In the last twenty years, a broad range of emerging memory technologies have been proposed as storage class memory (SCM) toward bridging the gap between high-performance memory and low-cost storage devices. Novel memory devices are also essential for developing low power, fast and accurate in-memory computing and neuromorphic engineering concepts that can compete with the conventional CMOS digital processors. 2D semiconductors, such as transition metal dichalcogenides (TMDs), provide a novel platform for advanced semiconductors, thanks to their atomic-scale thickness and their strong potential for 3D integration [1]. We present a three-terminal device called memtransistor, based on multilayer MoS2 with ultra-short channel length. Depending on the channel length (Lchannel) and the physics mechanism exploited, the device can be used as a memory [2] or as a powerful computing device [3,4]. When the distance between the two drain and source terminals is below 50 nm, the device exhibits a switching characteristic thanks to the Ag cation migration between the two electrodes. This device is called ion-based memtransistor to distinguish it from the electron-based memtransistor in which charge trapping is exploited to obtain an analog synaptic characteristic. The last device has a longer channel to avoid the ion migration between source and drain terminals. Thanks to the switching characteristic with independent control of the two resistive states, and the three-terminal structure, the ion-based memtransistor has been used in a chain-type memory array architecture where the individual memory devices along the chain can be selected for write and read [2]. This experiment paves the way for high-density, 3D memories based on 2D semiconductors. The charge trapping is instead exploited to obtain the synaptic characteristics with the electron-based memtransistor [4]. Synaptic potentiation/depression are obtained moving the device threshold and analogically changing the channel conductance. The linearity of the characteristic, the low power operation and the scalability offered by the 2D semiconductor makes the device extremely promising for the implementation of hardware neural network accelerators [3]. In addition, the dynamic characteristic of the device is exploited for the realization of the reservoir in a reservoir computing (RC) system for image recognition. The results make the memtransistors a promising technology for future high-density neuromorphic computing concepts.