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.
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.
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
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
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.
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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.
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
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.
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).