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Nvidia's Risky Business

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Re: Nvidia's Risky Business

#171

Post by grey-area »

HDBaseT wrote: post #131
grey-area wrote: post #53

Earlier quoted context omitted.

Just for context, they make up 5% (yes 5%) of holdings in global index funds like VWRA. https://stockanalysis.com/quote/lon/VWRA/holdings/ That is an astounding figure and means markets are highly imbalanced, unless you think Nvidia represents 5% of the global economy.

There is a number of index funds holding 7.5% of NVIDIA. This consolidation is scary. I've started putting a little bit in emerging markets and China. I cannot trust the US long term, hopefully I'm wrong!

I see China as very risky due to Taiwan.

Re: Nvidia's Risky Business

#172

Post by TonyStr »

atom_arranger wrote: post #83
rcr-anti wrote: post #74

For awhile I've found two things hard to square, that the hardware and software making up current gen AI will bring us to a socioeconomic singularity, and the reality the thing they're mostly trying to emulate is a few pounds of meat and fat running on tens of watts equivalent. On one hand the current AIs are obviously super human in some tasks, get completely dunked on in others by far simpler organisms. My cat can…

Another interesting discrepancy is that people think current GPUs are maybe capable of running AGI but they still can barely manage photorealistic rendering of a single room in realtime, or simulate something like a shirt thrown into a pile of laundry. They can generate a video of it based on millions of existing videos, but not do a real simulation of light and physics in realtime.

Is the human brain capable of doing real simulations of light and physics in realtime? Or does it hallucinate the details and represent some low-resolution mental image? You may be overestimating the capabilities of flesh-based neural networks and underestimating the capabilities of silicon-based neural networks.

Re: Nvidia's Risky Business

#173

Post by bugglebeetle »

galaxyLogic wrote: post #161
bri3d wrote: post #152

Earlier quoted context omitted.

The CUDA runtime coming with a gazillion reasonably decent kernels (DNN, BLAS, CUTLASS) and a concurrency system (NCCL) is a big deal; especially in the “early days” very few researchers or development runtimes were even writing their own kernels or dealing with CUDA C++ extensively, they were wrapping the ones NVidia gave them. I do agree that it’s really not great, and I also have never been a strong believer in th…

What I don't quite get is why can't they use AI to translate CUDA programs into more open architectures like AMD ROCm? AI is supposed have solved the "coding problem". But shouldn't translating a program from one platform to another be an even easier, more mechanical, task for the AI?

Undoubtedly, the frontier labs are already doing something akin to this as part of their new chip design endeavors.

Re: Nvidia's Risky Business

#174

Post by polanyer »

ijidak wrote: post #121
YuechenLi wrote: post #68

Nvidia's biggest advantage in AI has never been only their hardware performance but how entrenched their software is in ML research that flowed down stream. However, if you've actually used CUDA C/C++, it's pretty one of the worst software development ecosystem imaginable: you get all the footgun of regular C++, plus GPU compute pretending to be C++ and but doesn't actually behave like C++ because CPU and GPU compute…

Genuine question. Given that LLMs are supposed to allow us to rewrite anything, and I am an LLM believer, what I don't understand is: how does CUDA continue to be a moat in a world where LLMs can rewrite entire software development stacks? If NVIDIA is right about AI, isn't this same technology going to erode the software side of this same software moat?

It seems like path dependent lock in to me and a risk/reward calculation.

What do you gain by not using CUDA vs what do you risk?

Re: Nvidia's Risky Business

#175

Post by larnon »

mdp2021 wrote: post #169
galaxyLogic wrote: post #161

Earlier quoted context omitted.

What I don't quite get is why can't they use AI to translate CUDA programs into more open architectures like AMD ROCm? AI is supposed have solved the "coding problem". But shouldn't translating a program from one platform to another be an even easier, more mechanical, task for the AI?

> AI is supposed have solved the Which AI? LLMs are coding facilitators and code producers. A problem is solved when the solution is reliable. Non-deterministic Neural Networks are not reliable. In fact, > more mechanical[] task that suggests an expectation of process and procedure, which is still not a capability of current architectures. Sure, you can ask a brains-deficient operator to perform a huge task, but then…

The tool itself (AI) may not be reliable, but that is also very true for every other tool (e.g. Human). Also, you are right about when a problem is solved, but this doesn't need the tool to be reliable as you said, just the solution part. Hence, as long as the produced code works as intended, it doesn't matter what you used to produce the output.

Re: Nvidia's Risky Business

#176

Post by atom_arranger »

TonyStr wrote: post #172
atom_arranger wrote: post #83

Earlier quoted context omitted.

Another interesting discrepancy is that people think current GPUs are maybe capable of running AGI but they still can barely manage photorealistic rendering of a single room in realtime, or simulate something like a shirt thrown into a pile of laundry. They can generate a video of it based on millions of existing videos, but not do a real simulation of light and physics in realtime.

Is the human brain capable of doing real simulations of light and physics in realtime? Or does it hallucinate the details and represent some low-resolution mental image? You may be overestimating the capabilities of flesh-based neural networks and underestimating the capabilities of silicon-based neural networks.

That's a good point. It's just kind of surprising, there's been a lot of incremental progress towards rendering and simulation for a long time. If you'd asked 10 years ago if we'd have AGI or realistic realtime rendering and physics of a single room first I think most people would have answered the former.

Re: Nvidia's Risky Business

#177

Post by 2OEH8eoCRo0 »

grey-area wrote: post #171
HDBaseT wrote: post #131

Earlier quoted context omitted.

There is a number of index funds holding 7.5% of NVIDIA. This consolidation is scary. I've started putting a little bit in emerging markets and China. I cannot trust the US long term, hopefully I'm wrong!

I see China as very risky due to Taiwan.

I see Nvidia as very risky due to their chips all being fabbed in Taiwan and Taiwan is risky due to China.

Re: Nvidia's Risky Business

#178

Post by alexpotato »

Back in during the dotcom boom, there were multiple examples of companies being bought for ridiculous amounts. Often as the result of a bidding war.

Even back then, some economists used the "hidden wallet auction" as an example of how this could happen.

To summarize:

- there is a wallet

- you don't know how much is in the wallet

- you bid on amount to buy the wallet

- if you get the highest bid you win

- crucially, if you lose then you still have to pay

This is often cited as a game that you do not want to play b/c it's a. hard to predict the upside, b. the downside is huge.

That being said, people still got into these auctions and because of sunk cost fallacy, decided to keep bidding even if they might lose.

The hyperscaler race feels a bit like the above but no one seems to ant to admit it.

Re: Nvidia's Risky Business

#179

Post by bri3d »

galaxyLogic wrote: post #161
bri3d wrote: post #152

Earlier quoted context omitted.

The CUDA runtime coming with a gazillion reasonably decent kernels (DNN, BLAS, CUTLASS) and a concurrency system (NCCL) is a big deal; especially in the “early days” very few researchers or development runtimes were even writing their own kernels or dealing with CUDA C++ extensively, they were wrapping the ones NVidia gave them. I do agree that it’s really not great, and I also have never been a strong believer in th…

What I don't quite get is why can't they use AI to translate CUDA programs into more open architectures like AMD ROCm? AI is supposed have solved the "coding problem". But shouldn't translating a program from one platform to another be an even easier, more mechanical, task for the AI?

No, because the two platforms often don't share the same underlying kernels; this has been one of the main issues and complaints with ROCm/MIOpen since the start, although they are catching up slowly.

This is actually a corollary to the point I was making about "CUDA" usually also including a ton of the included kernels and not just referring to a crappy programming environment; translating mid-level C that does math between two runtimes wouldn't be hard for an LLM, but translating "doBigDNNThingNVidiaGaveMeInAKernel()" to "doBigDNNThingByHandBecauseAMDDoesntSupportIt()" isn't a rote translation at all.

Of course, once you accept that it's _not_ "why don't you just translate it," you _can_ iteratively use an LLM to implement the ThingNVidiaGaveYouInAKernel, but it probably isn't well-trained, yet, on low-level AMD optimization tricks, so the kernel you end up with will likely be slower than the CUDA one.

Re: Nvidia's Risky Business

#180

Post by galaxyLogic »

larnon wrote: post #175
mdp2021 wrote: post #169

Earlier quoted context omitted.

> AI is supposed have solved the Which AI? LLMs are coding facilitators and code producers. A problem is solved when the solution is reliable. Non-deterministic Neural Networks are not reliable. In fact, > more mechanical[] task that suggests an expectation of process and procedure, which is still not a capability of current architectures. Sure, you can ask a brains-deficient operator to perform a huge task, but then…

The tool itself (AI) may not be reliable, but that is also very true for every other tool (e.g. Human). Also, you are right about when a problem is solved, but this doesn't need the tool to be reliable as you said, just the solution part. Hence, as long as the produced code works as intended, it doesn't matter what you used to produce the output.

Saw this on the web:

"AMD and Anthropic also formed a multiyear engineering partnership to optimize ROCm using Claude"

FROM: https://finance.yahoo.com/markets/stocks/articles/ex-amd-exe...

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