Speaker
Adam Thompson
(NVIDIA)
Description
The Universe’s radio sky is rich with transient phenomena, but conventional surveys often depend on classical filtering and dedispersion techniques, potentially overlooking novel signals. We present a pipeline that bypasses these traditional steps by streaming RF data directly from telescope digitizers into GPU-accelerated AI models, enabling real-time detection directly on raw spectrograms. This end-to-end AI workflow streamlines model training, curation, and deployment, achieving both high performance and scalability. By eliminating classical pre-processing, our approach has the potential to simplify development, enhance discovery, and facilitate scalability.
