Extract from Tyler Maddry’s article “Open Source AI Models: How Open Are They Really? Part 1”
Although most generative AI models like ChatGPT and GitHub Copilot are proprietary, some AI providers have started to release AI models under an open source or similar licensing arrangement. Meta released its Llama AI model in early 2023, Google released Gemma in 2024, DeepSeek released R1 in January 2025, and there are several others. Using an open AI model can provide significant advantages, including avoidance of licensing fees and greater control over your data. However, adoption of open source AI is not as straightforward as using conventional open source software (OSS) because an AI model has more components than just the software. Building, understanding and modifying an AI model requires training data and the internal weights and parameters that are used for calculations during operation, and that is where open source AI starts to diverge from traditional OSS licensing.
Open Source Software Licensing
The OSS movement began back in the 1980s and 90s when Richard Stallman of MIT founded the Free Software Foundation and published the GPL 2.0 open source license. The Open Source Initiative (OSI) was formed in 1998 with one of its objectives to make OSS more accessible to a range of constituencies. Over the next few decades, the use of OSS increased substantially as programmers and businesses became more comfortable with the terms of the most popular OSS licenses.
