Nowadays the AI has reached human-like, or even better-than-human performances in tasks such as classification, recognition, etc.,so it is gaining more and more use in the everyday life. However, as of today, these networks run on non-dedicated hardware such as CPUs or GPUs, and to achieve such high results, these systems require a lot more power, time and area than necessary. Thus a lot of effort has been put into developing dedicated hardware, such as the digital accelerator TPU developed by Google, to drastically reduce the used resources. However, such accelerators still follow a Von-Neumann architecture, and the necessity of moving data from the memory to a processor is still a heavily limiting factor.