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Recently, some members of the Diverso Lab attended the highly esteemed AAAI’23 conference in Washington DC, which focuses on artificial intelligence. Their visit served two purposes. Firstly, they presented their contribution, “FASTDIAGP: An Algorithm for Parallelized Direct Diagnosis,” which resulted from a collaboration with TU Graz and former PhD students from Chile. Secondly, they aimed

natural language processing field connecting the advances with software engineering topics. The talk addressed the role of scaling a deep learning model to achieve unprecedented results across the whole set of natural language processing evaluations. This exposition of the scaling principles began with the critical property of model parallelism and the attention mechanism, first