Multimodal learning / multimodal AI

• Multimodal AI - or multimodal learning - mimics the human brain’s ability to simultaneously process textual, visual, and audio information, enabling a more nuanced understanding of reality.
• Transitioning from a unimodal model (like those specialized in text, images, or sounds) to a multimodal model presents technical challenges, particularly in creating shared representations for different types of data.
• Multimodal AI offers advantages such as capturing more comprehensive knowledge of the environment and enabling new applications, like merging data from various modalities for complex tasks.

Read also on Hello Future

AI: challenges faced by developers of automated systems to moderate hate speech

Discover
Close-up of a woman in a white coat carefully looking through the eyepiece of a black microscope, with her right eye aligned.

Efficient, lightweight computer vision models for innovative applications

Discover
Illustration of a smiling robot emerging from a large smartphone screen, reaching out to a seated man with a

The drive to simulate human behaviour in AI agents

Discover

Omnimodal AI: a game-changer for customer relations

Discover

AI therapy: marketing hype and the hidden risks for users

Discover

A lexicon of artificial intelligence: understanding different AIs and their uses

Discover