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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'

#341

Post by yoyohello13 »

Abishek_Muthian wrote: post #283

I'm looking at my Jetson Nano in the corner which is fulfilling its post-retirement role as a paper weight because Nvidia abandoned it in 4 years. Nvidia Jetson Nano, A SBC for "AI" debuted with already aging custom Ubuntu 18.04 and when 18.04 went EOL, Nvidia abandoned it completely without any further updates to its proprietary jet-pack or drivers and without them all of Machine Learning stack like CUDA, Pytorch et…

And unless there is some expanded maintenance going on, 22.04 is EOL in 2 years. In my experience, vendors are not as on top of security patches as upstream. We will see, but given NVIDIA's closed ecosystem, I don't have high hopes that this will be supported long term.

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

#342

Post by smallmancontrov »

busterarm wrote: post #336
vladslav wrote: post #303

Earlier quoted context omitted.

I've had a similar experience, my Xavier NX stopped working after the last update and now it's just collecting dust. To be honest, I've found the Nvidia SBC to be more of a hassle than it's worth.

Xavier AGX owner here to report the same.

Wait, my AGX is still working, but I have kept it offline and away from updates. Do the updates kill it? Or is it a case of not supporting newer pytorch or something else you need?

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

#343

Post by jckahn »

sensesp wrote: post #169
derbaum wrote: post #140

I'm a bit surprised by the amount of comments comparing the cost to (often cheap) cloud solutions. Nvidia's value proposition is completely different in my opinion. Say I have a startup in the EU that handles personal data or some company secrets and wants to use an LLM to analyse it (like using RAG). Having that data never leave your basement sure can be worth more than $3000 if performance is not a bottleneck.

100% I see many SMEs not willing to send their data to some cloud black box.

Exactly this. I would happily give $3k to NVIDIA to avoid giving 1 cent to OpenAI/Anthropic.

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

#345

Post by justin66 »

busterarm wrote: post #336
vladslav wrote: post #303

Earlier quoted context omitted.

I've had a similar experience, my Xavier NX stopped working after the last update and now it's just collecting dust. To be honest, I've found the Nvidia SBC to be more of a hassle than it's worth.

Xavier AGX owner here to report the same.

My Jetson TX2 developer kit didn't stop working, but it's on a very out of date Linux distribution.

Maybe if Nvidia makes it to four trillion in market cap they'll have enough spare change to keep these older boards properly supported, or at least upstream all the needed support.

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

#346

Post by startupsfail »

halJordan wrote: post #321
Abishek_Muthian wrote: post #283

I'm looking at my Jetson Nano in the corner which is fulfilling its post-retirement role as a paper weight because Nvidia abandoned it in 4 years. Nvidia Jetson Nano, A SBC for "AI" debuted with already aging custom Ubuntu 18.04 and when 18.04 went EOL, Nvidia abandoned it completely without any further updates to its proprietary jet-pack or drivers and without them all of Machine Learning stack like CUDA, Pytorch et…

It runs their dgx os and Jensen specifically said it would be a full part if their hw stack

If this is DGX OS, then yes, this is what you’ll find installed on their 4-cards workstations.

This is more like a micro-DGX then, for $3k.

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

#348

Post by lolinder »

logankeenan wrote: post #337
lolinder wrote: post #244

Earlier quoted context omitted.

Heck, I'm willing to pay $3000 for one of these to get a good model that runs my requests locally. It's probably just my stupid ape brain trying to do finance, but I'm infinitely more likely to run dumb experiments with LLMs on hardware I own than I am while paying per token (to the point where I currently spend way more time with small local llamas than with Claude), and even though I don't do anything sensitive I'm…

Have you been to the localLlama subreddit? It’s a great resource for running models locally. It’s what got me started. https://www.reddit.com/r/LocalLLaMA/

Yep! I don't spend much time there because I got pretty comfortable with llama before that subreddit really got started, but it's definitely turned up some helpful answers about parameter tuning from time to time!

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

#349

Post by lioeters »

tarsinge wrote: post #278
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 sure wished I held some Nvidia stocks I’m so tired of this recent obsession with the stock market. Now that retail is deeply invested it is tainting everything, like here on a technology forum. I don’t remember people mentioning Apple stock every time Steve Jobs made an announcement in the past decades. Nowadays it seems everyone is invested in Nvidia and just want the stock to go up, and every product announceme…

> hope we get a crash

That's the best time to buy. ;)

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

#350

Post by tcdent »

Abishek_Muthian wrote: post #283

I'm looking at my Jetson Nano in the corner which is fulfilling its post-retirement role as a paper weight because Nvidia abandoned it in 4 years. Nvidia Jetson Nano, A SBC for "AI" debuted with already aging custom Ubuntu 18.04 and when 18.04 went EOL, Nvidia abandoned it completely without any further updates to its proprietary jet-pack or drivers and without them all of Machine Learning stack like CUDA, Pytorch et…

If you're expecting this device to stay relevant for 4 years you are not the target demographic.

Compute is evolving way too rapidly to be setting-and-forgetting anything at the moment.

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