I kid, more real world use cases would be for concept images for a new product or marketing campaigns.

What an impossibly weird thing to "need" an LLM for.

https://youtu.be/-gGLvg0n-uY

Then include this image in a dataset of another net with marker "civilian". Train that new neural net better so that it does lower false positive rate when asked "is this target military".

Definitely a premium.

Videos on wikileaks tell a different story.

The real answer is probably way, way more mundane - generating images for marketing, etc.

[1] https://media.wired.com/photos/5933e578714b881cb296c6ef/mast...

With this, you could create a dataset that will by definition have that. You should still corroborate the data, but it's a step ahead without having to take 1000 photos and adding enough noise and variations to get to 30k.

You take your images and crop, shift, etc them so that your model doesn't learn "all x are in the middle of the image". For text you might auto replace days of the week with others, there's a lot of work there.

Broadly the intent is to keep the key information and generate realistic but irrelevant noise so that you train a model that correctly ignores the noise.

You don't want to train your model identifying some class of ship to base it on how choppy the water is, just because that was the simple signal that correlated well. There was a case of radiology results that detected cancer well but actually was detecting rulers in the image because in images with tumors there was often a ruler so the tumor could be sized. (I think it was cancer, broad point applies if it was something else).

I can get an AI to generate an image of a bear wearing a sombrero. There are no images of this in its training data, but there are bears, and there are images of sombreros, and other things wearing sombreros. It can combine the distributions in a plausible way.

If I am trying to train a small model to fit into the optical sensor of a warhead to target bears wearing sombreros, this synthetic training set would be very useful.

Same thing with artillery in bushes. Or artillery in different lighting conditions. This stuff is useful to saturate the input space with synthetic examples.

See bifrost.ai and their fun videos of training naval drones to avoid whales in an ethical manners

GCCH is typically 6-12 months behind in feature set.

I personally just warn customers that it cannot technically handle CUI or higher, can't say that it stops them

"GPT-4o is now available as part of Azure OpenAI Service for Azure Government and included as part of this latest FedRAMP High and DoD IL4/IL5 Authorization."

...we have everything setup in Azure but are weary to start using with CUI. Our DoD contacts think it's good to go, but nobody wants to go on record as giving the go-ahead.

https://devblogs.microsoft.com/azuregov/azure-openai-fedramp...

https://learn.microsoft.com/en-us/azure/azure-government/com...

* organization required to perform a Risk Assessment (is this standardized?)

* organization must issue an Authority to Operate (ATO) (example? to whom?) to use it for CUI as the data owner.

* organization must ensure data is encrypted properly both at rest and in transit (is plain text typed into a chat window encrypted at rest?).

* organization must ensure the system is documented in a System Security Plan (SSP) (example?).

* organization must get approval from government sponsor of each project to use CUI with AI tools

I am the one pushing for adoption, but don't have the time or FedRAMP/DISA expertise, and our FSO/CISO would rather we just not.

They also have a deployment on SIPR rated for secret.

Anything higher, you need a special key but AWS Bedrock has Claude up on C2S.

That being said both Azure OpenAI and AWS Bedrock suck for many reasons and they will by default extend your system boundary (meaning you need to extend your ATO). Also, for CUI, it has the P-ATO from JAB, not many agency specific ATOs, which means you will probably need to submit it thru your agency sponsor.

(fwiw for anyone curious how to implement it, it's the 'moderation' parameter in the JSON request you'll send, I missed it for a few hours because it wasn't in Dalle-3)

I just took any indication that the parent post meant absolute zero moderation as them being a bit loose with their words and excitable with how they understand things, there were some signs:

1. it's unlikely they completed an API integration quickly enough to have an opinion on military / defense image generation moderation yesterday, so they're almost certainly speaking about ChatGPT. (this is additionally confirmed by image generation requiring tier 5 anyway, which they would have been aware of if they had integrated)

2. The military / defense use cases for image generation are not provided (and the steelman'd version in other comments is nonsensical, i.e. we can quickly validate you can still generate kanban boards or wireframes of ships)

3. The poster passively disclaims being in military / defense themself (grep "in that space")

4. it is hard to envision cases of #2 that do not require universal moderation for OpenAI's sake, i.e. lets say their thought process is along the lines of: defense/military ~= what I think of as CIA ~= black ops ~= image manipulation on social media, thus, the time I said "please edit this photo of the ayatollah to have him eating pig and say I hate allah" means its overmoderated for defense use cases

5. It's unlikely openai wants to be anywhere near PR resulting from #4. Assuming there is a super secret defense tier that allows this, it's at the very least, unlikely that the poster's defense contractor friends were blabbing about about the exclusive completely unmoderated access they had, to the poster, within hours of release. They're pretty serious about that secrecy stuff!

6. It is unlikely the lack of ability to generate images using GPT Image 1 would drive the military to Chinese models (there aren't Chinese LLMs that do this! even if they were, there's plenty of good ol' American diffusion models!)

OP was clearly implying there is some greater ability only granted to extra special organizations like the military.

With all possible respect to OP, I find this all very hard to believe without additional evidence. If nothing else, I don't really see a military application of this API (specifically, not AI in general). I'm sure it would help them create slide decks and such, but you don't need extra special zero moderation for that.

I can't provide additional evidence (it's defense, duh), but the #1 use I've seen is generating images for computer vision training mostly to feed GOFAI algorithms that have already been validated for target acquisition. Image gen algorithms have a pretty good idea of what a T72 tank and different camouflage looks like, and they're much better at generating unique photos combining the two. It's actually a great use of the technology because hallucinations help improve the training data (i.e. the final targetting should be invariant to a T72 tank with a machine gun on the wrong side or with too many turrets, etc.)

That said, due to compartmentalization, I don't know the extent to which image gen is used in defense, just my little sliver of it.

I'm not aware of the moderation parameter here but these contractors have special API keys that unlock unmoderated access for them, they've apparently had it for weeks.

Now I'm just wondering what the hell defense contractors need image generation for that isn't obviously horrifying...

“Please move them to some desert, not the empire state building.”

“The civilians are supposed to have turbans, not ballcaps.”

I'm confused.

The bias leans towards overfitting the data, which in some use cases - such as missile or drone design which doesn't need broad comparisons like 747s or artillery to complete it's training.

Kind of like neural net back propogation but in terms of model /weights

I’m sure access to military grade tech is only one small slice in the set of advantages the masters get over the mastered in any human society.

>> How'd you do it?

> I don't know the details. ChatGPT did it for me, this thing's amazing. Our bonuses are gonna be huge this year, I might even be able to afford a lift kit for my truck.

Trying to align OpenAI etc. with the rest of humanity is a completely different problem.

Additionally, we don't tax unrealized capital gains.

It is generally accepted that business profit is taxed. Meanwhile, there are entire industries and tax havens set up to help corporations and their executives avoid paying taxes.[0]

However, the crux of my comment was not about the vagaries of corporate taxation, it was simply about "AI alignment" being more about the creators, than the entire species.

[0] https://en.wikipedia.org/wiki/Category:Corporate_tax_avoidan...

("There was an old lady who swallowed a fly, …")

Each of those proxies can have an alignment failure with the adjacent level(s).

And RLHF involves training one AI to learn human preferences, as a proxy for what "good" is, in order to be the reward function that trains the actual LLM (or other model, but I've only heard of RLHF being used to train LLMs)

Do people actually fall for these lol? Yes they do and it works to raise interest and get additional funding.

Morals and ethics are different and I would not want the US to be "protecting the world" with their ridiculous ethics and morals.

I would imagine defense contractors can cut deals for similar preferential treatment with OAI and the like to be exempt from potentially copyright-infringing uses of their API.

[0]https://fortune.com/asia/2024/07/03/pentagon-huawei-ban-nati...