Mamba, an AI model, has been found to solve key sequence tasks faster than other AI models.
The selective state space models (SSMs) used in Mamba are efficient in solving synthetic tasks, language modeling, DNA modeling, audio modeling and generation.
Mamba demonstrates computational efficiency in training and inference processes.
Mamba's selective SSM layer enables perfect performance in the induction heads task, outperforming other models.