A Yale University research team proposed a new type of open licenses CCAI (Contextual Copyleft), which extends the application of copyleft to generative AI models. The idea behind CCAI is that using content under this license as training data for machine learning results in the propagation of copyleft terms to the resulting generative AI models. It is expected that the new license may help reduce abuses in AI projects and prevent the emergence of bogus AI models that are formally presented as open but are tied to their producers due to the concealment of raw data and training tools. <\/p>\n
CCAI states that any distribution and publication of exact copies or modified derivative works distributed under the CCAI license must be done under the same licensing terms without any additional restrictions. This requirement applies to any AI model, dataset, or AI system that has used software licensed under CCAI or the results of its operation during training. In the context of training generative AI models, CCAI demands the disclosure of the model's source code, a detailed description of the data used in training, parameters, weights, and model architecture. <\/p>\n
The CCAI license can also be used as an additional requirement attached to existing copyleft licenses, such as AGPLv3. This requirement expands the license's applicability to training datasets, code, and model weights in accordance with the openness criteria for AI systems formulated by the Open Source Initiative (OSI). Code distributed under such a license can only be used for training an AI model if all users are provided with a description of the training dataset, the code for training the model, and the trained AI model. <\/p>\n
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Forr\u00e1s: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"