Sep 2026· AI-Driven Plant Biotechnology· pp. 159-180
Abstract
Artificial Intelligence (AI) has revolutionized plant systems biology via the possible combination of multi-omics data, higher-order modeling, and autonomous hypothesis construction. Through deep learning, machine learning, and hybrid models, AI interprets complex genotype–phenotype connections and aids predictive modeling of plant growth and development, metabolism, and environmental acclimatization. Multiscale and multi-omics merged models provide deeper insights into gene regulation, signaling, and metabolism, and generative and graph-based models provide dynamical and causal inference. Autonomous phenotyping based on AI, digital twin plants, and CRISPR genome editing optimizes crop improvement, environmental tolerance, and resource-efficient agriculture. Although data standardization, interpretation, and ethical regulation are issues, AI’s significance endures based on the improvement of precision agriculture, sustainability, and global food security. AI, IoT, and quantum computing intersection point offers a brilliant future of integrative, data-driven, and ethically responsible plant biology.
Some claim that especially in the field of agile software development the research lags years behind of the practice. In this paper, we characterize the status and main challenges for research on agile software development, and propose a preliminary roadmap, focusing on providing more empirical research, primarily on e...
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The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.
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This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
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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.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
