When a business depends 100% on a model, using an open weight model on multiple providers is a lot better strategy than relying on the latest closed frontier model. People dont necessarily need to be inference experts. There is Baseten, Fireworks, Fal and countless other companies figuring out how to make inference fast on open weights models.
Anthropic CEO Dario Amodei on Open-Source AI Models.
"I don't think open source works the same way in AI that it has worked in other areas. Primarily because with open source you can see the source code of the model. Here we can't see inside the model, it's often called open weights instead of open source to kind of distinguish that. But a lot of the benefits, which is that many people can work on it and that it's kind of additive, don't quite work in the same way.
So I've actually always seen it as a red herring. When I see a new model come out I don't care whether it's open source or not. If we talk about Deep Seek I don't think it mattered that Deep Seek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That's the only thing that I care about.
It actually doesn't matter either way. Because ultimately you have to host it on the cloud. The people who host it on the cloud do inference. These are big models, they're hard to do inference on.
When I think about competition I think about which models are good at the tasks that we do. I think open source is actually a red herring.
It's not free. You have to run it on inference and someone has to make it fast on inference."
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From 'Alex Kantrowitz' YT channel (full video link in comment)
