Neuromorphic Chips


Computer Engineering; Information Systems


Neuromorphic chips are a new generation of computer processors being designed to emulate the way that the brain works. Instead of being locked into a single architecture of binary signals, neuromorphic chips can form and dissolve connections based on their environment, in effect “learning” from their surroundings. These chips are needed for complex tasks such as image recognition, navigation, and problem solving.


Neuromorphic chips are designed to detect and predict patterns in data and processing pathways to improve future computing.

Neuromorphic chips are designed to detect and predict patterns in data and processing pathways to improve future computing. They simulate the brain's neuroplasticity, allowing for efficient abstraction and analysis of visual and auditory patterns. Each of the chips on this board has hundreds of millions of connections mimicking the synapses that connect neurons.
By DARPA SyNAPSE, public domain, via Wikimedia Commons.

In order to design neuromorphic chips, engineers draw upon scientific research about the brain and how it functions. One group doing such research is the Human Brain Project (HBP). HBP is trying to build working models of a rodent brain. Eventually HBP will try to build a fully working model of a human brain. Having models like these will allow scientists to test hypotheses about how the brain works. Their research will aid in the development of computer chips that can mimic such operations.


One reason researchers have begun to develop neuromorphic chips is that the designs of traditional chips are approaching the limits of their computational power. For many years, efforts were focused on developing computers capable of the type of learning and insights that the human brain can accomplish. These efforts were made on both the hardware and the software side. Programmers designed applications and operating systems to use data storage and access algorithms like those found in the neural networks of the brain. Chip designers found ways to make circuits smaller and smaller so they could be ever more densely packed onto conventional chips. Unfortunately, both approaches have failed to produce machines that have either the brain's information processing power or its neuroplasticity. Neuroplasticity is the brain's ability to continuously change itself and improve at tasks through repetition.


Neuromorphic chips are especially suitable for computing tasks that have proven too intense for traditional chips to handle. These tasks include speech-to-text translation, facial recognition, and so-called smart navigation. All of these applications require a computer with a large amount of processing power and the ability to make guesses about current and future decisions based on past decisions. Because neuromorphic chips are still in the design and experimentation phase, many more uses for them have yet to emerge.


Neuromorphic chips represent an answer to the computing questions that the future poses. Most of the computing applications being developed require more than the ability to process large amounts of data. This capability already exists. Instead, they require a device that can use data in many different forms to draw conclusions about the environment. The computers of the future will be expected to act more like human brains, so they will need to be designed and built more like brains.

—Scott Zimmer, JD

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