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Nvidia RTX Spark

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Re: Nvidia RTX Spark

#131
post #71

[flagged]

Right, the export controls are only forcing Chinese AI to innovate, build their own fabs, and make training and inference more efficient. The end game of this will be NVIDIA chips won’t be wanted because you can get a $50 chinese chip running a ternary model that is competitive with claude in English and is much better in Mandarin.

The US government has failed to learn from its own history.

60 years ago the US government had forbidden the export of fast computers to France, with the hope that this sanction will prevent the French from developing thermonuclear bombs.

The result was that the French state (which at that time was lead by de Gaulle, not much less autocratically than China) subsidized some of their computer manufacturers, which previously could not compete with the American companies like IBM and CDC, and also their semiconductor manufacturing industry, which had to provide the components for the locally-made computers.

Eventually, the French produced TTL circuits and mainframe computers made with them, and finally they also made thermonuclear bombs.

So the American "sanctions" against France have been a complete failure and have been great for the French industry of semiconductors and computers.

Many years later, when USA no longer had export restrictions towards France and the French state no longer protected their industry, the French industries of integrated circuits and computers have been greatly reduced, their companies either becoming bankrupt or being bought or merged into multinational companies.

Re: Nvidia RTX Spark

#133
post #113

Earlier quoted context omitted.

I cannot think why someone would run those workflows on a Windows laptop , unless someone has way too much money to spend.

If the workload is offloaded to the chip, why would the host platform matter?

Lots of machine learning workflows support Linux better than Windows, if they run on Windows at all. (e.g. https://docs.vllm.ai/en/latest/getting_started/quickstart/ )

DGX Spark runs Linux, and nobody is going to install Windows on that machine. This laptop got it backwards.

If someone decides to run Ollama for local inference with this laptop, they fit perfectly into the "has too much money to waste" bracket, which is addressed by a few other comments in the discussion.

Re: Nvidia RTX Spark

#134
post #92

I’m getting more and more convinced that we will end up running LLMs in our personal computers. Which makes me wonder where Anthropic/OpenAIs moats will come from.

While I agree with that in principle, it is very worrisome that the prices of personal computers, especially of any personal computer that is not a big desktop, have been increasing continuously.

The price of a mini-PC with Intel Panther Lake is at least double in comparison with the price of a mini-PC with Arrow Lake H having similar specifications, and I am talking about barebones, before adding DRAM and SSDs, whose prices have risen even more.

The rise in prices is somewhat obfuscated by the confusing names of CPUs, i.e. some old and new CPUs may seem to be at similar prices and they have similar names, but the new CPU actually corresponds to a lower segment of the market, by having e.g. a smaller GPU and a lower clock frequency, while the CPU model that really corresponds to the old is named such that it seems to belong to the class corresponding to its present price.

As a concrete example of this obfuscation, which may confuse the buyers of laptops or mini-PCs, I have an ASUS 15 Pro with "Core Ultra 5 225H". If I would buy an ASUS 16 Pro now, the corresponding CPU model, the cheapest which is not worse than what I have, would be "Core Ultra X7 358H".

Re: Nvidia RTX Spark

#135
post #133

Earlier quoted context omitted.

If the workload is offloaded to the chip, why would the host platform matter?

Lots of machine learning workflows support Linux better than Windows, if they run on Windows at all. (e.g. https://docs.vllm.ai/en/latest/getting_started/quickstart/ ) DGX Spark runs Linux, and nobody is going to install Windows on that machine. This laptop got it backwards. If someone decides to run Ollama for local inference with this laptop, they fit perfectly into the "has too much money to waste" bracket, which…

WSL

Re: Nvidia RTX Spark

#136
post #81

It's been almost 30 years, and a single letter changed. When will we get the Sparkstation, the UltraSpark and the SuperSpark?

SuperSpark and then UltraSpark. And then we can get SparkCube, Sparkii, and SparkiiU.

I'm personally waiting for the OpenSpark.

Re: Nvidia RTX Spark

#137
post #109

Earlier quoted context omitted.

To be fair the connectx-7 in the spark can't even push 2x200 Gbps since it is connected via 4 pcie lanes.

Technically it's connected via 8 PCIe gen 5 lanes (two 4x connections), allowing ~100Gbps per port.

Thanks for the correction. I should have looked it up; I only remembered it being somewhat odd.

Re: Nvidia RTX Spark

#138

So they have basically reused the same hardware as in the DGX Spark (GB10)... That chip isn't great for LLM inference actually. https://www.techpowerup.com/gpu-specs/gb10.c4342 https://www.nvidia.com/en-us/products/rtx-spark/

The RTX GPU laptops run very hot. Even though they are pound for pound better, it’s just runs too hot for local llm usage for me at least. Prefer Macs for this. A lot of AMD cards also run cooler. I wonder if undervting would help with smaller models and heat.

I mean the GB10 is pretty efficient for the power it has, but imho is nowhere near the power efficiency of Apple Silicon (it was never intended to be a chip used for mobile devices). I guess this is kind of the movement Apple did with the A12Z and the Mini but... the other way around?

I think its gonna be another failure as we are used to see with the PC market these days.

Re: Nvidia RTX Spark

#139
What is this product anyway? Is it a general purpose CPU or is it specifically designed for MS Windows? Nvidia stepping back from the open source?

"Introducing the NVIDIA RTX Spark™ Superchip. The fusion of NVIDIA AI and RTX graphics in a single chip redefines Windows PCs and delivers amazing creating, AI development, and gaming—on the slimmest, most beautiful RTX laptops ever and small, ultra-efficient desktops."

Re: Nvidia RTX Spark

#140

After nvidia's many years of neglecting Linux, paired with direct Microsoft's involvement? Are we going to trust them, to allow installing Linux in these easily? I don't think so. This most likely be a winmodem situation, again

DGX Spark has the same soc and ships with Ubuntu
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