This chapter delves into the concept of Solomonov induction and its connection to AGI, discussing the use of base theorem and the approximation capabilities of transformers and LSTMs. It also explores research papers comparing transformers with LSTM and RNNs, as well as the properties of Mamba as an alternative. Overall, it provides evidence supporting the capacity of neural networks in supporting Solomonov induction and AGI.