Generative AI in Science, Engineering, and Technology Innovation

Abstract: Generative AI advances science, engineering, and technology by enabling data-driven design, simulation, and decision support to boost discovery and innovation. It offers opportunities for rapid advancements through foundation models for data, text, images, code, and design, enhancing creativity and expanding problem-solving for designers and engineers. Generative modeling creates instances from training data while generative design uses optimization algorithms for feasible iterations in representations and geometries. While prevalent in arts and entertainment, GAI is becoming essential in scientific and engineering fields, where creativity drives breakthroughs through associative thinking and new phenomenon imagination. GAI-powered models provide extensive computational strengths and multimedia capabilities to enhance AI-assisted engineering, broadening design and discovery across various criteria. This expansion facilitates scientific research, design exploration, and technological innovation in areas like system modeling, code generation, and generative design. A GAI-enabled designer follows three steps: questioning a challenge, exploring digital solutions, and instructing GAI on desired styles to steer outcomes. "The right design" is about exploration in the correct domain for the posed question, while "the design right" emphasizes directing the generative process to shape results effectively. (K. Hong et al., 2023) Keywords: Generative AI advances science, engineering, and technology through data-driven design, simulation, and decision support to accelerate discovery, innovation, and practical impact.