  We introduce deep learning time-series forecasting for gravitational wave
detection of binary neutron star mergers. This method enables the
identification of these signals in real advanced LIGO data up to 30 seconds
before merger. When applied to GW170817, our deep learning forecasting method
identifies the presence of this gravitational wave signal 10 seconds before
merger. This novel approach requires a single GPU for inference, and may be
used as part of an early warning system for time-sensitive multi-messenger
searches.
