Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.

What is multimodal AI? Multimodal AI refers to machine learning models capable of processing and integrating information from multiple modalities or types of data. These modalities can include text, …

A multimodal agent may do this in multiple ways: through speech and intonation, facial expression and gaze, gesture, body movements and posture.

Jan 15, 2026 · What multimodal AI is and how it works Multimodal AI is emerging as part of the fast-moving world of AI technology, bringing together multiple types and modalities of data to build a …

Multimodal projects are simply projects that have multiple “modes” of communicating a message. For example, while traditional papers typically only have one mode (text), a multimodal project would …

Cities can gain many benefits from multimodal transportation, which encompasses all types of transport, from cars and buses to bikes and pedestrian traffic.

Dec 5, 2016 · The meaning of MULTIMODAL is having or involving several modes, modalities, or maxima. How to use multimodal in a sentence.

Jul 15, 2025 · Multimodal data is information that exists across multiple different formats or modalities simultaneously, including text, audio, image, video, and sensory or specialized data.

Jul 2, 2025 · At its core, multimodal learning involves leveraging multiple modalities of information to improve learning, understanding, and decision-making. A modality refers to a specific sensory …

May 29, 2024 · As technology advances and new media emerge, multimodal communication becomes increasingly relevant, enabling individuals and organizations to better engage with diverse audiences.