@tante The "Open Source AI Definition" was the final straw for me to recognize OSI for what they are (at least have become): a capitalist apologist shill group.

@tante hey @pallenberg dieser Post von Tante hat mich sehr an deiner Episode mit Don im Techlounge Podcast erinnert.

Gibt es oder gibt es keine Open Source AI?

@tante thanks for writing this. Actually, just reading your caption ("'Open Source AI' does not meaningfully exist. It's just openwashing proprietary shit") was a clarifying moment because I was wondering how practical a truly Open Source LLM (all the "sources", including the entire training data, bundled together into one big repo) would be

And then I realised: it's not about being "practical". The definition's job is to set the standard, and reaching that or not is the implementer's problem

@tante Curious, what do you think of apertus: https://www.swiss-ai.org/apertus ? The Swiss seem to be making a meaningful attempt? "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." (I haven't used it myself.)

@tante @colincornaby Have you looked at https://allenai.org/olmo? For most of the "open weight" models, I'd completely agree - but the Olmo3 work in particular exposes all of the training data as well, which I read as one of the core arguments in that piece. They not only share and show their data, they discuss - in quite some detail - their training processes, including experiments on the pros and cons for techniques on relatively weaker models.

If you haven't seen it, it's very worth looking.

@tante correct. burn the planet down from every desktop, now get to it

@tante There’s Mistral. They have models that have open training data. 🤔

@tante @aburka
Now always closed open - but minded

@tante when ai is open source they just mean its proprietry and not on the cloud

@tante

The thing that is giving me the greatest joy this morning when I woke up was watching Chris Noland and his wife discuss how people are openly rejecting data centers, and they show a short clip of people in the streets, breaking out in cries of joy when one person announced that the data center project had been rejected from their city

@tante

cont'd

"Even with open-source AI, you still need huge amounts of data, labor, and infrastructure. They don’t challenge the concentration that includes distribution networks, economies of scale, entrenched reach, the ability to define the tooling and the standards, and so on. Claiming they do these things confuses and distracts us from the type of solutions we need."

/2 /end

@tante

Meredith Whittaker explains *why* open source ai is simply a masquerade:

https://ainowinstitute.org/publications/open-source

The key novelty of the current AI moment is the presence of concentrated amounts of data that had not been available before, and powerful distributed computational systems to process that data to train and perform inference on AI models.

1/

@tante olmoe by Allen.ai and some Firefox things

@tante OMG thank you. "I run my model locally" has become the everlasting thoughtstopper for any #AntiAI comment. I'm becoming extremely irritated with that response.

(I know there are niche attempts that work even worse than all the other models)