The Struggle with Typography in Generative AI
Generative AI models have been incredibly successful in creating visual images, from photographs to illustrations. However, when it comes to typography, these models have historically faced significant challenges. The text generated by these AI models often appears distorted, with letters duplicated or garbled, making it almost unreadable.
Recent Advances in Text Coherence
Over the last six months, there have been notable improvements in text coherence across various generative AI platforms. Two models that stand out for their advancements in this area are Ideogram and Flux Pro. These models have been integrated into Euryka, allowing users to explore their capabilities in depth.
Examples of Improved Typography
To demonstrate the improvements, we recently created movie quote posters using Ideogram, Flux Pro, DALL-E, Midjourney, and Stable Diffusion. Here’s how each model performed:
Round 1: The Terminator
Prompt: A typographical poster with the quote "I'll be back" in the style of the movie "The Terminator". The text is in a bold, futuristic font and is white. The background is a dark, metallic blue. There is a small, white silhouette of a Terminator in the background.
As you can see, Midjourney favours the design, almost ignoring the prompt instructions. SD3 got some parts right but couldn’t reproduce the name of the movie properly. Dall-E decided to mock up the poster and got the spellings wrong. Flux Pro came close to the instructions, but the futuristic font seemed more circus-like. Ideogram was the one that followed the prompt and had the desired effect.
Winner Round 1: Ideogram
Round 2: Star Wars
Prompt: A poster with the quote "May the Force be with you" from "Star Wars". There is a light saber battle going on in the background. The background is a galaxy with stars and planets. The text is in the style of a cinematic title.
As usual, Midjourney refused to follow the prompt, showing a recurring pattern. SD3 got the text right but aesthetically didn’t have the same effect. Dall-E did better this time, creating its own interpretation of the prompt and the movie reference. Flux Pro got the text right, and the background image was relatable. Ideogram knocked it out of the park by creating the text in the famous Star Wars style, along with a proper cinematic background we expect from the Star Wars movie franchise.
Winner Round 2: Ideogram
Round 3: Casablanca
Prompt: A vintage movie poster with the quote "Here's looking at you, kid" from "Casablanca". The text is in white and is placed over a blue background. The background contains a silhouette of a man with a fedora hat and a woman with a fur coat. The overall design has a retro feel.
This time, Midjourney got the text right (the only one from the four it generated). SD3 is not cutting it. Dall-E struggled with the words. Flux Pro got closest to the text prompt, and Ideogram achieved the perfect balance between getting the words right and the retro aesthetic.
Winner Round 3: Ideogram, Flux Pro
Round 4: Taxi Driver
Prompt: A vintage-style poster with the quote "You talkin' to me?" from the movie "Taxi Driver". There's a silhouette of a man with a mohawk, wearing a red jacket and sunglasses. The background is a city skyline with tall buildings. The text is in a bold, retro font.
This round is subjective. Each of the models reproduced the text in its own unique style, following the vintage poster prompt instruction. Flux Pro and Ideogram created the most visually appealing of the options.
Winner Round 3: Tie! Flux Pro and Ideogram
Challenges and Limitations
Despite these improvements, generative AI still faces several challenges when it comes to typography:
- Lack of Control and Predictability: AI systems can generate unique fonts, but they often lack the control and predictability that human designers take for granted. This can result in inconsistent or aesthetically unappealing outputs.
- Copyright Infringement: AI-generated fonts can sometimes infringe on existing font copyrights, raising legal concerns. Ensuring that AI models use training data free from unlicensed content is crucial.
- Emotional Nuances: AI struggles to capture the subtle nuances and emotions that a human designer can infuse into their work. This makes AI-generated fonts less expressive and less capable of conveying the intended message.
- Data Quality: The quality and diversity of the training data are critical. Biases in the training data can lead to biased outputs, and the scarcity of high-quality datasets is a significant challenge.
Creative Workarounds
To navigate these challenges, designers are exploring creative workarounds:
- Integrating AI-Generated Icons:
- Using AI to generate icons that can be integrated into letter shapes can enhance typography. This method allows designers to add custom elements to their fonts, making them more visually appealing.
- Using AI to generate icons that can be integrated into letter shapes can enhance typography. This method allows designers to add custom elements to their fonts, making them more visually appealing.
- Complementary AI Backgrounds:
- Creating AI-generated backgrounds that complement the typography can help balance the design. This approach ensures that the text stands out while the background adds visual appeal.
- Creating AI-generated backgrounds that complement the typography can help balance the design. This approach ensures that the text stands out while the background adds visual appeal.
- Morphing Letter Forms:
- Combining AI-generated textures and effects with letter forms can create unique and captivating typography. This method allows designers to add a creative twist to their fonts.
- Combining AI-generated textures and effects with letter forms can create unique and captivating typography. This method allows designers to add a creative twist to their fonts.
- Font Completion:
- AI can be used for font completion, also known as “Few-shot font generation” or “Font style transfer”. This involves completing a font alphabet using only a few reference glyphs, which can be particularly useful for localising fonts for different languages.
Future of AI in Typography
As generative AI continues to evolve, it is likely to have a profound impact on the design and marketing industry. Here are some potential future developments:
- Automation and Efficiency: AI can automate tedious tasks in font production, allowing designers to focus on more creative aspects. This could lead to faster production rates and more innovative designs.
- Latent Space Interpolation: AI models can use latent space interpolation to help designers discover new styles between existing fonts. This could open up new possibilities for type design.
- Multimodal Generation: AI can enable multimodal generation, allowing fonts to be used in new and innovative ways by graphic designers, brand designers, and editorial designers.
By understanding these challenges and exploring creative workarounds, designers can harness the power of generative AI to create unique and captivating typography, while also navigating the ethical and legal complexities involved.