By combining a deep understanding of plasma physics with machine learning techniques, DIFFER researchers developed a new ultrafast neural network model of the turbulent plasma in a fusion reactor. The neural network can accurately predict heat and particle transport in the fusion reactor up to 100.000 times faster than before: a vital tool to optimize the performance of future fusion power plants. The prediction tool for heat and particle transport can also find applications in the following IPCs: for chemical and physical processes in general (stationary particles, moving particles, particles being subjected to vibrations or pulsations), where control of temperature is necessary.