Our recent paper introduces an innovative approach, based on the SPARC technique, which leverages machine learning algorithms to adaptively select a reduced kinetic mechanism for each computational cell in Large Eddy Simulations (LES) of turbulent reacting flows. This innovative methodology significantly reduces the computational cost of LES, offering a promising avenue for more efficient and accurate simulations of turbulent reacting flows, particularly in combustion research.