In content-based addressing, the weight used to read or write from a cell is a function of that cell. Using this, we can retrieve a complete vector-valued memory if we are able to produce a pattern that matches some but not all of its elements.

Content-Based Addressing

In location-based addressing, we can retrieve a complete vector-valued memory using the location of the content in the memory.

Location-Based Addressing

Memory networks were first introduced because neural networks lacked a working memory. They have a set of memory cells that can be easily accessed via an addressing mechanism.

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The working memory is the system that enables the ability to explicitly hold and manipulate pieces of information that are used to achieve a goal. Unlike humans, neural networks do not have a working memory.

Working Memory

Goodfellow, I., Bengio, Y., & Courville, A. (2016). $\mathit{Deep \ Learning.}$ MIT Press. Retrieved from [www.deeplearningbook.org](https://www.deeplearningbook.org) 

Deep Learning

Memory Network

Although the terms 'short-term memory' and 'working memory' are frequently used interchangeably, they represent distinct psychological concepts. Short-term memory specifically refers to the temporary storage system holding incoming sensory information. In contrast, working memory is a more comprehensive system that encompasses this temporary storage. Consequently, short-term memory is most accurately conceptualized as a sub-component operating within the larger working memory framework.

Distinction Between Short-Term Memory and Working Memory

Short-term memory (STM) serves as a temporary storage system that processes incoming information from sensory memory. It is capable of retaining a limited amount of data for a brief duration of 15 to 30 seconds. While in this active state, short-term memory can also integrate new sensory input with existing knowledge retrieved from long-term memory. Although often confused with working memory, short-term memory is more accurately classified as a distinct sub-component within the broader working memory framework.

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