TokEye: Fast Signal Extraction for Fluctuating Time Series via Offline Self-Supervised Learning From Fusion Diagnostics to Bioacoustics

Researchers developed TokEye, a self-supervised AI framework that can extract coherent signals from noisy time-series data in 0.5 seconds, initially designed for fusion reactor diagnostics. The system demonstrates applications beyond fusion research, including bioacoustics, suggesting broader potential for real-time signal processing across industries.