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OSI's draft definition seeks clarity amid growing confusion over what qualifies as open source AI, addressing concerns raised by restricted access models labeled as open source by tech giants like Meta.
The Open Source Initiative (OSI) has released a new draft definition for "open source AI" in an effort to clarify the often ambiguous use of the term. This move comes as tech giants like Meta release large language models with usage restrictions while still labeling them as open source, sparking debates among free-software advocates.
The OSI's latest draft definition aims to establish clear criteria for what constitutes "open source" in the context of AI. This is particularly important as more companies release AI models with varying degrees of openness and usage restrictions.
For practitioners, this clarification can have significant implications:
The draft emphasizes "four fundamental freedoms" inspired by the principles of free software:

The ambiguity in what constitutes "open source" in AI is highlighted by examples like Meta's Llama 3 model:
To address these issues formally, the OSI has assembled a group of about 70 participants, including:
Representatives from major tech companies like Meta, Google, and Amazon are also involved in this effort. The current draft (version 0.0.9) is the result of their collaborative work.
For developers and organizations using AI models:
The OSI's new draft definition for open source AI is a step towards clarifying the landscape of AI model licensing. By establishing clear criteria, it aims to promote transparency and foster a more collaborative development environment. As the debate continues, practitioners can benefit from a better understanding of what truly constitutes an open source AI model.
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About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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