Platform for Situated Intelligence
This framework addresses the problem of building complex AI systems that integrate multiple data modalities, primarily for researchers and developers in AI and robotics, though it appears incremental as it builds on existing technologies rather than introducing a new paradigm.
The authors tackled the challenge of developing multimodal, integrative-AI systems by introducing an open-source framework that provides infrastructure for sensing, fusing, and inferring from temporal data streams, enabling rapid construction and refinement with efficiency for real-world deployment.
We introduce Platform for Situated Intelligence, an open-source framework created to support the rapid development and study of multimodal, integrative-AI systems. The framework provides infrastructure for sensing, fusing, and making inferences from temporal streams of data across different modalities, a set of tools that enable visualization and debugging, and an ecosystem of components that encapsulate a variety of perception and processing technologies. These assets jointly provide the means for rapidly constructing and refining multimodal, integrative-AI systems, while retaining the efficiency and performance characteristics required for deployment in open-world settings.