View source for 18092694. NEUROMORPHIC COMPUTING SYSTEM FOR EDGE COMPUTING simplified abstract (GM Cruise Holdings LLC)

=NEUROMORPHIC COMPUTING SYSTEM FOR EDGE COMPUTING=


==Organization Name==

[[:Category:GM Cruise Holdings LLC|GM Cruise Holdings LLC]]


[[Category:GM Cruise Holdings LLC]]

==Inventor(s)==

[[:Category:Juan Nunez of Palo Alto CA (US)|Juan Nunez of Palo Alto CA (US)]][[Category:Juan Nunez of Palo Alto CA (US)]]

==NEUROMORPHIC COMPUTING SYSTEM FOR EDGE COMPUTING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18092694 titled 'NEUROMORPHIC COMPUTING SYSTEM FOR EDGE COMPUTING

==Simplified Explanation==
The patent application describes systems and techniques for neuromorphic computing at edge devices like sensor systems. This includes a sensor collecting data, a neuromorphic compute platform with processing circuitry and memory circuitry, and neural networks processing the sensor data.

* Sensor collects data
* Neuromorphic compute platform includes processing circuitry and memory circuitry
* Neural networks process sensor data

==Key Features and Innovation==
* Integration of processing circuitry, memory circuitry, and communication channels in a neuromorphic compute platform
* Implementation of neural networks for processing sensor data at edge devices like sensor systems

==Potential Applications==
The technology can be used in various applications such as:
* Internet of Things (IoT) devices
* Autonomous vehicles
* Robotics
* Healthcare monitoring systems

==Problems Solved==
* Efficient processing of sensor data at edge devices
* Real-time decision-making based on sensor inputs

==Benefits==
* Reduced latency in data processing
* Improved accuracy in decision-making
* Enhanced performance of edge devices

==Commercial Applications==
### Neuromorphic Computing for Edge Devices: Revolutionizing Sensor Systems and IoT

The technology can be commercially applied in:
* Smart home devices
* Industrial automation
* Environmental monitoring systems

==Prior Art==
Further research can be conducted in the field of neuromorphic computing, edge devices, and sensor systems to explore existing technologies and innovations.

==Frequently Updated Research==
Stay updated on advancements in neuromorphic computing, edge computing, and sensor technology to enhance the implementation of this technology.

==Questions about Neuromorphic Computing at Edge Devices==
===What are the potential challenges in implementing neuromorphic computing at edge devices?===
Implementing neuromorphic computing at edge devices may face challenges related to power consumption, scalability, and compatibility with existing systems. Solutions to these challenges require further research and development.

===How does neuromorphic computing differ from traditional computing methods in processing sensor data at edge devices?===
Neuromorphic computing mimics the structure and function of the human brain, enabling efficient and parallel processing of sensor data at edge devices. This differs from traditional computing methods by offering low-power consumption and real-time decision-making capabilities.


==Original Abstract Submitted==

Systems and techniques are provided for neuromorphic computing at edge devices such as sensor systems. An example system can include a sensor configured to collect sensor data; a neuromorphic compute platform including processing circuitry collocated with memory circuitry and communication channels interconnecting the processing circuitry and the memory circuitry; and one or more neural networks implemented by the neuromorphic compute platform, wherein the one or more neural networks are configured to process the sensor data from the sensor.



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