this post was submitted on 30 Jun 2026
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[–] insurgentrat@hexbear.net 26 points 2 days ago* (last edited 2 days ago) (2 children)

There are no open source models. The source is all the training data, the weights are open but due to the nature of neural nets this doesn't allow studying, extension, or remixing.

It is akin to distributing the machine code. It runs the stuff sure, but you can't usefully take a bit out or say "Why is it producing text that looks like xyz?" you can only be like "yep neuron 426 has a weight of .112 and activated here. What does neuron 426 do? When did it get that weight? How does the weight change with changes to the source material? Who knows".

This matters to me. The important thing about open source isn't that you can run it for free. We had shareware. It's that you can study it, learn from it, critique it, and improve it.

[–] SchillMenaker@hexbear.net 7 points 2 days ago (1 children)
[–] insurgentrat@hexbear.net 11 points 2 days ago (1 children)

I should probably effortpost about the history of opensource and the key characteristics of it vs shareware/freeware and how this relates to LLMs

Too many people have just blindly swallowed the corporate line that they are open source because corps say so. I think this is because most people's exposure to opensource is as free as in beer software you just passively use.

[–] QuietCupcake@hexbear.net 4 points 2 days ago (1 children)

I should probably effortpost about the history of opensource and the key characteristics of it vs shareware/freeware and how this relates to LLMs

I for one would really appreciate this and wouldn't mind being tagged if/when you do.

[–] KuroXppi@hexbear.net 2 points 2 days ago
[–] Letztertod@hexbear.net 3 points 2 days ago

Literally, open source means something like linux, something that can be studied on the most fundamental level.