The ongoing AI revolution is based on machine learning models that rely on vast artificial neural networks trained on enormous amounts of data. These models use a transformer architecture and are generated through an automated process of training. The model is comprised of two files, a simple run file that establishes the model architecture, and a much larger file of parameters or weights expressed as floating point numbers. Protecting copyright in the machine learning model weights faces a challenge due to their functional nature. However, the sui generis protection for databases established in Directive 96/9 provides a strong candidate for protecting model weights. To apply the EU sui generis database protection to machine learning models’ weights, one needs to establish that these can qualify as a database and that there is substantial investment in them by the database maker.
Source: Kluwer Copyright blog
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