AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
294 papers indexed here
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This study designs a qualitative survey aimed at software startup educators at Universities, and gathers enough information so it can help the academic community in improving their own courses.
A conceptual model to explain for coop competition among software firms in OSS projects is proposed and shows two aspects of coopetition can be managed at the same time based on firm gatekeepers.
A multi-vocal literature review focusing on practitioner literature is conducted in order to compile a list of metrics used by software startups, intended to serve as a basis for further research in the area.
This paper discusses a research framework for implementing AI ethics in industrial settings and presents a starting point for empirical studies into AI ethics but is still being developed further based on its practical utilization.
An empirical study on the current state of practice in artificial intelligence ethics is conducted by means of a multiple case study of five case companies, which indicates a gap between research and practice in the area.
Software Engineers work using highly diverse methods and practices, and general theories in software engineering are lacking. A recent attempt at creating a common ground in the area of software engineering methodologies has been the Essence Theory of Software Engineering. Essence is a method-agnostic progress management framework and a meta-method for Software Engineering (SE). However, tooling for Essence is still lacking. Without dedicated tools and other instruments, a meta-method such as Essence is cumbersome to utilize by practitioners and students. Indeed, Essence currently suffers from a lack of widespread practitioner adoption. In this paper, we thus present an Open Source tool for essentializing methods and practices: Essencery. We conduct a qualitative evaluation of the tool through a quasi-formal experiment and a set of semi-structured interviews. Based on this data, we improve Essencery iteratively before it is utilized in a large-scale project-based course as a proof of concept.
This paper provides a baseline for ethics in AI based software development by reporting results from an industrial multiple case study on AI systems development in the health care sector, and explores the current state of practice out on the field in the absence of formal methods and tools for ethically aligned design.
An overview of the trends driving the transition to focusing on effectiveness is provided, the challenges that companies experience as well as the requirements for a successful transformation are discussed.
It is found that the key conditions for making these blockchain-based solutions viable are attaining technological maturity and competences, ecosystem thinking and adequate governance of these ecosystems, and finally (3) achieving legal and regulatory predictability.
A holistic view of an iterative, continuous approach to develop industrial AI software basing on business goals, requirements and Minimum Viable Products is described and a research agenda with seven questions for future studies is proposed.
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