AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,489 papers
It is suggested that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.
A key finding from the study indicates that simply the presence of an ethical tool has an effect on ethical consideration, creating more responsibility even in instances where the use of the tool is not intrinsically motivated.
This paper begins to address the focal problem of implementing ethics into AI system design and development in practice by providing elements needed for producing a baseline for ethics in AI based software development by means of an industrial multiple case study on AI systems development in the healthcare sector.
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The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
This investigation revealed different types of AI systems and different AI development approaches, but it is common that business opportunities involving with AI systems are not validated and there is lack of business-driven metrics that guide the development ofAI systems.
The Second International Workshop on Requirement Engineering for Software startups and Emerging Technologies (RESET) brought together requirements engineering researchers and practitioners to discuss the need for adapting conventional requirement engineering artifacts in developing and operating emerging technologies.
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
A unified platform that utilizes multiple artificial intelligence agents to automate the process of transforming user requirements into well-organized deliverables, including user stories, prioritization, and UML sequence diagrams, along with the modular approach to APIs, unit tests, and end-to-end tests.
A web-based software tool utilizing AI agents and prompt engineering to automate task prioritization and apply diverse prioritization techniques, aimed at enhancing project management within the agile framework is introduced.
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Results corroborate the effectiveness of LLMs in improving and streamlining RE phases by analyzing the semantic similarity and API performance of different models, as well as their effectiveness and efficiency in requirements analysis.
In a new book, Professor Eric So explores how the technology affects our thinking skills.
Earth AI
GPT-Lab
· gpt-lab.eu
Oct 14, 2026
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Professor Deb Roy contends there should be someone who is “answerable” for every piece of text in public life, no matter its origins.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
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