Profile for bryan

Display name
Bryan :tng_badge:
Username
@bryan@dusty.ninja
Role
admin

About bryan

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$jiqiren

Bio

ex-Apple, ex-Yahoo, ex-Digg, ex-NASA(JPL & Ames), “i like pop music”

Previously @Bryan

Kubernetes fanboi

Honolulu, Hawaii

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Recent public and unlisted posts

exclude boosts

Seems like whenever I tap a word in the #Kindle app to see a definition… I need to download the English dictionary again. I can’t remember this ever just working first tap.

Either I rarely look at word definitions or the Kindle app is 💩.

Good read about #RISC vs #ARM ecosystems. I didn't see the previous two blogs (he wrote an initial post that generated a response... now he is responding to this).

NOTE: I deleted original of this because #RISC got autocorrected to #RISK... 🤦🏼‍♂️
If I was doing (ANY!) embedded work I'd probably enjoy this more...
https://rvembedded.com/blog_post/12/

Bryan :tng_badge: , @bryan
(open profile)
Boost of @wyattearp@defcon.social
Wyatt Neal , @wyattearp@defcon.social
(open profile)

THE DGX SPARK WAS NEVER SUPPOSED TO SET YOU FREE

Listen to me.

128GB WAS NOT A TECHNICAL LIMIT.

It was a containment boundary.

You think NVIDIA accidentally built a tiny Blackwell supercomputer with 200Gb networking and then somehow stumbled into exactly enough memory to make every ambitious local-AI workload tantalizingly miserable?

COME ON.

64GB would've been obviously useless.

256GB would've been dangerous.

Because at 256GB, normal people start getting ideas.

Suddenly you're running giant quantized models comfortably. Fine-tuning gets breathing room. Long contexts stop being a hostage negotiation. You start running multiple models.

Then somebody asks the forbidden question:

"Why the hell am I renting GPUs?"

AND THAT QUESTION CANNOT BE ALLOWED TO PROPAGATE.

So they gave us 128GB.

Not enough to escape.

Enough to see the fence.

And look at the networking!

WHY DOES THE CUTE LITTLE DESKTOP AI BOX HAVE 200 GIGABIT CONNECTX?!

Because the second you smash into the memory ceiling, NVIDIA already has the solution:

BUY ANOTHER SPARK.

Now you've got 256GB!

Need more?

BUY FOUR.

Congratulations!

You wanted a desktop computer and somehow NVIDIA convinced you to build a FUCKING CLUSTER.

And if you're sitting there thinking:

"Surely NVIDIA couldn't possibly put dramatically more coherent memory into a local workstation..."

WRONG.

DGX STATION: 748GB.

THE MEMORY EXISTS.

THE TECHNOLOGY EXISTS.

THEY KNOW YOU WANT IT.

THEY JUST PUT IT IN THE NEXT ROOM AND CHARGE ADMISSION.

This isn't product segmentation.

THIS IS COMPUTATIONAL EDGING.

Spark lets you load the model.

Lets you run the model.

Lets you fine-tune just enough of the model.

Lets you build an entire workflow around the model.

And precisely when you've invested three weekends, fourteen containers, two broken CUDA environments and the remaining fragments of your marriage:

OOM

That's not an error message.

THAT'S THE SALES DEPARTMENT KNOCKING.

And NVIDIA TELLS YOU THE PLAN!

Develop locally.

Prototype locally.

Validate locally.

Then move the serious work onto larger NVIDIA infrastructure.

MY BROTHER IN CUDA,

THAT ISN'T A WORKFLOW.

THAT IS A FUNNEL.

Spark isn't supposed to replace the data center.

Spark is the free sample outside the data center.

The 128GB isn't there because NVIDIA couldn't give you 256.

It's there because 256GB might have been enough.

And enough is the most dangerous word in NVIDIA's entire business model.

So remember:

64GB = nobody buys it.

128GB = everybody wants more.

256GB = people start getting independent.

748GB = PLEASE SEE YOUR NVIDIA SALES REPRESENTATIVE.

WAKE UP.

REMOVE THE THERMAL PASTE FROM YOUR THIRD EYE.

ALIGN YOUR CUDA CHAKRAS.

WRAP YOUR CONNECTX CABLES IN TIN FOIL.

THE DGX SPARK ISN'T A PERSONAL AI SUPERCOMPUTER.

IT'S A 128GB GATEWAY DRUG TO THE DATA CENTER.

#DGXSpark #NVIDIA #LocalAI #AI #MachineLearning #LLM #OpenSourceAI #SelfHostedAI #CUDA #Blackwell #GPU #AIInfrastructure #Homelab #LocalLLM #DataCenter #BigTech #TechConspiracy #UnhingedEddie #WakeUpSheeple #FollowTheVRAM #128GBContainmentProtocol #CUDAChakras #OOMIsTheUpsell #TinFoilComputing

I was browsing #Reddit when I ran into this interesting post. Basically what brought you into #Apple ecosystem. For me it was a Power Mac G5. I was at a startup and a co-founder would always get the newest Apple #Mac when it was released. He unexpectedly gave me his in 2006 when the first Intel Mac Pro tower came out and he got one. Coming from NASA/JPL where I had a Sun Blade running Solaris for my desktop … I was blown away by the #BSD-ness of the Power Mac G5. It was like pure UNIX with actual ecosystem, applications, and vision.

https://www.reddit.com/r/mac/s/EOjPX5Venm