  We report the results from our ongoing pilot investigation of the use of deep
learning techniques for forecasting the state of turbulent flows onto black
holes. Deep neural networks seem to learn well black hole accretion physics and
evolve the accretion flow orders of magnitude faster than traditional numerical
solvers, while maintaining a reasonable accuracy for a long time.
