When it comes to artificial intelligence and machine learning, we often think of factory halls where sensors and data can be used to optimize processes. Yet, other sectors can also benefit from AI systems. In the creative industry, for example, designers can work in radically different ways.
When new designers join an agency, they must first spend years mastering the agency's style. Creative design can be slow and, most importantly, expensive. Artificial intelligence can provide a solution because the technology can learn at lightning speed. An AI system can thus help conceptualize and prototype on the fly, with design and product teams working closely together. This results in faster design cycles, lower costs, higher quality and unlimited variations of selected designs in seconds.
One of the most critical aspects is training your model. Every company or agency has its own style, and you want the algorithm to have an understanding of your design philosophy. Only then can the output match your other designs.
Imagine, for example, interior design. House decorators need inspiration to design a living room. They can take pictures of a room and tell their AI model to create design variations. The algorithm can then replace specific furniture with better-fitting items, add a painting to the wall, or change the entire style of the living room. The more trained the model is on the task (interior design) and the style of the designer or company, the better the suggestions or variations will be.
The designer can use these suggestions to mix the best options and create a design, significantly speeding up the process and expanding creative opportunities. Sounds like fiction? It isn’t! We created a demo that you can test here.
This is just the beginning. Imagine a future where you have an AI that can incorporate your own products into designs! For example, a furniture manufacturer would be able to offer its customers the ability to visualize their dream living room with its products seamlessly integrated. While this is technically speaking not yet possible, it represents an exciting use case with tangible business value for companies.
Also in the broader design industry we see the potential for significant business value generation from AI assisted design. Skating and idea creation in Architectural design could help architects bring their vision to life, advertising campaigns could be crafted based on campaign goals and brand strategy, or fashion design could be supported by insights from customers’ preferences and the fashion brands’ look and feel.
Currently, we are at a tipping point when it comes to these AI models. Data creation is becoming easier, making models more powerful. Processing costs are decreasing and there’s more data available.
In particular, we are seeing the rise of so-called foundation models, such as Stable Diffusion or GPT3. These large AI models are trained on billions of data points and can be adapted to a wide range of other tasks. They serve as the foundation for many different models and use cases.
You can adapt these powerful but generic foundation models to a specific task or style. By doing so, they become powerful assistants to designers and create business value by proposing designs based on their input.
The fuel on which your AI model works is the data you feed it. In the case of designers, we’re talking about images of a specific task or in a specific style. However, collecting that data and converting it in the right format, often constitutes 80 to 90 percent of the budget. Fortunately, there are various tools and frameworks available that make this data process easier and faster. Fondant, the framework we developed at ML6, can help.
At ML6, we have experience in building custom AI models based on fine-tuning foundation models to meet your specific use case. Check out the solution we have built with Creative Fabrica. Are you interested in learning more? Reach out to us!