GAISE 2026: Reflections on AI, Software Engineering and Responsible Innovation
Set in Tampere during the Finnish summer, the three-day event brought together researchers, practitioners, industry leaders, and students to explore how generative AI is changing software engineering and organisational work. The post GAISE 2026: Reflections on AI, Software Engineering and Responsible Innovation appeared first on GPT-Lab.
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Building trustworthy AI: The role of AI harnesses, intent contracts and evals
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.
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AI-powered Code Review with LLMs: Early Results
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.
Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Large Language Model Evaluation Via Multi AI Agents: Preliminary results
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A Multiple Case Study of Artificial Intelligent System Development in Industry
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.