The Open Source Initiative, a nonprofit that advocates for open-source software, defines open-source AI as “a system made available under terms that grant users the freedom to use, study, modify and share [it].”
The Open Source Initiative (OSI), a nonprofit that sets the foundation for the open source software ecosystem, did the hard work to define open source decades ago. It identified 10 criteria that include free redistribution, integrity of the author’s source code and no discrimination against persons and groups, among others. These criteria are the guarantees that allow companies to use OSS without calling their legal department every time a developer installs a package.
The Carnegie Mellon University-led Open Forum for AI (OFAI) is developing an Openness in AI framework, which includes the Open Source AI Definition (OSAID) as one of its underpinnings.
According to the Open-Source Initiative, for software to be considered open, it must offer users the freedom to use the software for any purpose, to study how it works, to modify it and to share both the original and modified versions. When applied to AI, true open-source AI include model architecture (the blueprint for how the AI processes data); training data recipes (documenting how data was selected and used to train the model); and weights (the numerical values representing the AI’s learned knowledge).
In this episode of Interpreting India, host Shruti Mittal is joined by Kailash Nadh, chief technology officer of Zerodha and co-founder of FOSS United, to provide a technologist’s perspective on one of the most consequential debates shaping the future of artificial intelligence: the open versus closed source AI debate. Against the backdrop of a rapidly evolving AI landscape, this conversation examines risks, rewards, and the strategic implications of open-source AI for India.
Before diving into what an open approach to AI looks like in practice, we must first understand what “open-source AI” really means. Defining it is a complex and evolving effort involving plenty of debate, but creating a standard is helpful for providing clear guidelines, promoting transparency and trust, and accelerating innovation and collaboration. One formal definition that has emerged comes from the Open Source Initiative (OSI): the Open Source AI Definition (OSAID), which is a work in progress that we endorse.
Open source is more than freeware: According to the Open Source AI definition of the Open Source Initiative (OSI), a model is only open source if not only the model and the code to run it. But also the code and data (information) used to create the model have been published under an open source license
Die Open Source Business Alliance – Bundesverband für digitale Souveränität e.V. (OSBA) begrüßt die Initiative der Open Source Initiative (OSI) zur Schaffung einer Open Source AI Definition (OSAID). Die klare Definition und Abgrenzung offener KI-Modelle ist essenziell, um Transparenz, Nachvollziehbarkeit und Innovationsfreiheit in der KI-Entwicklung zu gewährleisten.
For their contribution to Maintainer Month, the OSI has collected nearly four dozen stories from maintainers to create a moment of visibility, publishing them all as a curated collection at OpenSource.org
The definition from the Open Source Initiative, which was only released in October 2024 after multiple years of research, is more specific. Users must be able to, for any purpose, use the system without having to ask permission, understand how it works, modify it, and share it with others, either with or without modifications. All these statements must apply to the model’s source code, parameters and weights, and detailed information about its training data.
Last summer, the Open Source Initiative and Open Future convened a group of experts to explore this challenge and propose a path forward. A recently released report from the convening, “Data Governance in Open Source AI” argues that collective action is needed to release more data and improve data governance to balance open sharing with responsible release.
Adding the GNU Affero General Public License (AGPL) as an additional licensing option for Redis, starting with Redis 8, the business said it is moving to a licensing model approved as open source by the Open Source Initiative (OSI) – as the Server Side Public License (SSPLv1) it switched to in March last year has remained outside the accepted definition of open source software.
