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Nvidia’s $589B DeepSeek rout

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Re: Nvidia’s $589B DeepSeek rout

#771

Post by milkshakes »

ponty_rick wrote: post #665
cageface wrote: post #590

Earlier quoted context omitted.

You could even say that overconfidence in abilities and knowledge outside of core expertise is the critical flaw of today's entire tech industry.

With the crowdstrike outage earlier last year it was incredible how many hidden security and kernel "experts" came out crawling from the woodwork, questioning why anything needs to run in the kernel and predicting the company's demise.

the experts were correct. in 2024 there are now OS APIs that provide the same observability and control with much less risk involved.

Re: Nvidia’s $589B DeepSeek rout

#772

Post by jes5199 »

yo-cuddles wrote: post #448
Sol- wrote: post #54

I find it interesting because the DeepSeek stuff, while very cool, doesn't seem invalidate that more compute wouldn't translate to even _higher_ capabilities? It's amazing what they did with a limited budget, but instead of the takeaway being "we don't need that much compute to achieve X", it could also be, "These new results show that we can achieve even 1000*X with our currently planned compute buildout" But perhap…

Probably not. If the price of Nvidia is dropping, it's because investors see a world where Nvidia hardware is less valuable, probably because it will be used less. You can't do the distill/magnify cycle like you do with alphago. LLM models have basically stalled in their base capabilities, pre training is basically over at this point, so the news arms race will be over marginal capability gains and (mostly) making th…

> You can't do the distill/magnify cycle like you do with alphago

are you sure? people are saying that there’s an analogous cycle where you use o1-style reasoning to produce better inputs to the next training round

Re: Nvidia’s $589B DeepSeek rout

#773

Post by jes5199 »

msoad wrote: post #701
qqtt wrote: post #634

Earlier quoted context omitted.

Well you have to keep in mind that Nvidia has a 3 trillion dollar valuation. That kind of heavy valuation comes with heavy expectations about future growth. Some of those assumptions about future Nvidia growth are their ability to maintain their heavy growth rates, for very far into the future. Training is a huge component of Nvidia's projected growth. Inference is actually much more competitive, but training is almo…

My layman view is that more compute (more reasoning) will not solve harder problems. I'm using those models every day and when problem hits a certain complexity it will fail, no matter how much it "reasons"

I had a similar intuition for a long time, but I’ve watched the threshold of “certain complexity” move, and I’m no longer convinced that I know when it’s going to stop

Re: Nvidia’s $589B DeepSeek rout

#774

Post by jes5199 »

medion wrote: post #699
ozten wrote: post #431

NVIDIA sells shovels to the gold rush. One miner (Liang Wenfeng), who has previously purchased at least 10,000 A100 shovels... has a "side project" where they figured out how to dig really well with a shovel and shared their secrets. The gold rush, wether real or a bubble is still there! NVIDA will still sell every shovel they can manufacture, as soon as it is available in inventory. Fortune 100 companies will still…

Can anyone comment on why Wenfeng shared his secret sauce? Other than publicity, there only seems to be downsides for him, as now everyone else with larger compute will just copy and improve?

pure prestige play, I think

Re: Nvidia’s $589B DeepSeek rout

#775

Post by rx_tx »

zeven7 wrote: post #695
plaidfuji wrote: post #640

Here’s a take I haven’t seen yet: If training and inference just got 40x more efficient, but OpenAI and co. still have the same compute resources, once they’ve baked in all the DeepSeek improvements, we’re about to find out very quickly whether 40x the compute delivers 40x the performance / output quality, or if output quality has ceased to be compute-bound.

I've missed the stories on this until now. Is it known (and is there an ELI5) how they were able to do it so much more efficiently?

This article has good background, context, and explanations [1] They skipped CUDA and instead used PTX which is a lower level instruction set where they were able to implement more performant cross-chip comms to make up for the less-performant H800 chips.

[1]: https://stratechery.com/2025/deepseek-faq/

Re: Nvidia’s $589B DeepSeek rout

#776

Post by beefnugs »

culi wrote: post #462
linkregister wrote: post #408

Earlier quoted context omitted.

> the Chinese Daya Guo, Dejian Yang, Haowei Zhang, et.al., quant researchers at High Flyer, a hedge fund based in China, open-sourced their work on a chain-of-thought reasoning model, based on Qwen and LLama (open source LLMs). It would be somewhat bizarre to describe Meta's open sourcing of LLama as "the Americans gifting a model", despite Meta having a corporate headquarters in the United States.

Thank you. The amount of casual sinophobia allowed on hackernews has been a real turn off. I find myself avoiding threads like these in anticipation of these comments

Nah, its about the "party" not the people or culture. They will never shake the stigma now that they fist their way into controlling any company, creating artificial market manipulation, restricting technology, restricting information, violence and threats against their own people and everyone else.

Re: Nvidia’s $589B DeepSeek rout

#777

Post by michaelscott »

vishnugupta wrote: post #753
aurareturn wrote: post #608

Earlier quoted context omitted.

I think you’re wrong and Wallstreet got Deepseek’s impact wrong. You say DeepSeek should decrease Nvidia demand. Wallstreet agreed today. I say DeepSeek should increase Nvidia’s demand due to Jevon’s Paradox.

> DeepSeek should increase Nvidia’s demand due to Jevon’s Paradox. How exactly? From what I’ve read the full model can run on MacBook M1 sort of hardware just fine. And this is their first release, I’d expect it to get more efficient and maybe domain specific models can be run on much lower grade hardware sort of raspberry pi sort.

Only the distilled models can run on everyday machines, not the full model

Re: Nvidia’s $589B DeepSeek rout

#778

Post by plussed_reader »

CursedSilicon wrote: post #767
riffraff wrote: post #698

Earlier quoted context omitted.

IIUC they released a paper, it's partially algorithmic improvements partially good old low level optimization.

There's something to be said about the idea that instead of just dumping oceans of money into buying Nvidia cards they just...optimized what they had I'd say the wider industry could learn a thing or two, but as other commentors have joked. The line must go up

The double edged sword of export controls.

Re: Nvidia’s $589B DeepSeek rout

#779

Post by rl3 »

roenxi wrote: post #704
haliskerbas wrote: post #670

Earlier quoted context omitted.

But every successful SV founder and or VC is not only a tech genius but also a geopolitical and socioeconomic expert! That’s why they make war companies, cozy up to politicians, and talk about how woke is ruining the world. /s

In fairness, 'geopolitical experts' may not really exist. There are a range of people who make up interesting stories to a greater or lesser extent but all seem to be serially misinformed. Some things are too complicated to have expertise in. Indeed, while the existence of socioeconomic experts seems more likely we don't have any way of reliably identifying them. The people who actually end up making social or econom…

>In fairness, 'geopolitical experts' may not really exist.

Except for, I don't know, the many thousands of people who work at various government agencies (diplomatic, intelligence) or even private sector policy circles whose job it is to literally be geopolitical experts in a given area.

Re: Nvidia’s $589B DeepSeek rout

#780

Post by rightbyte »

culi wrote: post #462
linkregister wrote: post #408

Earlier quoted context omitted.

> the Chinese Daya Guo, Dejian Yang, Haowei Zhang, et.al., quant researchers at High Flyer, a hedge fund based in China, open-sourced their work on a chain-of-thought reasoning model, based on Qwen and LLama (open source LLMs). It would be somewhat bizarre to describe Meta's open sourcing of LLama as "the Americans gifting a model", despite Meta having a corporate headquarters in the United States.

Thank you. The amount of casual sinophobia allowed on hackernews has been a real turn off. I find myself avoiding threads like these in anticipation of these comments

Jingoism seems like something that was always lurking beneath the surface waiting to emerge.
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