Video/Webinars
Webinar "Towards Transparent, Safe and Trustworthy AI for critical infrastructures"
This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.
Video/Webinars
Webinar "Industry-driven Use Cases"
AI4REALNET project covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic control), modelled by networks that can be simulated and traditionally operated by humans and where AI complements a
Video/Webinars
Webinar "Distributed and Hierarchical Reinforcement Learning"
In this webinar, AI4REALNET project provides an overview of two emerging topics in Reinforcement Learning (RL): Distributed RL and Hierarchical RL.
Article/Books/eBooks
Don’t ask if AI is good or fair, ask how it shifts power
Opinion piece by Pratyusha Kalluri in Nature
Article/Books/eBooks
An overview of key trustworthiness attributes and KPIs for trusted ML-based systems engineering
When deployed, machine-learning (ML) adoption depends on its ability to actually deliver the expected service safely, and to meet user expectations in terms of quality and continuity of service.
Article/Books/eBooks
Cooperating with machines
Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go).