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Another potential reason, not mentioned in the article, is that open source models obviously pose the biggest threat in the labs' ability to monetize their tech. Anthropic especially seems to be very anti open-source. If frontier models start to plateau and don't have capabilities that truly differentiate them, nobody will pay what the labs would want to charge. Posing the tech as a danger is a way for them to make the government regulate open source models.

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This is a great point. I'm kind of surprised there isn't a greater proliferation of open source models to do things the public ones won't. I know such things exist, but imagine how many web browsers there would be if all the mainstream ones had the same content restrictions as LLMs.

I guess since training them does take cash that raises the bar for what people will do as a prank or on principle.

Training is time-consuming and/or expensive but it is not the main blocker.

The main problem is obtaining a big enough training data set. Now, unless you are someone like Google or Microsoft, it has become much harder to scrap data from the Internet than by the time when OpenAI and Anthropic got most of their data.

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