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Nvidia's Project Digits is a 'personal AI supercomputer'

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Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#201

Post by epolanski »

dagmx wrote: post #7
Karupan wrote: post #6

I feel this is bigger than the 5x series GPUs. Given the craze around AI/LLMs, this can also potentially eat into Apple’s slice of the enthusiast AI dev segment once the M4 Max/Ultra Mac minis are released. I sure wished I held some Nvidia stocks, they seem to be doing everything right in the last few years!

I think the enthusiast side of things is a negligible part of the market. That said, enthusiasts do help drive a lot of the improvements to the tech stack so if they start using this, it’ll entrench NVIDIA even more.

If this is gonna be widely used by ML engineers, in biopharma, etc and they land 1000$ margins at half a million sales that's half a billion in revenue, with potential to grow.

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#202

Post by [deleted] »

spaceman_2020 wrote: post #163
qwertox wrote: post #23

Earlier quoted context omitted.

You could have said the same about gamers buying expensive hardware in the 00's. It's what made Nvidia big.

I keep thinking about stocks that have 100xd, and most seemed like obscure names to me as a layman. But man, Nvidia was a household name to anyone that ever played any game. And still so many of us never bothered buying the stock Incredible fumble for me personally as an investor

[deleted]

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#203

Post by kllrnohj »

fweimer wrote: post #193

If they end up actually shipping this, lots of people will buy these machines to get an AArch64 Linux workstation—even if they are not interested in AI or Nvidia GPUs. At $3,000, it will be considerably cheaper than alternatives available today (except for SoC boards with extremely poor performance, obviously). I also expect that Nvidia will use its existing distribution channels for this, giving consumers a shot at…

> At $3,000, it will be considerably cheaper than alternatives available today

$3000 gets me a 64-core Altra Q64-22 from a major-enough SI today: https://system76.com/desktops/thelio-astra-a1-n1/configure

And of course if you don't care about the SI part, then you can just buy that motherboard & CPU directly for $1400 https://www.newegg.com/asrock-rack-altrad8ud-1l2t-q64-22-amp... with the 128-core variant being $2400 https://www.newegg.com/asrock-rack-altrad8ud-1l2t-q64-22-amp...

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#204

Post by a_bonobo »

newsclues wrote: post #196
a_bonobo wrote: post #192

There's a market not described here: bioinformatics. The owner of the market, Illumina, already ships their own bespoke hardware chips in servers called DRAGEN for faster analysis of thousands of genomes. Their main market for this product is in personalised medicine, as genome sequencing in humans is becoming common. Other companies like Oxford Nanopore use on-board GPUs to call bases (i.e., from raw electric signal…

Is this for research labs, health clinics, or peoples homes?

ONT sells its smallest MinION to regular people, too. But Illumina's and ONT's main market is universities, followed by large hospitals

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#205

Post by pbalcer »

palmfacehn wrote: post #147
blackoil wrote: post #137

Earlier quoted context omitted.

Isn't that just a regular PC with one or more 5090 or equivalent workstation GPU?

There would be unified GPU/CPU memory and an ARM processor that isn't soldered to the board.

One of the reasons why they can do unified memory efficiently is because the CPU/GPU is a single SoC. If you separate them, you end up with a normal PC architecture, with memory having to go through a PCIe bus. This is possible to do with reasonable latency and bandwidth (thanks to CXL), but we haven't seen that in consumer hardware. Even in server space I think only MI300 supports CXL, and even then I don't think it's something AMD particularity promotes.

Personally I think Strix Halo workstations may come with expendable memory, storage and free PCIe slots. But then you have to deal with ROCm...

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#206

Post by mft_ »

treprinum wrote: post #150

Nvidia just did what Intel/AMD should have done to threaten CUDA ecosystem - release a "cheap" 128GB local inference appliance/GPU. Well done Nvidia, and it looks bleak for any AI Intel/AMD efforts in the future.

I think you nailed it. Any basic SWOT analysis of NVidia’s position would surely have to consider something like this from a competitor - either Apple, who is already nibbling around the edges of this space, or AMD/Intel who could/should? be.

It’s obviously not guaranteed to go this route, but an LLM (or similar) on every desk and in every home is a plausible vision of the future.

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#208

Post by trhway »

tatersolid wrote: post #190
trhway wrote: post #97

Earlier quoted context omitted.

>enthusiast AI dev segment i think it isn't about enthusiast. To me it looks like Huang/NVDA is pushing further a small revolution using the opening provided by the AI wave - up until now the GPU was add-on to the general computing core onto which that computing core offloaded some computing. With AI that offloaded computing becomes de-facto the main computing and Huang/NVDA is turning tables by making the CPU is jus…

> these databases can be executed on GPU with a significant performance gain vs. CPU No, they can’t. GPU databases are niche products with severe limitations. GPUs are fast at massively parallel math problems, they anren’t useful for all tasks.

>GPU databases are niche products with severe limitations.

today. For the reasons like i mentioned.

>GPUs are fast at massively parallel math problems, they anren’t useful for all tasks.

GPU are fast at massively parallel tasks. Their memory bandwidth is 10x of that of the CPU for example. So, typical database operations, massively parallel in nature like join or filter, would run about that faster.

Majority of computing can be parallelized and thus benefit from being executed on GPU (with unified memory of the practically usable for enterprise sizes like 128GB).

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#209

Post by evandijk70 »

a_bonobo wrote: post #192

There's a market not described here: bioinformatics. The owner of the market, Illumina, already ships their own bespoke hardware chips in servers called DRAGEN for faster analysis of thousands of genomes. Their main market for this product is in personalised medicine, as genome sequencing in humans is becoming common. Other companies like Oxford Nanopore use on-board GPUs to call bases (i.e., from raw electric signal…

This is, at least for now, a relatively small market. Illumina acquired the company manufacturing these chips for $100M. Analysis of a genome in the cloud generally costs below $10 on general purpose hardware.

It is of course possible that these chips enable analyses that are currently not possible/prohibited by cost, but at least for now, this will not be the limiting factor for genomics, but cost of sequencing (which is currently $400-500 per genome)

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#210

Post by gkuan »

acchow wrote: post #98
Karupan wrote: post #65

Earlier quoted context omitted.

They are perfectly fine for certain people. I can run Qwen-2.5-coder 14B on my M2 Max MacBook Pro with 32gb at ~16 tok/sec. At least in my circle, people are budget conscious and would prefer using existing devices rather than pay for subscriptions where possible. And we know why they won't ship NVLink anymore on prosumer GPUs: they control almost the entire segment and why give more away for free? Good for the compa…

> I can run Qwen-2.5-coder 14B on my M2 Max MacBook Pro with 32gb at ~16 tok/sec. At least in my circle, people are budget conscious Qwen 2.5 32B on openrouter is $0.16/million output tokens. At your 16 tokens per second, 1 million tokens is 17 continuous hours of output. Openrouter will charge you 16 cents for that. I think you may want to reevaluate which is the real budget choice here Edit: elaborating, that extra…

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