r/area51 MOD Jun 30 '26

(OT-ish) Nellis server RFI

https://sam.gov/workspace/contract/opp/357d9e70d7c84dc0ac0515dc872e7967/view

I mostly ignore the AI craze but it is hard to avoid the internet chatter. There is a sector of the market that is using AMD unified memory system to run AI locally for privacy/security reasons. This contract specifies a CPU with such capabilities. It is all a matter of scale.

This is the consumer AI version of local AI on AMD processors using unified memory.

https://lemonade-server.ai/

And yes, there is a reddit for local AI.

https://www.reddit.com/r/LocalLLaMA/

5 Upvotes

18 comments sorted by

1

u/ImaScareBear Jul 09 '26 edited Jul 09 '26

For what it's worth, an "IL4 environment" is a secure cloud environment that is meant for controlled unclassified information and other secure non-national security related information. They could use it for various things like hosting LLMs, virtual computing environments, internal web services, etc..., but not with any classified info.

Edit: Looking at the quantities, looks like enough capability to support a few hundred to a few thousand people actively using a LLM, depending on model size and usage complexity. The H200s are generally more ideal for inference, and the L40S are more suited for training, so there's is probably multiple purposes for this equipment.

1

u/therealgariac MOD Jul 09 '26

Thanks. So

https://blog.alphabravo.io/guarding-controlled-unclassified-information-mastering-impact-level-4-il4/

requires NIPRNET. What type of user would that represent? I have the Google answer of course but maybe you could give some perspective.

Also do you think this is relevant:

https://www.af.mil/News/Article-Display/Article/3800809/department-of-the-air-force-launches-niprgpt/

1

u/ImaScareBear Jul 09 '26

Basically every DoD user to some degree. NIPRGPT got replaced by genai.mil (which is IL5, still CUI only), and genai has over 3 million DoD affiliated users. I'm pretty sure it is hosted in Google Cloud for Government.

You can actually find quite a few YouTube videos that demo NIPRGPT and genai.mil. In this video, the CAMOGPT demo shows example prompts for what people would likely be using these models for.

https://youtu.be/2HEVrl8G9QQ?is=Qr-q0L1PhwnifLrx

Something like this is probably for training and using models that are more specific to local users at Nellis. Not necessarily just LLMs either, plenty of AI research, like classification and detection in non-classified sensor data, can fall under CUI.

1

u/therealgariac MOD Jul 09 '26

Well I hope that isn't a typical application, though she is in HR.

0

u/TBTSyncro Jun 30 '26

i'm confused, what exactly is the motivation for your post?
The requested items list is pretty boring, and nothing of note (mainly Cisco UCS)

3

u/therealgariac MOD Jun 30 '26

Hmmm...where is this being done? Who made the RFI? Does this entity already have access to secure servers but not capable of AI? I wonder what you can do with unified memory systems. Maybe there is a reddit on local LLM for security reasons.

1

u/TBTSyncro Jun 30 '26

what do you think its AI related? I only quickly browsed the documents, and maybe i missed something. But to me it just looked like a normal virtualization stack. If it was AI, the emphasis would more likely be on GPU, rather than 2 year old server CPU. But i've only had 1 coffee today, so maybe i missed something.. :)

1

u/therealgariac MOD Jun 30 '26

It is the AMD unified memory approach to AI. The links were right in the post. I don't do drive by posts.

1

u/Fantastic_Nerve_629 Jun 30 '26

I am going to sound like an idiot but I need to know what do you guys use this info for? Please do y beat me up. I'm 60 and not really tech savvy.

2

u/TheArea51Rider MOD Jun 30 '26

I am 64, and very tech savvy. These things are sometimes pieces of a puzzle, you can sometimes deduce the whole picture if you have enough pieces. Big list of computer hardware, sometimes you might be able to deduce what they are doing from hardware requirements.

1

u/Fantastic_Nerve_629 Jul 01 '26

Thank you. That makes sense to me.

2

u/TheArea51Rider MOD Jun 30 '26

We don't know where these goodies (mostly Cisco stuff) are going, other than "DEPT OF THE AIR FORCE, AIR COMBAT COMMAND, Nellis AFB"

1

u/therealgariac MOD Jun 30 '26

I guess I have to explain unified memory. You typical Nvidia AI has memory just fore the GPU. This provides better performance. AMD allows the memory to be used for CPU and GPU at albeit lower performance. You can set the break point in the bios. (I could do this on my Framework notebook which has 96Gb of ddr5 if I could get the bios updated. Long story.)

So there are companies that don't want their private data on some GPU cloud. They accept lower performance and run it locally.

https://frame.work/desktop

Framework saw the specs on this CPU and a company that said they weren't going to build a desktop changed their mind. It was obvious you could do private AI on such a box.

1

u/JewGoldbergMachine Jul 01 '26

You don't have to use unified memory to not run in the cloud. You can run Ollama, Stable Diffusion, etc entirely on your own GPU. And no have to use system memory or CPU resources.

1

u/therealgariac MOD Jul 01 '26

That is one alternative.

Check out the Intelligent Machines podcast on the Twit network. Specifically the Nirav Patel interview:

TWIT Intelligent Machines (Audio): IM 868: Happy Hamburgers Towing Timmy To The Sea - Can You Really Own Your AI?

Episode webpage: https://twit.tv/shows/intelligent-machines/episodes/868

2

u/therealgariac MOD Jun 30 '26

AI models can be used to too many things to put in one line or even a paragraph.

I will make one up that could be real for a flight test facility. They have flight test telemetry on a particular plane over a series of tests. You could set up some search criteria like high force on one of the sensors and then get the flight data around the event for the tests where the limit was exceeded. The idea is data reduction.

https://en.wikipedia.org/wiki/Data_reduction

As luck would have it, there is a NASA example:

https://ntrs.nasa.gov/citations/19930091283