Understanding Multimodal AI: Overview, Workflow, and Practical Applications
At its core, Multimodal AI is an artificial intelligence approach designed to process, integrate, and make sense of several types of data, known as modalities, at the same time. Traditional (or unimodal ) AI systems are built to do one thing well with one specific format: analyze text, recognize images, or process audio files. Multimodal AI breaks out of these silos. By combining information from several formats simultaneously, it develops a far richer, more realistic understanding of complex scenarios. Think of OpenAI’s GPT-4 Vision (GPT-4V) as a classic example. Instead of just reading text prompts, it can look at an image, read an accompanying caption, and generate a response that draws insights from both inputs at once. Common Data Modalities ● Text: Articles, chat logs, transcripts, and social media posts. ● Images: Photographs, diagrams, illustrations, and single frames from videos. ● ...