[xyst]

Because their stock value is highly coupled with crypto mining and AI craze.

The move from PoW to PoS for most crypto networks in combination with bust of ‘22. NVDA slid down in value.

OpenAI debuts ChatGPT in late 2022 and now it’s suddenly bumping in price as the hype and rush for GPUs from companies of all types buys up their stock of GPUs. Demand is far outpacing the supply. Nvda can’t keep up.

Thus, share price is brittle. Competition in the GPU market is dominantly owned by Nvidia. That can change, but so far openai loves using nvidia for some reason.

[ryandrake]

If you are a true believer that AI is not a craze, then the stock can only go up from here. If you think there is a chance that everyone gets bored of AI and moves on to some other fad that is not in Nvidia’s wheelhouse, then it’s probably down from here. I’m staying out of this bet: don’t have the stomach for it.

[throw0101b]

> If you think there is a chance that everyone gets bored of AI and moves on to some other fad that is not in Nvidia’s wheelhouse, then it’s probably down from here.

You may wish to look at history to see how things can work out: Cisco had a P/E ratio of 148 in 1999:

* https://www.dividendgrowthinvestor.com/2022/09/cisco-systems...

The share price tanked, but that does not mean that people got bored of the Internet and the need for routers and switches. QCOM had a P/E of 166: did people decide that mobile communications was a fad?

The connection between technological revolutions and financial bubbles dates back to (at least) Canal Mania:

* https://en.wikipedia.org/wiki/Canal_Mania

* https://en.wikipedia.org/wiki/Technological_Revolutions_and_...

It is possible for both AI to be a big thing and for NVDA to drop.

[oblio]

Regarding bubbles:

https://en.m.wikipedia.org/wiki/South_Sea_Company

https://en.m.wikipedia.org/wiki/Tulip_mania

[throw0101b]

Neither of these were technologically based speculations.

> https://en.wikipedia.org/wiki/Tulip_mania

While widely used as an example, most of the well-known stories about this were actually made up, and it wasn't as bad as it is often made out to be.

Quinn and Turner, when they wrote about bubbles:

* https://www.goodreads.com/book/show/48989633-boom-and-bust

* https://old.reddit.com/r/AskHistorians/comments/i2wfsm/i_am_...

purposefully excluded it because their research found it wasn't actually a thing. (Though for the general public it can be an illustrative parable.)

[AlexandrB]

There's another case for pessimism as well: cost. It's possible that many AI applications aren't worth the money required for the extra compute. AI-enhanced search comes to mind here: how is Microsoft going to monetize users of Copilot in Bing to justify the extra cost? Right now a lot of this stuff is heavily subsidized by VCs or the MSFTs of the world, but when it comes time to make a profit we'll see what actually sticks around.

[_factor]

Better question: why does a simple search for “What color is a labrador retriever” require any compute time when the answer can be cached? This is a simple example, but 90% of my searches don’t require an llm to process a simple question.

[jazzyjackson]

One time I came across a git repo that let me download a gigabyte of prime numbers and I thought to myself, is that more or less efficient than me running a program locally to generate a gigabyte of prime numbers?

The compute for a direct answer like that is fractions of a penny, it might be better to create answers on the fly than store an index of every question anyone has asked (well, that's essentially what the weights are after all)

[_factor]

It’s in interesting question. I assume they’re using accelerators, and the alternative is a disk or memory hit. It still seems expensive to me.

https://www.linkedin.com/pulse/rising-cost-llm-based-search-...

[jacobr1]

This seems true as far as incentives go. But how much of that cost driver will be due to efficiencies driven by companies like NVIDIA? They seem well poised to benefit from a lot of the increased (non-hype) use of AI. Seems like we spent a decade or more of stalled CPU performance gains chasing better energy efficiency in the data center, same story could play out here.

[partiallypro]

AI is obviously the future, though current iterations will probably die at some point. but the dot com bubble ended up with the internet being more pervasive than may have even been thought of at the time, but regardless even the likes of Amazon's stock went bust before it recollected itself. Not a perfect comparison given Nvidia has really good revenue growth, but the point still stands.