From text and vision to touch and brain interfaces: exploring every way AI can perceive and interact with the world.
These modalities are production-ready today, powering applications from chatbots to autonomous vehicles.
The foundation of modern AI. Large language models (LLMs) process and generate human language with remarkable fluency.
Understanding and analyzing images, from object recognition to complex scene interpretation and visual reasoning.
Processing speech, music, and environmental sounds. Includes speech-to-text, text-to-speech, and audio understanding.
Understanding video content and generating video from text or images. Rapidly advancing in 2024-2025.
Creating images from text descriptions using diffusion models and transformers.
Understanding and generating 3D content, spatial relationships, and augmented reality elements.
Models that combine multiple modalities in a single architecture, enabling richer understanding and generation.
Natively trained end-to-end on text, vision, and audio. 232ms voice response time.
First truly omni model with real-time voice
Supports all four major input types with 1M+ token context. Native multimodal training.
Most versatile multimodal context window
Safety-focused multimodal model with strong reasoning. Constitutional AI alignment.
Industry-leading safety and helpfulness balance
Generates high-resolution video with synchronized audio, music, and dialogue.
First text-to-video with native audio
Open-source multimodal model. 11B and 90B vision variants available.
Leading open-source multimodal option
The next frontier: sensory modalities currently in research that will expand AI's perceptual abilities. Ericsson predicts 2030 as the year of the "Internet of Senses."
Digitizing tactile sensations for robotics, VR, and prosthetics. Enabling AI to understand and simulate touch.
Digital scent technology for food, healthcare, and immersive experiences. Early research in molecular detection.
Digital taste simulation for food science, medical applications, and virtual dining experiences.
Body position and movement sensing. Critical for robotics, rehabilitation, and embodied AI.
Internal body sensing: heartbeat, breathing, hunger, temperature. Foundation for health AI.
Direct neural interfaces for thought-based control, sensory restoration, and cognitive enhancement.
Sensing radio waves, magnetic fields, and electrical signals invisible to humans.
Understanding and predicting molecular structures, drug interactions, and chemical reactions.
Human intelligence is inherently multimodal. We don't just process text—we see, hear, touch, smell, and sense our bodies in space. The expansion of AI modalities is not just about adding features; it's about moving toward systems that understand the world as richly as we do.
Current research suggests that truly general AI will need to integrate information across all sensory modalities, understanding how sight relates to sound, how touch informs movement, and how internal states affect cognition. The journey from text-only GPT to omni-modal systems is just the beginning.
FullAI provides access to cutting-edge models across text, vision, and more. Join the multimodal revolution.
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