Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …

Hardware realization of artificial intelligence (AI) requires new design styles and even
underlying technologies than those used in traditional digital processors or logic circuits …

Can large language models produce expert‐quality philosophical texts? To investigate this,
we fine‐tuned GPT‐3 with the works of philosopher Daniel Dennett. To evaluate the model …

Artificial Intelligence (AI) and, in particular, Machine Learning (ML), have emerged to be
utilized in various applications due to their capability to learn how to solve complex …

As DNNs become increasingly common in mission-critical applications, ensuring their
reliable operation has become crucial. Conventional resilience techniques fail to account for …

Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …

Assessing the reliability of modern devices running CNN algorithms is a very difficult task.
Actually, the complexity of the state-of-the-art devices makes exhaustive Fault Injection (FI) …

Deep learning tasks cover a broad range of domains and an even more extensive range of
applications, from entertainment to extremely safety-critical fields. Thus, Deep Neural …

Abstract Nowadays, Convolutional Neural Networks (CNNs) are widely used as prediction
models in different fields, with intensive use in real-time safety-critical systems. Recent …

Artificial intelligence (AI) systems are increasingly popular in many applications.
Nevertheless, AI technologies are still develo**, and many issues need to be addressed …