A battle is raging over the definition of open-source AI

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Subscribe to enjoy similar stories. There are two sides to the software industry. One faces outwards, with whizzy products and services that bring in billions of dollars of revenue for trillion-dollar companies.

The other faces inwards, creating, updating and sharing—often for free—the basic software infrastructure and tools that makes the digital world tick. Open-source software—in which a developer releases the source code for a product and allows anyone else to reuse and remix it to their liking—is at the foundation of Google’s Android, Apple’s iOS and all four of the largest web browsers. The encryption of a WhatsApp chat, the compression of a Spotify stream and the format of a saved screenshot are all controlled by open-source code.

Though the open-source movement has its roots in the post-hippy utopianism of 1980s California, it is nevertheless going strong today in part because its ethos is not entirely altruistic. Making software freely available has allowed developers to get help making their code stronger; prove its trustworthiness; earn plaudits from their peers; and, in some cases, make money by selling support to those who use the products for free. Several model-makers in the world of artificial intelligence (AI), including Meta, a social-media giant, want to follow in this open-source tradition as they develop their suites of powerful products.

They hope to corral hobbyists and startups into a force that can rival billion-dollar labs—all while burnishing their reputation. Unfortunately for them, though, guidelines published last week by the Open Source Initiative (OSI), an American non-profit, have suggested that the modern use of the term by tech giants has become stretched into meaninglessness. Burdened