Alexandra Covaci

Boyd Branch, Piotr Mirowski, Kory Mathewson et al.

Social robotics researchers are increasingly interested in multi-party trained conversational agents. With a growing demand for real-world evaluations, our study presents Large Language Models (LLMs) deployed in a month-long live show at the Edinburgh Festival Fringe. This case study investigates human improvisers co-creating with conversational agents in a professional theatre setting. We explore the technical capabilities and constraints of on-the-spot multi-party dialogue, providing comprehensive insights from both audience and performer experiences with AI on stage. Our human-in-the-loop methodology underlines the challenges of these LLMs in generating context-relevant responses, stressing the user interface's crucial role. Audience feedback indicates an evolving interest for AI-driven live entertainment, direct human-AI interaction, and a diverse range of expectations about AI's conversational competence and utility as a creativity support tool. Human performers express immense enthusiasm, varied satisfaction, and the evolving public opinion highlights mixed emotions about AI's role in arts.

A. Xygkou-Tsiamoulou, Alexandra Covaci, Zeqi Jia et al.

As humanity pivots toward long-duration interplanetary travel, the psychological constraints of Isolated and Confined Environments (ICE) emerge as a primary mission risk. This paper presents COSMIC (COmpanion System for Mission Interaction and Communication) representing the inaugural investigation into the deployment of a high-fidelity, emotionally intelligent AI companion in an analog astronaut setting. By integrating a Large Language Model (LLM) architecture with a diffusion-based digital avatar interface, COSMIC transcends traditional task-oriented automation to provide longitudinal affective support. We detail a modular system architecture designed for temporal continuity through short- and long-term memory systems and outline a robust naturalistic observational framework for evaluating psychological resilience at the LunAres Research Station. This work constitutes the first formal submission in the field to evaluate the efficacy of state-of-the-art generative AI and synthesized visual empathy in mitigating the effects of extreme isolation.

Alexandra Covaci, Simone Madeo, Patrick Motylinski et al.

Blockchain-driven technologies are considered disruptive because of the availability of dis-intermediated, censorship-resistant and tamper-proof digital platforms of distributed trust. Among these technologies, smart contract platforms have the potential to take over functions usually done by intermediaries like banks, escrow or legal services. In this paper, we introduce a novel protocol aiming to execute smart contracts as part of a blockchain transaction validation. We enable extensions in the execution of smart contracts while guaranteeing their privacy, correctness and verifiability. Man-in-the-middle attacks are prevented, since no communication between participants is requested, and contract validations do not imply the re-execution of the code by all the nodes in the network. However, proofs of correct execution are stored on the blockchain and can be verified by multiple parties. Our solution is based on programming tools which optimize the time execution and the required memory while preserving the embedded functionality.