In this ambitious paper, we present a groundbreaking paradigm for human-computer interaction that revolutionizes the traditional notion of an operating system. Within this innovative framework, user requests issued to the machine are handled by an interconnected ecosystem of generative AI models that seamlessly integrate with or even replace traditional software applications. At the core of this paradigm shift are large generative models, such as language and diffusion models, which serve as the central interface between users and computers. This pioneering approach leverages the abilities of advanced language models, empowering users to engage in natural language conversations with their computing devices. By capitalizing on the power of language models, users can articulate their intentions, tasks, and inquiries directly to the system, eliminating the need for explicit commands or complex navigation. The language model comprehends and interprets the user's prompts, generating and displaying contextual and meaningful responses that facilitate seamless and intuitive interactions. This paradigm shift not only streamlines user interactions but also opens up new possibilities for personalized experiences. Generative models can adapt to individual preferences, learning from user input and continuously improving their understanding and response generation. Furthermore, it enables enhanced accessibility, as users can interact with the system using speech or text, accommodating diverse communication preferences. However, this visionary concept also raises significant challenges, including privacy, security, trustability, and the ethical use of generative models. Robust safeguards must be in place to protect user data and prevent potential misuse or manipulation of the language model. While the full realization of this paradigm is still far from being achieved, this paper serves as a starting point for envisioning the transformative potential of a human-computer interaction paradigm centered around artificial intelligence. We discuss the envisioned benefits, challenges, and implications, paving the way for future research and development in this exciting and promising direction.

Prompt-to-OS (P2OS): Revolutionizing Operating Systems and Human-Computer Interaction with Integrated AI Generative Models / Tolomei, Gabriele; Campagnano, Cesare; Silvestri, Fabrizio; Trappolini, Giovanni. - (2023), pp. 128-134. (Intervento presentato al convegno 2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI) tenutosi a Atlanta; USA) [10.1109/cogmi58952.2023.00027].

Prompt-to-OS (P2OS): Revolutionizing Operating Systems and Human-Computer Interaction with Integrated AI Generative Models

Tolomei, Gabriele
;
Campagnano, Cesare
;
Silvestri, Fabrizio
;
Trappolini, Giovanni
2023

Abstract

In this ambitious paper, we present a groundbreaking paradigm for human-computer interaction that revolutionizes the traditional notion of an operating system. Within this innovative framework, user requests issued to the machine are handled by an interconnected ecosystem of generative AI models that seamlessly integrate with or even replace traditional software applications. At the core of this paradigm shift are large generative models, such as language and diffusion models, which serve as the central interface between users and computers. This pioneering approach leverages the abilities of advanced language models, empowering users to engage in natural language conversations with their computing devices. By capitalizing on the power of language models, users can articulate their intentions, tasks, and inquiries directly to the system, eliminating the need for explicit commands or complex navigation. The language model comprehends and interprets the user's prompts, generating and displaying contextual and meaningful responses that facilitate seamless and intuitive interactions. This paradigm shift not only streamlines user interactions but also opens up new possibilities for personalized experiences. Generative models can adapt to individual preferences, learning from user input and continuously improving their understanding and response generation. Furthermore, it enables enhanced accessibility, as users can interact with the system using speech or text, accommodating diverse communication preferences. However, this visionary concept also raises significant challenges, including privacy, security, trustability, and the ethical use of generative models. Robust safeguards must be in place to protect user data and prevent potential misuse or manipulation of the language model. While the full realization of this paradigm is still far from being achieved, this paper serves as a starting point for envisioning the transformative potential of a human-computer interaction paradigm centered around artificial intelligence. We discuss the envisioned benefits, challenges, and implications, paving the way for future research and development in this exciting and promising direction.
2023
2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI)
AI generative models for operating systems; AI generative models for human-computer interaction; AI generative models as universal applications
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Prompt-to-OS (P2OS): Revolutionizing Operating Systems and Human-Computer Interaction with Integrated AI Generative Models / Tolomei, Gabriele; Campagnano, Cesare; Silvestri, Fabrizio; Trappolini, Giovanni. - (2023), pp. 128-134. (Intervento presentato al convegno 2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI) tenutosi a Atlanta; USA) [10.1109/cogmi58952.2023.00027].
File allegati a questo prodotto
File Dimensione Formato  
Tolomei_postprint_Prompt_2023.pdf

accesso aperto

Note: DOI: 10.1109/CogMI58952.2023.00027
Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 180.24 kB
Formato Adobe PDF
180.24 kB Adobe PDF
Tolomei_Prompt_2023.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 133.25 kB
Formato Adobe PDF
133.25 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1705588
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact