Open source isn’t working for AI

opensource ai
opensource ai

Clearly, we need to do something about how we talk about open source and openness in general. It’s been clear since at least 2006 when I rightly got smacked down for calling out Google and Yahoo! for holding back on open source. As Tim O’Reilly wrote at the time, in a cloud era of open source, “one of the motivations to share—the necessity of giving a copy of the source in order to let someone run your program—is truly gone.” In fact, he went on, “Not only is it no longer required, in the case of the largest applications, it’s no longer possible.”

That impossibility of sharing has roiled the definition of open source during the past decade, and it’s now affecting the way we think about artificial intelligence (AI), as Mike Loukides recently noted. There’s never been a more important time to collaborate on AI, yet there’s also never been a time when doing so has been more difficult. As Loukides describes, “Because of their scale, large language models have a significant problem with reproducibility.”

Just as with cloud back in 2006, the companies doing the most interesting work in AI may struggle to “open source” in the ways we traditionally have expected. Even so, this doesn’t mean they can’t still be open in meaningful ways.

Good luck running that model on your laptop

According to Loukides, though many companies may claim to be involved in AI, there are really just three companies pushing the industry forward: Facebook, OpenAI, and Google. What do they have in common? The ability to run massive models at scale. In other words, they’re doing AI in a way that you and I can’t. They’re not trying to be secretive; they simply have infrastructure and knowledge of how to run that infrastructure that you and I don’t.

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