Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Nvidia Stock Crash Prediction

entropicthoughts.com

Post reply on HN
Print view View original

261–270 of 385 posts

Re: Nvidia Stock Crash Prediction

#261

Post by jiggawatts »

alfalfasprout wrote: post #145
cortesoft wrote: post #140

Earlier quoted context omitted.

> The problem I have with this argument is that it's simply unsustainable to be spending that much every 2-3 years Isn’t this entirely dependent on the economic value of the AI workloads? It all depends on whether AI work is more valuable than that cost. I can easily see arguments why it won’t be that valuable, but if it is, then that cost will be sustainable.

100% this. all of this spending is predicated on a stratospheric ROI on AI investments at the proposed investment levels. If that doesn't pan out, we'll see a lot of people left holding the cards including chip fabs, designers like Nvidia, and of course anyone that ponied up for that much compute.

Chip fabs will be fine. The demand for high end processors will remain because of the likes of Apple and AMD.

Re: Nvidia Stock Crash Prediction

#262

Post by pvab3 »

unsupp0rted wrote: post #236
iLoveOncall wrote: post #160

Earlier quoted context omitted.

> short of major algorithmic breakthroughs I am not convinced the global demand for GPUs will drop any time soon Or, you know, when LLMs don't pay off.

Even if LLMs didn't advance at all from this point onward, there's still loads of productive work that could be optimized / fully automated by them, at no worse output quality than the low-skilled humans we're currently throwing at that work.

inference requires a fraction of the power that training does. According to the Villalobos paper, the median date is 2028. At some point we won't be training bigger and bigger models every month. We will run out of additional material to train on, things will continue commodifying, and then the amount of training happening will significantly decrease unless new avenues open for new types of models. But our current LLMs are much more compute-intensive than any other type of generative or task-specific model

Re: Nvidia Stock Crash Prediction

#264

Post by WalterBright »

_fat_santa wrote: post #11

This article goes more into the technical analysis of the stock rather than the underlying business fundamentals that would lead to a stock dump. My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Right now Nvidia is flying high because datacenters are breaking ground everywhere but eventually that will come to an end as the supply of compute goes up. The counterargument to th…

> technical analysis of the stock

AKA pictures in clouds

Re: Nvidia Stock Crash Prediction

#265

Post by bigyabai »

matthewdgreen wrote: post #258
bigyabai wrote: post #255

Earlier quoted context omitted.

> Nvidia’s valuation is based on the current trend continuing People said this back when Folding@Home was dominated by Team Green years ago. Then again when GPUs sold out for the cryptocurrency boom, and now again that Nvidia is addressing the LLM demand. Nvidia's valuation is backstopped by the fact that Russia, Ukraine, China and the United States are all tripping over themselves for the chance to deploy it operati…

China is restricting purchases of H200s. The strong likelihood is that they're doing this to promote their own domestic competitors. It may take a few years for those chips to catch up and enter full production, but it's hard to envision any "trillion dollar" Nvidia defense empire once that happens.

It's very easy to envision. America needs chips, and Intel can't do most of this stuff.

Re: Nvidia Stock Crash Prediction

#266

Post by bluGill »

Melatonic wrote: post #199
belval wrote: post #172

Earlier quoted context omitted.

Miners usually don't overclock though. If anything underclocking is the best way to improve your ROI because it significantly reduces the power consumption while retaining most of the hashrate.

Exactly - more specifically undervolting. You want the minimum volts going to the card with it still performing decently. Even in amateur setups the amount of power used is a huge factor (because of the huge draw from the cards themselves and AC units to cool the room) so minimising heat is key. From what I remember most cards (even CPUs as well) hit peak efficiency when undervolted and hitting somewhere around 70-80…

The only amatures I know doing this are trying to heat their garrage for free. so long as the heat gain is paid for they can afford to heat an otherwise unheated building.

Re: Nvidia Stock Crash Prediction

#267

Post by zozbot234 »

pvab3 wrote: post #262
unsupp0rted wrote: post #236

Earlier quoted context omitted.

Even if LLMs didn't advance at all from this point onward, there's still loads of productive work that could be optimized / fully automated by them, at no worse output quality than the low-skilled humans we're currently throwing at that work.

inference requires a fraction of the power that training does. According to the Villalobos paper, the median date is 2028. At some point we won't be training bigger and bigger models every month. We will run out of additional material to train on, things will continue commodifying, and then the amount of training happening will significantly decrease unless new avenues open for new types of models. But our current LL…

> We will run out of additional material to train on

This sounds a bit silly. More training will generally result in better modeling, even for a fixed amount of genuine original data. At current model sizes, it's essentially impossible to overfit to the training data so there's no reason why we should just "stop".

Re: Nvidia Stock Crash Prediction

#268

Post by reppap »

agentcoops wrote: post #128
_fat_santa wrote: post #11

This article goes more into the technical analysis of the stock rather than the underlying business fundamentals that would lead to a stock dump. My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Right now Nvidia is flying high because datacenters are breaking ground everywhere but eventually that will come to an end as the supply of compute goes up. The counterargument to th…

I hear your argument, but short of major algorithmic breakthroughs I am not convinced the global demand for GPUs will drop any time soon. Of course I could easily be wrong, but regardless I think the most predictable cause for a drop in the NVIDIA price would be that the CHIPS act/recent decisions by the CCP leads a Chinese firm to bring to market a CUDA compatible and reliable GPU at a fraction of the cost. It shoul…

People will want more GPUs but will they be able to fund them? At what points does the venture capital and loans run out? People will not keep pouring hundreds of billions into this if the returns don't start coming.

Re: Nvidia Stock Crash Prediction

#269

Post by galaxyLogic »

SchemaLoad wrote: post #246
zozbot234 wrote: post #106

Earlier quoted context omitted.

If the AI hasn't specifically learned about SeqTracks as part of its training it's not going to give you useful answers. AI is not a crystal ball.

The problem is it's inability to say "I don't know". As soon as you reach the limits of the models knowledge it will readily start fabricating answers.

Both true. Perplexity knows a lot about SeqTrack, I assume it has read the UserGuide. But some things it gets wrong, seems especially things it should understand by looking at the pictures.

I'm just wondering if there's a clear path for it to improve and on what time-table. The fact that it does not tell you when it is "unsure" of course makes things worse for users. (It is never unsure).

Re: Nvidia Stock Crash Prediction

#270

Post by WalterBright »

Yizahi wrote: post #130
Melatonic wrote: post #90

Earlier quoted context omitted.

It's the opposite actually - most GPU used for mining are run at a consistent temp and load which is good for long term wear. Peaky loads where the GPU goes from cold to hot and back leads to more degradation because of changes in thermal expansion. This has been known for some time now.

That is commonly repeated idea, but it doesn't take into account countless token farms which are smaller than a datacenter. Basically anything from a single MB with 8 cards to a small shed with rigs, all of which tend to disregard common engineering practices and run hardware into a ground to maximize output until next police raid or difficulty bump. Plenty of photos in the internet of crappy rigs like that, and no o…

Why would police raid a shed housing a compute center?
Post reply on HN