Parth Nobel, Alan Z. Rozenshtein & Chinmayi Sharma
In light of the explosive growth of generative AI, which the general public has adopted at a faster rate than personal computers or the Internet, it is natural to worry about who controls this technology. Most of the major industry players—including leading AI labs such as OpenAI (makers of ChatGPT), Anthropic (Claude), and Google (Gemini)—rely on closed models whose details are kept private and whose operation is entirely dependent on the whims of these (increasingly profit-hungry) private companies.
A notable exception to this trend of closed AI models is Meta, whose advanced foundation model, Llama, has publicly available parameters. Meta has gone all-in on what it calls “open-source AI”—what we, for reasons explained below, call “open-access AI”—going so far as to argue that such models are not only as good as but are indeed superior to closed models. Indeed, while open-access models have traditionally lagged behind their closed counterparts in performance, Meta, along with other makers of open-access foundational models such as IBM and AI chip giant Nvidia, has largely closed the gap. Although competition between closed and open-access models will no doubt continue, it is plausible that, going forward, there will not be a meaningful capability gap between open and closed models.
Meta’s argument in favor of openness in AI models relies heavily on analogy to open-source software. In a statement accompanying one of the Llama releases, Meta founder and CEO Mark Zuckerberg made a direct analogy to what is arguably open-source software’s greatest triumph: the development of the Linux operating system that runs a majority of the world’s computers, including most phones (Android being a fork of Linux) and web servers. He is not alone.
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