4 Contributo in Atti di Convegno (Proceeding)

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Advancements and Challenges in Generative AI: Architectures, Applications, and Ethical Implications

Architecture, classification, and major applications of Generative AI interfaces, specifically chatbots, are presented in this paper. Research paper details how the Generative AI interfaces work with various Generative AI approaches and show the architecture and their working. On the other hand, the generative model is built using advanced machine learning techniques to build dynamic, contextually relevant responses automatically. On the other hand, the retrieval-based model builds up with de...

Artificial intelligence tools in the ongoing fight against bullying and cyberbullying: a multidisciplinary approach

The problem of bullying and cyberbullying is growing and is a phenomenon that negatively influences our society: for this reason, it requires advanced solutions aimed at prevention. Starting from a previous project called BullyBuster which paved the way for the application of artificial intelligence (AI) in this area, exploiting interdisciplinary skills to develop algorithms capable of identifying and mitigating bullying behaviours, in this paper, we present the follow-up, called BullyBuster ...

Responsibile and Reliable AI: Activities of the CINI-AIIS Lab at University of Naples Federico II

Over the course of the last decade, AI researchers have made groundbreaking progress in hard and longstanding problems related to machine learning, computer vision, speech recognition, and autonomous systems. Despite the success of AI, its adoption so far is mostly in low-risk applications, while the uptake in medium/high-risk applications, which might have a deeper transformative impact on our society, such as in healthcare, public administration, safety-critical industries etc., is still lo...

AI in Medicine: Activities of the CINI-AIIS Lab at University of Naples Federico II

Artificial Intelligence (AI) encompasses a variety of methods and algorithms that have found applications across numerous domains over time. The increasing complexity and abundance of data in healthcare have spurred investigations into utilizing AI techniques within the medical field, leading to promising avenues for fostering innovation, facilitating early diagnosis, and aiding in treatments. In this study, we provide a concise overview of several initiatives conducted within this realm at t...

AI in Industry: Activities of the CINI-AIIS Lab at University of Naples Federico II

Artificial intelligence (AI) is reshaping the manufacturing landscape, offering opportunities for efficiency improvements and innovation. Through Machine Learning (ML) and Deep Learning (DL), AI enables predictive maintenance, anomaly detection, and image analysis in industrial settings. ML algorithms empower systems to learn from data, facilitating predictive maintenance by predicting optimal equipment servicing schedules based on operational conditions. DL techniques, including Convolutiona...

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