We used advanced text-to-image generation techniques to create designs for "Fluttertoy," a concept brand of children's toys inspired by the appearance of the butterfly. The goal of this project was to assess the capabilities of generative AI models in producing novel and appealing visual designs for Fluttertoy products that are both visually interesting.
Our prompts yielded a vast array of designs, which effectively demonstrated the potential of utilizing text-to-image models during the initial stages of developing new products, particularly for consumer products where a distinct visual aesthetic is a crucial aspect of its appeal. The collage below showcases a selection of the various Fluttertoy concepts that we generated through this method.
The collage below shows another set of designs that were generated, showcasing the variety of design concepts that may be obtained using this method.
The purpose of the toy concepts generated using this approach is not immediately apparent and is up to the designer to decide. The next step in the idea management process is to infer the function from the design. Creating a large number of such designs can encourage the designer to think creatively and explore new possibilities. Such designs can also be used as part of a market research activity or focus group exercise to generate new insights into potential new products. We refer to this process as reverse ideation.
This post is part of a series of articles on the use of generative AI for bioinspired product ideation. The use of AI for product concept generation allows for the quick creation of many potentially novel designs, which could then be evaluated and refined to select the most promising concepts to move to the next stage of the product development process.
To learn how leading Fortune Global 500 companies such as ABB, Bosch, Google, Samsung, and NetApp have used Innomantra's Functional Innovation Methodology to turbocharge their idea management process, schedule a meeting today at calendly.com/innomantra.
Post a Comment