Introduction
GenAI and the potential to augment engineering
Working alongside other tools, technologies and methodologies, GenAI can make a transformative contribution across the product lifecycle
The collections we published last year were showcases of our work across a number of different industries and disciplines.
This one is different. Its pages are united by a theme – and that theme is Generative AI (GenAI), and the extent to which, in conjunction with other technologies, it can augment engineering, taking processes and outputs to entirely new levels.
Introducing Hybrid AI
What do we mean by this? Let’s expand on it a little. Augmented engineering involves using technology not to replace human endeavor, but to enhance and accelerate it. We can merge GenAI with complementary types of artificial intelligence, including discriminative AI, contextual AI, and symbolic reasoning, and also with other types of engineering and scientific models, including automation. The result is a powerful and transformative approach that we call Hybrid AI.
In this collection, we present a set of handpicked demonstrators to illustrate the extent to which Hybrid AI can achieve business transformation by boosting performance at different stages of the product lifecycle – from research, through concept, design, and development, to in-service support and maintenance.
The stories you will see here demonstrate how Hybrid AI can be used at each of these stages to do things smarter, faster, and more efficiently by:
Exploiting the past: unveiling and harnessing decades of structured and unstructured data within engineering organizations, learning from invaluable but often overlooked knowledge to improve the quality of actions and outcomes
Optimizing the present: increasing engineering efficiency to tackle pressing business priorities while laying down robust foundations for further development
Defining the future: creating new product categories, fostering innovation, and developing competitive advantage in new ways
Game-changing and foundational
It’s not just about processing information, but about putting it to work to create new things – new products, new drugs, new software designs, new applications, new processes. It’s about identifying the most and least promising options from a wide body of knowledge to focus effort and facilitate creativity. It’s about GenAI-enabled iterative and incremental processes of discovery, design, and decision-making that help to accelerate how you think and what you do.
And of course, the standards for which professional engineering is known – precision, regulation, industrial standards, and willingness to take calculated risks – are just as relevant to the application of GenAI tools and technologies.
The contribution that GenAI can make to this hybrid model is nothing less than foundational. By incorporating it into Hybrid AI and bringing it together with engineering domain expertise, with transformation methodologies, and with cutting-edge digital assets and ecosystems, we can craft and implement programs that can result in immediate action, but that at the same time can deliver long-term strategies.
