Frequently Asked Questions
Multimodal AI is a type of artificial intelligence that processes and combines multiple data types—such as text, images, audio, video, and sensor inputs, within a single model to produce more accurate and context-rich outputs.
It uses a combination of specialized encoders to process each data type, then applies fusion techniques (like attention mechanisms) to align and integrate the information into a shared representation for analysis and prediction.
Unimodal AI focuses on one data type (like only text or only images), while multimodal AI can handle several data types at once, offering deeper context understanding and human-like reasoning.
It improves decision-making, enhances user experiences, supports automation of complex tasks, enables richer data analysis, and helps organizations innovate faster across multiple industries.
Sectors like Healthcare, Finance, Retail, Manufacturing, Education, and Autonomous Driving are actively adopting multimodal AI for use cases ranging from diagnostics to predictive analytics.
