It’s coming, Pelosi sold her shares like a month ago.

Yeah but only cause she was really disappointed with the 5000 series lineup. Can you blame her for wanting real rasterization improvements?

Hope and cope

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).

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.

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.

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.

It’s a reaction to thinking China has better AI

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

It’s about cheap Chinese AI

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

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.

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).

Nvidia cards were the only GPUs used to train DeepSeek v3 and R1. So, that narrative still superficially holds. Other stocks like TSMC, ASML, and AMD are also down in pre-market.

Quick, wedge crypto in there somehow! That should buy us at least two more rounds of investment.

I don’t know. In a lot of usecase AI is kinda crap, but there’s certain usecase where it’s really good. Honestly I don’t think people are giving enough thought to it’s utility in early-middle stages of creative works where an img2img model can take the basic composition from the artist, render it then the artist can go in and modify and perfect it for the final product. Also video games that use generative AI are going to be insane in about 10-15 years. Imagine an open world game where it generates building interiors and NPCs as you interact with them, even tying the stuff the NPCs say into the buildings they’re in, like an old sailer living in a house with lots of pictures of boats and boat models, or the warrior having tons of books about battle and decorative weapons everywhere all in throw away structures that would have previously been closed set dressing. Maybe they’ll even find sane ways to create quests on the fly that don’t feel overly cookie-cutter? Life changing? Of course not, but definitely a cool technology with a lot of potential

Also realistically I don’t think there’s going to be long term use for AI models that need a quarter of a datacenter just to run, and they’ll all get tuned down to what can run directly on a phone efficiently. Maybe we’ll see some new accelerators become common place maybe we won’t.

Sure but you had the .com bubble but it was still useful. Same as AI in a big bubble right now doesn’t mean it won’t be useful.

Lots of techies loved the internet, built it, and were all early adopters. Lots of normies didn’t see the point.

With AI it’s pretty much the other way around: CEOs saying “we don’t need programmers, any more”, while people who understand the tech roll their eyes.