AI Application
Artificial intelligence (AI) applications are rapidly transforming various sectors, driven by advancements in model architectures like large language models (LLMs) and deep learning, and a focus on efficient data management and deployment. Current research emphasizes responsible AI development, including addressing ethical concerns, mitigating biases, and ensuring trustworthiness through standardized documentation and robust testing frameworks. This work holds significant implications for improving efficiency and decision-making across diverse fields, from healthcare and finance to manufacturing and autonomous systems, while simultaneously highlighting the need for careful consideration of societal impact and potential risks.
Papers
Reducing the Barriers to Entry for Foundation Model Training
Paolo Faraboschi, Ellis Giles, Justin Hotard, Konstanty Owczarek, Andrew Wheeler
Artificial Intelligence in Everyday Life 2.0: Educating University Students from Different Majors
Maria Kasinidou, Styliani Kleanthous, Matteo Busso, Marcelo Rodas, Jahna Otterbacher, Fausto Giunchiglia
Farsight: Fostering Responsible AI Awareness During AI Application Prototyping
Zijie J. Wang, Chinmay Kulkarni, Lauren Wilcox, Michael Terry, Michael Madaio
Harnessing the Computing Continuum across Personalized Healthcare, Maintenance and Inspection, and Farming 4.0
Fatemeh Baghdadi, Davide Cirillo, Daniele Lezzi, Francesc Lordan, Fernando Vazquez, Eugenio Lomurno, Alberto Archetti, Danilo Ardagna, Matteo Matteucci
A Comprehensive Review of Artificial Intelligence Applications in Major Retinal Conditions
Hina Raja, Taimur Hassan, Bilal Hassan, Muhammad Usman Akram, Hira Raja, Alaa A Abd-alrazaq, Siamak Yousefi, Naoufel Werghi
Artificial Intelligence in the Service of Entrepreneurial Finance: Knowledge Structure and the Foundational Algorithmic Paradigm
Robert Kudelić, Tamara Šmaguc, Sherry Robinson