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I put a datacenter GPU in my gaming PC

blog.tymscar.com

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Re: I put a datacenter GPU in my gaming PC

#121

Post by iugtmkbdfil834 »

yjftsjthsd-h wrote: post #96
iugtmkbdfil834 wrote: post #84

Earlier quoted context omitted.

In a sense, there is a clear market for it ( people want 'authentic' experience ). I can kinda understand it. I want pure linux experience without systemd, but I recognize that in the current ecosystem, it comes at a cost. So the language harness makes sense to me, but corps are already cracking down on token use ( and such a harness would likely only add to the cost ). The other question is whether the people, who c…

> I want pure linux experience without systemd, but I recognize that in the current ecosystem, it comes at a cost. Running Alpine/Gentoo/Devuan isn't that expensive. (I'm assuming the cost is time/effort when I say this; let me know if there's another relevant metric)

No, you are right on point. I think I reached the same level of 'troubleshooting fatigue' my buddy did ( but he does that for a living, which adds another layer to this ). At certain point, I just want stuff to work. And right now at least, systemd provides least amount of annoyance in terms of time spent chasing issues on home machines.

FWIW, I tried Void and Devuan, but that may have been too early for me then. Naturally, now that stuff mostly works, I am debating whether I can make that attempt again;p

Re: I put a datacenter GPU in my gaming PC

#122

Post by hakfoo »

mschuster91 wrote: post #60
echelon wrote: post #21

Earlier quoted context omitted.

> Consider this: in 5-10 years, the trillions spent on AI data centers will likewise be sold for scrap most likely. That's how short the runway is for OpenAI and Anthropic to recover that investment. Even more interesting: it'll devalue all of SaaS and the entire US tech sector. We might have just shot our most valuable non-AI tech products in the foot.

> We might have just shot our most valuable non-AI tech products in the foot. Counterpoint: the fiber buildout during the dotcom boost. That crashed the economy pretty hard when the bubble burst, but we are still benefitting from all the dark fiber that was arranged for and built out back in that era. A lot of today's ISPs were able to grab up that fiber after the bust for cents on the dollar. Assume that OpenAI and…

You're expecting that there's going to be a supply collapse only, but there's a real risk the collapse hits both supply and demand.

A lot of the current AI business is FOMO and vanity metrics. Nobody really wants to acknowledge the support tickets where the first three responses are the customer cursing because they didn't appreciate being handed off to a chatbot, or the reworks, or the compliance/policy/privacy concerns, or the internal friction and brand damage it's causing.

Right now, a lot of that is being dazzled away by how "cheap" the alternative is, since it's built on an unsustainable cost base. It's like someone opened a "restaurant" where the food was actually supplied by making a bazillion new DoorDash accounts to claim promotional credits and having them drop the food at the "kitchen". During the initial phase, the customers will forgive that the burger was cold because it was $1.79.

Once the funny money runs out and services start shuttering or pricing for actual profitability, people are going to ask about actual quality and return on investment. There will be a demand rollback.

Even if you can do it cheaper with an open-model running on fire-sale hardware, we probably don't need 500 "chatbot listens and transcribes your meeting" services that weren't that much better than dictation software running locally on a Pentium III. We probably don't need AI-powered support experiences that manage to be worse than actually keyword-searching your company's Confluence. We probably don't need to be spinning up coding agents to spend 15 minutes discombobulating and bibblewabbling and re-reading 82 billion tokens of context before making a two-line change that an actual developer with learned experience in the code would make in 15 seconds.

Re: I put a datacenter GPU in my gaming PC

#125

Post by lowbloodsugar »

20wenty wrote: post #56
whoamii wrote: post #36

The real question: did your local LLM write this post?

There are many tells aren't there? There was clearly hard human work and experimentation here, but it's a shame the OP let AI do chunks of the writing. Once you see it, it's much harder to take the post seriously.

Oh then please stop reading. There are many of us who are really good at solving complex problems and also really bad at communicating them. Your attitude is just the latest bastion of bigotry. So do feel free to self-select out of useful knowledge and experience.

Re: I put a datacenter GPU in my gaming PC

#126

Post by lelanthran »

tymscar wrote: post #118
lelanthran wrote: post #116

Earlier quoted context omitted.

> I’m glad I’ve started this blog before the AI wave so I can prove people I’m just weird at writing. Your previous blog posts didn't trigger any LLM detector (go on - check for yourself).

Neither does this one. I replied in another thread. It comes out as 0% and the one from 2021 comes out as 8%. LLM detectors are all BS

GPTzero says 100% AI generated for specific paragraphs that I chose (such as `Multi-token prediction`). If you remove all the code listings, tables, etc and just paste the prose into these tools, it drops to 87% AI generated.

None of the 3x older blogs of yours that I tried went above 5% AI generated.

Maybe you're spending so much of time with the LLM that you are talking like it; in which case, take an old blog and a recent blog, give the prose from them both to you favourite LLM and ask them if the same author wrote both. I just did that on ChatGPT and on Gemini, and both found that it is extremely unlikely that the same author wrote both.

Look, if all the SOTA LLMs agree that your recent blogs sounds generated, you can't blame the reader, can you?

Re: I put a datacenter GPU in my gaming PC

#127

Post by lelanthran »

tymscar wrote: post #115
lelanthran wrote: post #28

Earlier quoted context omitted.

> Where do you think llms learned to write that way? Not from individual human content, that's for sure - maybe MLM marketing copy? Sleazy 4AM ads? I mean, every time this response comes up, I keep asking the person to point at something written prior to 2022 that gets 80%+ on the LLM detectors, and yet no one can find anything. Maybe you, postalrat, can find something written in this style that was published prior t…

I have written the blog post. I know empirically that I have used 0% AI while writing it. I also know LLM detectors are total BS and they don't really work. I have tried a couple on this exact blog post, and QuillBot, for example, gave me 0% AI detected on it. I have then used a blog post of mine from 2021. QuillBot gave me 8%... The King James version of the Bible came out at almost 100% AI generated a while ago. It…

> I have tried a couple on this exact blog post, and QuillBot, for example, gave me 0% AI detected on it.

Don't use Quillbot; not sure why, but their model is reluctant to classify anything as AI generated. I ran into this when proof-reading a students Phd - ChatGPT, Gemini, CLaude (and others) all agreed it was AI generated, but Quillbot said it wasn't.

Re: I put a datacenter GPU in my gaming PC

#128

Post by tymscar »

lelanthran wrote: post #126
tymscar wrote: post #118

Earlier quoted context omitted.

Neither does this one. I replied in another thread. It comes out as 0% and the one from 2021 comes out as 8%. LLM detectors are all BS

GPTzero says 100% AI generated for specific paragraphs that I chose (such as `Multi-token prediction`). If you remove all the code listings, tables, etc and just paste the prose into these tools, it drops to 87% AI generated. None of the 3x older blogs of yours that I tried went above 5% AI generated. Maybe you're spending so much of time with the LLM that you are talking like it; in which case, take an old blog and…

GPTzero is a joke.

It thinks this is AI: “I bought a datacenter GPU that doesn’t even have a normal PCIe connector, stuck it in my gaming PC with an adapter, and now I have 32GB of VRAM across two GPUs running a 27 billion parameter model at 32 tokens per second.”

There’s nothing AI about that. Not all SOTA LLMs agree, hell, none of them do. The same exact example I sent here gives me 0% in some, 10% in others, 100% in GPTzero.

Re: I put a datacenter GPU in my gaming PC

#129

Post by _zoltan_ »

legitronics wrote: post #81
Teknomadix wrote: post #14

Tesla V100 SXM2 16GB is NOT DGX class as the author writes. It's HGX class. The V100 comes in two classes, SXM2 and SXM4, the latter coming with a Max of 80gb on board memory. Typically these are installed 8×A100 80GB SXM4 on an HGX riser, and what that gives you is NVSwitch fabric and 640GB of pooled HBM2e (on package stacked memory /w ~2 TB/s of memory bandwidth). 2u standard rack footprint too.

I have no idea what you are trying to say. V100 came as sxm2 and sxm3. And it was 16 and 32gb. HGX is DGX with extra toppings.

No. DGX is when it's Nvidia's design, HGX when it's a 3rd party design.

Re: I put a datacenter GPU in my gaming PC

#130

Post by _zoltan_ »

Teknomadix wrote: post #14

Tesla V100 SXM2 16GB is NOT DGX class as the author writes. It's HGX class. The V100 comes in two classes, SXM2 and SXM4, the latter coming with a Max of 80gb on board memory. Typically these are installed 8×A100 80GB SXM4 on an HGX riser, and what that gives you is NVSwitch fabric and 640GB of pooled HBM2e (on package stacked memory /w ~2 TB/s of memory bandwidth). 2u standard rack footprint too.

What on earth are you talking about? Your comment makes no sense.

The V100 and A100 are different generations altogether.

The V100 does not have 2TB/s.

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