AI-powered UI that evolves based on user habits, reducing clutter and improving usability.

AI analyzes market trends and audience sentiment to suggest branding elements like logos, fonts, and slogans.

Helps models concentrate on the most relevant features of the input data, improving the quality of outputs.

AI fine-tunes kerning, leading, and spacing to achieve perfect readability and aesthetics without manual tweaking.

AI suggests microcopy, button labels, and user-friendly prompts to enhance usability.

Refers to systematic errors that can lead to unfair outcomes, often stemming from the data used to train models.

AI’s attempt at being the next Picasso. Computational creativity refers to AI systems that generate original content, from art to music and even branding concepts.

A magic eraser for designers. AI analyzes surrounding pixels to intelligently remove and replace objects in an image, making photo editing feel like a breeze.

Understands the meaning behind images and text, enhancing its ability to make relevant design choices.

AI-generated code that translates artistic concepts into interactive experiences.

Involves expanding your dataset by making slight modifications to existing data, enhancing the diversity and robustness of your designs.

Letting AI analyze user behavior to suggest design improvements, ensuring layouts, colors, and features resonate with audiences.

AI-generated media where someone in an existing image or video is replaced with someone else's likeness, often used to create deceptive visuals.

Generate data by progressively transforming simple patterns into complex structures, often used in image synthesis.

Trained to differentiate between various categories of data, enhancing the accuracy of design classifications.

Scans facial expressions or user reactions to assess how visuals impact emotions.

Ensures AI-generated visuals are inclusive, diverse, and free from bias, avoiding problematic stereotypes.

Focuses on making AI decisions transparent and understandable.

Are large-scale AI models trained on broad data, adaptable to multiple tasks with minimal fine-tuning.

Consist of two neural networks—the generator and the discriminator—that work together to produce increasingly realistic outputs.

Uses algorithms to explore all possible permutations of a solution, quickly generating design alternatives.

AI-created typefaces that morph and adapt based on input, mood, or user interaction.

Ensuring AI-enhanced designs put user experience and accessibility first.

AI that looks at an image and writes a relevant description, helping with accessibility and searchability.

Are AI models trained on extensive text data, capable of understanding and generating human-like language.

Processes and integrates multiple types of data, enhancing its understanding and generation capabilities.

Applies the style of one image to the content of another, creating a unique blend of both.

Enables the extraction of text from images or scanned documents, facilitating easy editing and searching.

Tailoring visuals to each user. AI dynamically adjusts interfaces, colors, or layouts based on user behavior and preferences.

AI forecasts design trends based on social media engagement, market research, and cultural shifts.

Involves designing inputs to guide AI models toward generating desired outputs, crucial for effective AI-human interaction.

Involves an AI model learning to make decisions by receiving rewards or penalties, optimizing its actions over time.

AI-generated wireframes that take your ideas and instantly turn them into interactive prototypes, helping teams visualize concepts quickly.

Rough doodles become polished designs. AI identifies sketches and turns them into vector art or wireframes.

A type of GAN that generates new images based on artistic themes, often used to create photorealistic faces or unique abstract compositions.

Involves training AI models on labeled data, where the correct answers are provided, enabling accurate predictions.

AI models (like DALL·E and Midjourney) transform words into stunning visuals, revolutionizing concept art and brainstorming.

Allows AI models to apply knowledge gained from one task to another related task, accelerating the learning process.

Involves AI models identifying hidden patterns in data without labeled examples, leading to novel insights.

Speak your edits into existence. AI listens and executes commands, making design tools hands-free.