high paying engineers and data centers, and somehow got upstaged by someone else with a fraction of their resources.
Looking at the market cap of Nvidia vs their competitors the market belives it is, considering they just lost more than AMD/Intel and the likes are worth combined and still are valued at $2.9 billion.
And with technology i mean both the performance of their hardware and the software stack they’ve created, which is a big part of their dominance.
Yeah. I don’t believe market value is a great indicator in this case. In general, I would say that capital markets are rational at a macro level, but not micro. This is all speculation/gambling.
My guess is that AMD and Intel are at most 1 year behind Nvidia when it comes to tech stack. “China”, maybe 2 years, probably less.
However, if you can make chips with 80% performance at 10% price, its a win. People can continue to tell themselves that big tech always will buy the latest and greatest whatever the cost. It does not make it true. I mean, it hasn’t been true for a really long time. Google, Meta and Amazon already make their own chips. That’s probably true for DeepSeek as well.
From what I understand, it’s more that it takes a lot less money to train your own llms with the same powers with this one than to pay license to one of the expensive ones. Somebody correct me if I’m wrong
I wouldn’t be surprised if China spent more on AI development than the west did, sure here we spent tens of billions while China only invested a few million but that few million was actually spent on the development while out of the tens of billions all but 5$ was spent on bonuses and yachts.
Exactly. Galaxy brains on Wall Street realizing that nvidia’s monopoly pricing power is coming to an end. This was inevitable - China has 4x as many workers as the US, trained in the best labs and best universities in the world, interns at the best companies, then, because of racism, sent back to China. Blocking sales of nvidia chips to China drives them to develop their own hardware, rather than getting them hooked on Western hardware. China’s AI may not be as efficient or as good as the West right now, but it will be cheaper, and it will get better.
It’s coming, Pelosi sold her shares like a month ago.
It’s going to crash, if not for the reasons she sold for, as more and more people hear she sold, they’re going to sell because they’ll assume she has insider knowledge due to her office.
Which is why politicians (and spouses) shouldn’t be able to directly invest into individual companies.
Even if they aren’t doing anything wrong, people will follow them and do what they do. Only a truly ignorant person would believe it doesn’t have an effect on other people.
They’re giving up on improving rasterazation and focusing on “ai cores” because they’re using gpus to pay for the research into AI.
“Real” core count is going down on the 5000 series.
It’s not what gamers want, but they’re counting on people just buying the newest before asking if newer is really better. It’s why they’re already cutting 4000 series production, they just won’t give people the option.
I think everything under 4070 super is already discontinued
You joke but there’s a lot of grandma/grandpa gamers these days. Remember someone who played PC games back in the 80s would be on their 50s or 60s now. Or even older if they picked up the hobby as an adult in the 80s
Prices rarely, if ever, go down and there is a push across the board to offload things “to the cloud” for a range of reasons.
That said: If your focus is on gaming, AMD is REAL good these days and, if you can get past their completely nonsensical naming scheme, you can often get a really good GPU using “last year’s” technology for 500-800 USD (discounted to 400-600 or so).
Something is got to give. You can’t spend ~$200 billion annually on capex and get a mere $2-3 billion return on this investment.
I understand that they are searching for a radical breakthrough “that will change everything”, but there is also reasons to be skeptical about this (e.g. documents revealing that Microsoft and OpenAI defined AGI as something that can get them $100 billion in annual revenue as opposed to some specific capabilities).
I really hope this is the beginning of a massive correction on AI hype.
It’s a reaction to thinking China has better AI, not thinking AI has less value.
Or from the sounds of it, doing things more efficiently.
Fewer cycles required, less hardware required.
Maybe this was an inevitability, if you cut off access to the fast hardware, you create a natural advantage for more efficient systems.
That’s generally how tech goes though. You throw hardware at the problem until it works, and then you optimize it to run on laptops and eventually phones. Usually hardware improvements and software optimizations meet somewhere in the middle.
Look at photo and video editing, you used to need a workstation for that, and now you can get most of it on your phone. Surely AI is destined to follow the same path, with local models getting more and more robust until eventually the beefy cloud services are no longer required.
The problem for American tech companies is that they didn’t even try to move to stage 2.
OpenAI is hemorrhaging money even on their most expensive subscription and their entire business plan was to hemorrhage money even faster to the point they would use entire power stations to power their data centers. Their plan makes about as much sense as digging your self out of a hole by trying to dig to the other side of the globe.
Hey, my friends and I would’ve made it to China if recess was a bit longer.
Seriously though, the goal for something like OpenAI shouldn’t be to sell products to end customers, but to license models to companies that sell “solutions.” I see these direct to consumer devices similarly to how GPU manufacturers see reference cards or how Valve sees the Steam Deck: they’re a proof of concept for others to follow.
OpenAI should be looking to be more like ARM and less like Apple. If they do that, they might just grow into their valuation.
China really has nothing to do with it, it could have been anyone. It’s a reaction to realizing that GPT4-equivalent AI models are dramatically cheaper to train than previously thought.
It being China is a noteable detail because it really drives the nail in the coffin for NVIDIA, since China has been fenced off from having access to NVIDIA’s most expensive AI GPUs that were thought to be required to pull this off.
It also makes the USA gov look extremely foolish to have made major foreign policy and relationship sacrifices in order to try to delay China by a few years, when it’s January and China has already caught up, those sacrifices did not pay off, in fact they backfired and have benefited China and will allow them to accelerate while hurting USA tech/AI companies
Oh US has been doing this kind of thing for decades! This isn’t new.
I don’t think this is the primary reason behind Nvidia’s drop. Because as long as they got a massive technological lead it doesn’t matter as much to them who has the best model, as long as these companies use their GPUs to train them.
The real change is that the compute resources (which is Nvidia’s product) needed to create a great model suddenly fell of a cliff. Whereas until now the name of the game was that more is better and scale is everything.
China vs the West (or upstart vs big players) matters to those who are investing in creating those models. So for example Meta, who presumably spends a ton of money on high paying engineers and data centers, and somehow got upstaged by someone else with a fraction of their resources.
…in a cave with Chinese knockoffs!
I really don’t believe the technological lead is massive.
Looking at the market cap of Nvidia vs their competitors the market belives it is, considering they just lost more than AMD/Intel and the likes are worth combined and still are valued at $2.9 billion.
And with technology i mean both the performance of their hardware and the software stack they’ve created, which is a big part of their dominance.
Yeah. I don’t believe market value is a great indicator in this case. In general, I would say that capital markets are rational at a macro level, but not micro. This is all speculation/gambling.
My guess is that AMD and Intel are at most 1 year behind Nvidia when it comes to tech stack. “China”, maybe 2 years, probably less.
However, if you can make chips with 80% performance at 10% price, its a win. People can continue to tell themselves that big tech always will buy the latest and greatest whatever the cost. It does not make it true. I mean, it hasn’t been true for a really long time. Google, Meta and Amazon already make their own chips. That’s probably true for DeepSeek as well.
From what I understand, it’s more that it takes a lot less money to train your own llms with the same powers with this one than to pay license to one of the expensive ones. Somebody correct me if I’m wrong
It’s about cheap Chinese AI
I wouldn’t be surprised if China spent more on AI development than the west did, sure here we spent tens of billions while China only invested a few million but that few million was actually spent on the development while out of the tens of billions all but 5$ was spent on bonuses and yachts.
Does it still need people spending huge amounts of time to train models?
After doing neural networks, fuzzy logic, etc. in university, I really question the whole usability of what is called “AI” outside niche use cases.
Ah, see, the mistake you’re making is actually understanding the topic at hand.
😂
If inputText = "hello" then Respond.text("hello there") ElseIf inputText (...) ```Exactly. Galaxy brains on Wall Street realizing that nvidia’s monopoly pricing power is coming to an end. This was inevitable - China has 4x as many workers as the US, trained in the best labs and best universities in the world, interns at the best companies, then, because of racism, sent back to China. Blocking sales of nvidia chips to China drives them to develop their own hardware, rather than getting them hooked on Western hardware. China’s AI may not be as efficient or as good as the West right now, but it will be cheaper, and it will get better.
It’s coming, Pelosi sold her shares like a month ago.
It’s going to crash, if not for the reasons she sold for, as more and more people hear she sold, they’re going to sell because they’ll assume she has insider knowledge due to her office.
Which is why politicians (and spouses) shouldn’t be able to directly invest into individual companies.
Even if they aren’t doing anything wrong, people will follow them and do what they do. Only a truly ignorant person would believe it doesn’t have an effect on other people.
Yeah but only cause she was really disappointed with the 5000 series lineup. Can you blame her for wanting real rasterization improvements?
Everyone’s disappointed with the 5000 series…
They’re giving up on improving rasterazation and focusing on “ai cores” because they’re using gpus to pay for the research into AI.
“Real” core count is going down on the 5000 series.
It’s not what gamers want, but they’re counting on people just buying the newest before asking if newer is really better. It’s why they’re already cutting 4000 series production, they just won’t give people the option.
I think everything under 4070 super is already discontinued
xx_Pelosi420_xx doesn’t settle for incremental upgrades
Pelosi says AI frames are fake frames.
You joke but there’s a lot of grandma/grandpa gamers these days. Remember someone who played PC games back in the 80s would be on their 50s or 60s now. Or even older if they picked up the hobby as an adult in the 80s
I just hope it means I can get a high end GPU for less than a grand one day.
Prices rarely, if ever, go down and there is a push across the board to offload things “to the cloud” for a range of reasons.
That said: If your focus is on gaming, AMD is REAL good these days and, if you can get past their completely nonsensical naming scheme, you can often get a really good GPU using “last year’s” technology for 500-800 USD (discounted to 400-600 or so).
They definitely used to go down, just not since Bitcoin morphed into a speculative mania.
I’m using an Rx6700xt which you can get for about £300 and it works fine.
Edit: try using ollama on your PC. If your CPU is capable, that software should work out the rest.
Hope and cope
If anything, this will accelerate the AI hype, as big leaps forward have been made without increased resource usage.
Something is got to give. You can’t spend ~$200 billion annually on capex and get a mere $2-3 billion return on this investment.
I understand that they are searching for a radical breakthrough “that will change everything”, but there is also reasons to be skeptical about this (e.g. documents revealing that Microsoft and OpenAI defined AGI as something that can get them $100 billion in annual revenue as opposed to some specific capabilities).