MLP is "Multimodal Learning and Perception".

Our work in artificial intelligence is centered around the concept of multimodality. We are pioneering the integration of diverse sensory data into cohesive learning models, harnessing the power of multiple sensory inputs to enhance the depth and accuracy of our AI systems. By combining visual, auditory, and tactile data, our models gain a richer and more nuanced understanding of the environment, significantly improving object detection, tracking, and classification capabilities, even in challenging conditions.

This multimodal approach is integral to our continual and zero-shot learning innovations with large language models (LLMs). Our AI systems are not just limited to processing visual data but are adept at interpreting and correlating information across different sensory modalities. This holistic processing capability enables our models to adapt to new scenarios in real-time and make informed decisions based on a comprehensive sensory analysis. The collaboration of experts from various disciplines in our team ensures that we continue to push the boundaries of what's possible in multimodal AI, leading to more intuitive, robust, and versatile AI systems.