Opportunities and Challenges of Generative Artificial Intelligence: Research, Education, Industry Engagement, and Social Impact

Generative Artificial Intelligence (Generative AI) is transforming the way we live and work. Following several decades of Artificial Narrow Intelligence, Generative AI is signalling a paradigm shift in the intelligence of machines, an increased generalisation capability with increased accessibility and equity for non-technical users. Large Language Models (LLMs) are leading this charge, specifically, conversational interfaces such as ChatGPT, Gemini, Claude and Llama. Besides language and text, robust and effective Generative AI models have emerged for all other modalities of digital data, image, video, audio, code, and combinations thereof. This article presents the opportunities and challenges of Generative AI in advancing industrial systems and technologies. The article begins with an introduction to Generative AI, which includes, its rapid progression to state-of-the-art, the deep learning algorithms, large training datasets and computing infrastructure used to build Generative AI models, as well as the technical limitations. The contribution, value and utility of Generative AI is presented in terms of its four capabilities of accelerating academic research, augmenting learning and teaching experience, supporting industry practice and increasing social impact. The article concludes with an expeditious message to the academic research and industry practitioner communities to invest time and effort in training, adoption and application of Generative AI, with consideration for AI literacy for all stakeholders, human-centricity and the responsible development and use of AI in industrial settings.