Sure. My company has a database of all technical papers written by employees in the last 30-ish years. Nearly all of these contain proprietary information from other companies (we deal with tons of other companies and have access to their data), so we can't build a public LLM nor use a public LLM. So we created an internal-only LLM that is only trained on our data.

It can use public domain licenced data

Apertus was developed with due consideration to Swiss data protection laws, Swiss copyright laws, and the transparency obligations under the EU AI Act. Particular attention has been paid to data integrity and ethical standards: the training corpus builds only on data which is publicly available. It is filtered to respect machine-readable opt-out requests from websites, even retroactively, and to remove personal data, and other undesired content before training begins.

https://www.swiss-ai.org/apertus

Fully open source, even the training data is provided for download. That being said, this is the only one I know of.

Adobe's image generator (Firefly) is trained only on images from Adobe Stock.

Keep going. Handmade analog mediums only.

Coincidentally, this paper published yesterday indicates that LLMs are worse at coding the closer you get to the low level like assembly or binary. Or more precisely, ya stop seeing improvements pretty early on in scaling up the models. If I'm reading it right, which I'm probably not.

Just stop using computers at all to program computer games.

Or just have a hard cut-off for software released after 2022.

It's the only way I search for recipes anymore - a date filter from 1/1/1990 - 1/1/2022.

That’s a big part of the reason why “AI slop” looks so bad. Inference is fundamentally not how people create complex and delicate art pieces. It’s like constructing a house by starting with the paint job and ending with the framing lumber, then asking an architect to fix where you fucked up.

This is just the whole robot sandwich thing to me.

A tool is a tool. Fools may not use them well, but someone who understands how to properly use a tool can get great things out of it.

Doesn’t anybody remember how internet search was in the early days? How you had to craft very specific searches to get something you actually wanted? To me this is like that. I use generative AI as a search engine and just like with altavista or google, it’s up to my own evaluation of the results and my own acumen with the prompt to get me where I want to be. Even then, I still need to pay attention and make sure what I have is relevant and useful.

I think artists could use gen AI to make more good art than ever, but just like a photographer… a thousand shots only results in a very small number of truly amazing outcomes.

Gen AI can’t think for itself or for anybody, and if you let it do the thinking and end up with slop well… garbage in, garbage out.

At the end of the day right now two people can use the same tools and ask for the same things and get wildly different outputs. It doesn’t have to be garbage unless you let it be though.

I will say, gen AI seems to be the only way to combat the insane BEC attacks we have today. I can’t babysit every single user’s every email, but it sure as hell can bring me a shortlist of things to look at. Something might get through, but before I had a tool a ton of shit got through, and we almost paid tens of thousands of dollars in a single bogus but convincing looking invoice. It went so far as a fucking bank account penny test (they verified two ach deposits) Four different people gave their approvals - head of accounting included… before a junior person asked us if we saw anything fishy. This is just one example for why gen AI can have real practical use cases.

How do you think a human decides what to sketch? They talk about the requirements.