AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice  

作　　者：Mitra Madanchian Hamed Taherdoost 

机构地区：[1]Department of Arts,Communications and Social Sciences,University Canada West,Vancouver,BC V6Z 0E5,Canada [2]GUS Institute,Global University Systems,London,EC1N 2LX,UK [3]Hamta Group,Hamta Business Corporation,Vancouver,BC V6E 1C9,Canada [4]Q Minded,Quark Minded Technology Inc.,Vancouver,BC V6E 1C9,Canada

出　　处：《Computers, Materials & Continua》2024年第11期2133-2159,共27页计算机、材料和连续体（英文）

摘　　要：This comparative review explores the dynamic and evolving landscape of artificial intelligence(AI)-powered innovations within high-tech research and development(R&D).It delves into both theoreticalmodels and practical applications across a broad range of industries,including biotechnology,automotive,aerospace,and telecom-munications.By examining critical advancements in AI algorithms,machine learning,deep learning models,simulations,and predictive analytics,the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies.The review integrates both qualitative and quantitative data derived from academic studies,industry reports,and real-world case studies to showcase the tangible impacts of AI on product innovation,process optimization,and strategic decision-making.Notably,it discusses the challenges of integrating AI within complex industrial systems,such as ethical concerns,technical limitations,and the need for regulatory oversight.The findings reveal a mixed landscape where AI has significantly accelerated R&D processes,reduced costs,and enabled more precise simulations and predictions,but also highlighted gaps in knowledge transfer,skills adaptation,and cross-industry standardization.By bridging the gap between AI theory and practice,the review offers insights into the effectiveness,successes,and obstacles faced by organizations as they implement AI-driven solutions.Concluding with a forward-looking perspective,the review identifies emerging trends,future challenges,and promising opportunities inAI-poweredR&D,such as the rise of autonomous systems,AI-driven drug discovery,and sustainable energy solutions.It offers a holistic understanding of how AI is shaping the future of technological innovation and provides actionable insights for researchers,engineers,and policymakers involved in high-tech Research and Development(R&D).

关 键 词：Deep learning high-tech research and development theoretical models practical applications neural networks predictive analytics innovation strategies 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]