Whether you need an illustration for your next social media post, or a sketch of a new product that’s in development, creating the right image content is vital. It used to be a challenge as well…but artificial intelligence (AI) is busy making it simple.
Photo by Elena Mozhvilo on Unsplash
Stunning images are being created by multimodal AI, where text, images, video, and audio converge. This type of content creation provides experts and amateurs alike with the ability to share their stories and imaginations visually.
If multimodal content is a new concept for you, we’ll begin with a definition.
An Introduction to Multimodal AI
Multimodal AI refers to a system or application that uses several types of data to generate content. Depending on the type of data that’s made available, a multimodal system may even be able to make accurate predictions and generate insights for a particular subject.
Multimodal models can handle several types of input, including text, images, video and speech. For example, if a multimodal model is given several photographs of green bean casserole, it should be able to generate a recipe for the dish upon request.
Previous AI models, such as the now-famous ChatGPT chatbot and its growing list of competitors, can only produce text content from text prompts. This is because it’s powered by a large language model (LLM) system.
Instead of an LLM system, multimodal AI is powered by convolutional neural networks (CNNs) that have been developed to work particularly well with image interpretation and creation.
The Power of Multimodal Content: Why Text Alone’s Not Enough
Multimodality provides you with the power to tap into an AI-powered, humanized approach to sights and sounds. Your creativity is only limited by your ability to work with your preferred multimodal application (more about those later).
Here are several reasons why multimodal content is becoming the preferred type of online medium.
Enhanced Comprehension: Humans process visual information 60,000 times faster than text. In addition, viewers retain 95% of a video’s message, compared to 10% when reading the text version.
Increased Engagement: A site or article with video content keeps viewers watching five times longer than text-only posts.
More Accessibility: Audio versions of articles or video captions make content accessible to those with visual or hearing impairments.
Emotional Connections: Music, voice inflections, and visuals can evoke emotions in ways that text cannot.
Now that we have a clearer picture of what multimodal content can achieve, here are some of the current methods used to create it.
The AI Revolution in Multimodal Creation
Artificial intelligence is making it easier for more people to create multimodal content. Developers have created some powerful tools that don’t require users to attend training or have similar experiences.
Let’s explore some of the exciting developments in AI-powered content creation:
AI-Generated Images
If you can create a text prompt for ChatGPT or Gemini, you can create images. Online tools like DALL-E 3, Midjourney, and Stable Diffusion have revolutionized image creation.
After analyzing a simple text prompt, these AI models can generate stunning, original artwork, illustrations, and photorealistic images. This technology is currently creating these types of images:
- Custom illustrations for articles and social media posts
- Unique product mockups for e-commerce
- Personalized visual content for marketing campaigns
Want to take things further? Check out these innovative video methods.
Multimodal Video Creation
Video production is being streamlined by AI-powered platforms, tools and apps.
- Platforms like Synthesia and D-ID can turn scripts into presenter-led videos with realistic AI avatars.
- Tools like Runway ML use AI to automate tasks like background removal, object tracking, and generating drone-like footage. You can view a three-minute demo video by clicking here.
- Platforms like Animaker leverage AI to simplify the creation of animated educational “explainer” videos and infographics. Choose from hundreds of existing templates and characters and thousands of music tracks.
AI in Audio Production
The audio landscape is also being transformed by AI users and video producers alike. Not everybody likes the sound of their own voice.
- Natural-sounding AI voices from companies like WellSaid Labs and Resemble AI can turn text into speech. It’s ideal for converting your articles into podcasts or providing voiceovers for videos.
- AI-powered tools like Adobe’s Project Awesome Audio can clean up audio, remove background noise, and even generate realistic sound effects.
Join the Multimodal Movement
The next wave of AI-generated content is here, and it’s multimodal and fascinating.
AI Detectors for Multimodal Content Assurance
As AI technology develops and creates increasingly complex multimodal content, ensuring its authenticity and quality becomes essential. AI detectors have quickly become critical tools in this landscape, analyzing and verifying the authenticity of AI-generated images, videos, and audio content.
These detectors use sophisticated algorithms to recognize inconsistencies, artifacts, and signs of manipulation that might compromise content’s authenticity. AI detectors use deep learning and pattern recognition techniques to differentiate between human-created content and AI-generated media, helping maintain trust and credibility within digital media. As multimodal content becomes increasingly prevalent, this technology becomes even more essential to ensure creators and consumers alike can rely on its integrity.
