The rate coefficient of an inelastic collision, a.k.a. chemical reaction, can be determined by a non-linear Arrhenius-like mathematical relation. This is mathematically similar to the weights in an artificial neural network (ANN) determined by the activation functions. Therefore, a chemical pathway network (CPN) that massive chemical species are connected by the cause-effect chemical reaction pathways and share a similar mathematical ability with ANN: a functional mapping between the input space and output space. One can thus consider the CPN of material with enough complication of chemical reactions as an ANN and apply the machine learning (ML) technique on it to train, in other words, program the material for specific purposes. This approaches to a new type of intelligent material that is programmable and is different from others on the market that is merely basic logic embedded in the design of material for specific and fixed purposes. The programmability can make the intelligent material hardware that can switch to one of its software to complete a mission alone. In this work, we derived the theoretical general equations to show how a CPN can be a functional of mapping and how to practically program the CPN by finding the optimal parameters such as the temperature and pressure as the weights of the CPN. As an example, to demonstrate this theory, we propose a programmable material intelligence by training a He-air plasma, considering the CPN as an ANN, to play the board game Tic-Tac-Toe. In each turn, the board information is sent to the plasma discharge units by feeding a gas combination, and the plasma returns spectra to show its next move. After training, the plasma shows a significantly high winning rate when playing against a random-move player in a 500-game test. This means that the plasma learned to make logical decisions with strategy. As fewer and fewer move number is required for the plasma to finish its opponent, the decisions of intelligent plasma are more and more aggressive. The plasma finally even concludes that the best defense is a good offense by itself. This work thus reveals the potential of any matter that has a complicated chemical reaction system that can be used as a carrier of artificial intelligence. In other words, a material can be programmed and process data through its own molecular collisions, and thus can be considered an analog computer at the molecular level.