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

Gabriele Tolomei, Cesare Campagnano, Fabrizio Silvestri, Giovanni Trappolini
{"title":"Prompt-to-OS (P2OS): Revolutionizing Operating Systems and Human-Computer Interaction with Integrated AI Generative Models","authors":"Gabriele Tolomei, Cesare Campagnano, Fabrizio Silvestri, Giovanni Trappolini","doi":"arxiv-2310.04875","DOIUrl":null,"url":null,"abstract":"In this paper, we present a groundbreaking paradigm for human-computer\ninteraction that revolutionizes the traditional notion of an operating system. Within this innovative framework, user requests issued to the machine are\nhandled by an interconnected ecosystem of generative AI models that seamlessly\nintegrate with or even replace traditional software applications. At the core\nof this paradigm shift are large generative models, such as language and\ndiffusion models, which serve as the central interface between users and\ncomputers. This pioneering approach leverages the abilities of advanced\nlanguage models, empowering users to engage in natural language conversations\nwith their computing devices. Users can articulate their intentions, tasks, and\ninquiries directly to the system, eliminating the need for explicit commands or\ncomplex navigation. The language model comprehends and interprets the user's\nprompts, generating and displaying contextual and meaningful responses that\nfacilitate seamless and intuitive interactions. This paradigm shift not only streamlines user interactions but also opens up\nnew possibilities for personalized experiences. Generative models can adapt to\nindividual preferences, learning from user input and continuously improving\ntheir understanding and response generation. Furthermore, it enables enhanced\naccessibility, as users can interact with the system using speech or text,\naccommodating diverse communication preferences. However, this visionary concept raises significant challenges, including\nprivacy, security, trustability, and the ethical use of generative models.\nRobust safeguards must be in place to protect user data and prevent potential\nmisuse or manipulation of the language model. While the full realization of this paradigm is still far from being achieved,\nthis paper serves as a starting point for envisioning this transformative\npotential.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"39 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Operating Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2310.04875","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this 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. 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 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 this transformative potential.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
即时操作系统(P2OS):革命性的操作系统和集成人工智能生成模型的人机交互
在本文中,我们提出了一个开创性的人机交互范例,它彻底改变了操作系统的传统概念。在这个创新的框架中,用户向机器发出的请求由一个由生成式人工智能模型组成的互联生态系统处理,这些模型与传统的软件应用程序无缝集成,甚至取代传统的软件应用程序。这种范式转变的核心是大型生成模型,如语言和扩散模型,它们作为用户和计算机之间的中心接口。这种开创性的方法利用了高级语言模型的能力,使用户能够与他们的计算设备进行自然语言对话。用户可以直接向系统表达他们的意图、任务和查询,从而消除了明确命令或复杂导航的需要。语言模型理解和解释用户的提示,生成和显示上下文和有意义的响应,促进无缝和直观的交互。这种模式的转变不仅简化了用户交互,而且为个性化体验开辟了新的可能性。生成模型可以适应个人偏好,从用户输入中学习,并不断提高他们的理解和响应生成。此外,它还增强了可访问性,因为用户可以使用语音或文本与系统交互,以适应不同的通信偏好。然而,这个有远见的概念提出了重大挑战,包括隐私、安全、可信赖性和生成模型的道德使用。必须有强大的保护措施来保护用户数据并防止对语言模型的潜在滥用或操纵。虽然这种范式的完全实现仍远未实现,但本文可以作为设想这种变革潜力的起点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Analysis of Synchronization Mechanisms in Operating Systems Skip TLB flushes for reused pages within mmap's eBPF-mm: Userspace-guided memory management in Linux with eBPF BULKHEAD: Secure, Scalable, and Efficient Kernel Compartmentalization with PKS Rethinking Programmed I/O for Fast Devices, Cheap Cores, and Coherent Interconnects
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1