Key-value storage systems are essential for modern applications, offering high performance and scalability to efficiently manage and retrieve growing data volumes. 

Deep learning compilers optimize neural networks comprehensively considering hardware's intrinsic characteristics to boost AI performance and enable efficient deployment.

Edge AI deploys AI on local devices, reducing latency and bandwidth use while enhancing privacy and enabling real-time applications. 

Solid-State Drive (SSD) are high-speed storage devices that use flash memory to store data, offering faster read/write speeds, better durability, and lower power consumption compared to traditional hard drives. 

A neural network pipeline organizes the stages of data preprocessing, model training, and inference, and the use of an external knowledge base, ensuring efficient or effective data flow for AI applications. 

Unstructured data can be managed and handled efficiently via vector database engines for the use-cases of recommendation or retrieval information systems