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Nvidia’s $589B DeepSeek rout

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Re: Nvidia’s $589B DeepSeek rout

#721

Post by SOLAR_FIELDS »

deadbabe wrote: post #628
Aloisius wrote: post #621

Earlier quoted context omitted.

> Jevon’s Paradox I've now seen this referenced two dozen times today which is well up from the 0 times I've seen it over the past year. Is there some recent article referencing it that everyone is regurgitating?

Most people know Jevon’s Paradox there is just rarely an opportunity to bring it up, similar to Poe’s Law.

I never knew there was an actual term for this, but I knew of the concept in my professional work because this situation often plays out when the government widens roads here in the States. Ostensibly the road widening is intended to lower congestion, but instead it often just causes more people to live there and use it, thereby increasing congestion.

Probably a decent amount of professions have some variation of this, so it probably is accurate to say most people know OF Jevon’s Paradox because it’s pretty easy to dig up examples of it. But probably much fewer know it’s actual name, or even that it has a name

Re: Nvidia’s $589B DeepSeek rout

#722

Post by dumpsterdiver »

aurareturn wrote: post #608
eigenvalue wrote: post #567

90% of the comments in this thread make it clear that knowing about technology does not in any way qualify someone to think correctly about markets and equity valuations.

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.

I’m also baffled by the reaction. Even with the ability to do more with less, the nature of the race still encourages everyone to do more with more.

Re: Nvidia’s $589B DeepSeek rout

#723

Post by divbzero »

gniv wrote: post #711
divbzero wrote: post #709

Greater efficiency of light bulbs has led to more light bulb use, not less. More efficient training of LLMs could just as likely lead to more chip use, not less.

But did it not lead to net less electricity used for lighting?

With more efficiency offset by more light bulbs, electricity used for lighting has been roughly flat since 2010: https://www.iea.org/data-and-statistics/charts/global-electr...

(For LLMs I wish that efficiency could lead to less electricity used for chips, but I think the best we can hope for is for electricity use to flatten out.)

Re: Nvidia’s $589B DeepSeek rout

#724

Post by johnfn »

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 think this is fairly easily debunked by o1, which is basically just 4o in a thinking for loop, and performs better on difficult tasks. Not a LOT better, mind you, but better enough to be measurable.

Re: Nvidia’s $589B DeepSeek rout

#725

Post by benzible »

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…

So, you think the system is genuinely trying to identify expertise to achieve equitable outcomes, and just happening to fail at it? Rather than policy being shaped by personal networks and existing power structures that tend to benefit themselves?

Re: Nvidia’s $589B DeepSeek rout

#726

Post by Jlagreen »

optimiz3 wrote: post #697
snake_doc wrote: post #669

Earlier quoted context omitted.

The other way is certainly also true. Your short piece is rational, but lacks insight into the inference and training dynamics of ML adoption unconstrained. The rate of ML progress is spectacularly compute constrained today. Every step in today’s scaling program is setup to de-risked the next scale up, because the opportunity cost of compute is so high. If the opportunity cost of compute is not so high, you can skip…

Everyone can say things that sound smart. When it comes to markets the only thing that matters is if your portfolio was green or red.

My entry into Nvidia is 2016, my portfolio has never been red since then.

Re: Nvidia’s $589B DeepSeek rout

#727

Post by jstummbillig »

gniv wrote: post #711
divbzero wrote: post #709

Greater efficiency of light bulbs has led to more light bulb use, not less. More efficient training of LLMs could just as likely lead to more chip use, not less.

But did it not lead to net less electricity used for lighting?

Maybe, at some point.

From what I can tell there's are mostly two options: Either AI is and will be useless or it's severely undersupplied. People, even those deeply technical, where AI has the most impact right now, still widely argue about if AI even offers any value. Adoption is far from anything that is plausible, if (not when) it became clear that it does.

If you land on "does not", given the investments so far, commercial entities would obviously be overvalued already and any investment goes to 0 over time.

But if we land on "does", how could Nvidia not be anything other than undervalued right now? No matter what frontier model: I can look at my screen, LLM generated characters visibly appearing in chunks, depending on the model after initially waiting for 10-20 seconds, for even benign queries — because that is the best we can do right now. And that's while most people still argue if AI will actually do anything and humanity at large does not really use it, neither personally nor societally.

If AI does in fact do something valuable and that something gets better, everyone will want it and there will be demand for lots of chips.

Re: Nvidia’s $589B DeepSeek rout

#728

Post by johnfn »

jcgrillo wrote: post #522
elihu wrote: post #450

Earlier quoted context omitted.

Jevon's paradox would imply that there's good reason to think that demand for shovels will increase. AI doesn't seem to be one of those things where society as a whole will say, "we have enough of that; we don't need any more". (Many individual people are already saying that, but they aren't the people buying the GPUs for this in the first place. Steam engines weren't universally popular either when they were introdu…

> AI doesn't seem to be one of those things where society as a whole will say, "we have enough of that; we don't need any more". Really? Has anyone made a useful, commercially successful product with it yet?

Cursor?

Re: Nvidia’s $589B DeepSeek rout

#729

Post by nyrikki »

dylan604 wrote: post #687
01100011 wrote: post #683

Earlier quoted context omitted.

> Can you guess what the next step will be? He fixes the cable? But seriously, video encoding isn't AI. Video encoding is a well understood problem. We can't even make "AI" that doesn't hallucinate yet. We're not sure what architectures will be needed for progress in AI. I get that we're all drunk on our analogies in the vacuum of our ignorance but we need to have a bit of humility and awareness of where we're at.

Conversely, can you name one computing thing that used to be hard when it was first created that is still hard in the same way today after generations of software/hardware improvements?

The Entscheidungsproblem, from the 17th century to today and forever in the future.

Re: Nvidia’s $589B DeepSeek rout

#730

Post by Ekaros »

deeviant wrote: post #569
addicted wrote: post #561

Earlier quoted context omitted.

What you are missing is that it turns out the gold isn’t actually gold. It’s bronze. So earliest, the shovelers were willing to spend thousands of dollars for a single shovel because they were expecting to get much more valuable gold out the other end. But now that it’s only bronze, they can’t spend that much money on their tools anymore to make their venture profitable. A lot of shovelers are gonna drop out of the r…

Wait, so AI might become 25x cheaper to train and run, and your thesis is... no one will make money on AI now?!?!

Many discussed aspects are disconnected. Cost of training, cost of hardware(and margin there), cost of operation, possible use cases, and then finally demand.

Cheaper training still expect there is some use case for those trained models. There might or might not be. It can very well be that cost of training did not really limit the number of usable models.

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