The memBrain™ neuromorphic memory product by SST is a groundbreaking solution tailored for artificial intelligence applications, particularly at the network edge. As AI tasks migrate from cloud-based servers to battery-operated, embedded devices, there is a growing need for efficient memory solutions to handle complex AI operations like video and voice recognition.\n\nmemBrain leverages the principles of deep neural networks (DNNs) by storing necessary weights in local storage through its analog compute-in-memory approach. This method allows for vast multiplication-accumulate operations to occur efficiently within the memory cell itself, alleviating traditional digital processors' limitations. As a result, memBrain significantly reduces system latency by minimizing off-chip DRAM interaction, concurrently achieving a notable power reduction compared to traditional DSP-based solutions.\n\nIncorporating memBrain into devices provides numerous economic and performance advantages. It reduces both the bill of materials cost and the power consumption, offering up to 20 times the power efficiency of previous digital methods. This neuromorphic memory is particularly apt for AI edge applications where low latency and high efficiency are paramount, exemplifying SST's forefront position in embedded memory technologies.
