Native Multimodal
Foundations.
The transition to end-to-end models that experience data natively. It removes the need to translate sensory inputs into text, allowing AI to process and reason through audio and visual data directly.
Speech-to-Speech
The removal of the text transcription bottleneck. By training models to reason directly within audio tokens, the latency of speech-to-text-to-speech is bypassed for deeply fluid conversations.
Acoustic Comprehension
Models designed to natively ingest, tokenize, and understand raw audio signals in real time, making them instantly ready for high-fidelity generation without intermediate text layers.
Vision-Language Navigation
The visual perception layer for AI agents. It gives models the ability to 'see' graphical interfaces, allowing them to autonomously navigate CRMs and software tools to execute complex actions.