View source for 17808921. DEEP LEARNING ACCESS AND AUTHENTICATION IN A COMPUTING ARCHITECTURE simplified abstract (MICRON TECHNOLOGY, INC.)

=DEEP LEARNING ACCESS AND AUTHENTICATION IN A COMPUTING ARCHITECTURE=


==Organization Name==

[[:Category:MICRON TECHNOLOGY, INC.|MICRON TECHNOLOGY, INC.]]


[[Category:MICRON TECHNOLOGY, INC.]]

==Inventor(s)==

[[:Category:Poorna Kale of Folsom CA (US)|Poorna Kale of Folsom CA (US)]][[Category:Poorna Kale of Folsom CA (US)]]

==DEEP LEARNING ACCESS AND AUTHENTICATION IN A COMPUTING ARCHITECTURE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17808921 titled 'DEEP LEARNING ACCESS AND AUTHENTICATION IN A COMPUTING ARCHITECTURE

==Simplified Explanation==

Methods, systems, and devices for deep learning access and authentication in a computing architecture are described in this patent application. The system consists of a processor, a deep learning device, and a memory system. The deep learning device uses a neural network to perform operations associated with the processor. The memory system controls access to the deep learning device by verifying the authorization of the processor and enabling or disabling access accordingly. If access is granted, the deep learning device performs the operations, and if access is denied, it is restricted from performing the operations.

* The patent application describes a system for deep learning access and authentication in a computing architecture.
* The system includes a processor, a deep learning device, and a memory system.
* The deep learning device uses a neural network to perform operations associated with the processor.
* The memory system verifies the authorization of the processor to access the deep learning device.
* Access to the deep learning device is enabled or disabled based on the verification.
* If access is granted, the deep learning device performs the operations, and if denied, it is restricted from performing the operations.

==Potential Applications==
This technology has potential applications in various fields, including:

* Artificial intelligence systems
* Machine learning platforms
* Deep learning applications
* Data analysis and processing systems
* Computer vision and image recognition systems

==Problems Solved==
The technology addresses the following problems:

* Unauthorized access to deep learning devices
* Ensuring secure and authorized usage of deep learning capabilities
* Preventing misuse or unauthorized operations on the deep learning device
* Enhancing the overall security and control of deep learning systems

==Benefits==
The technology offers several benefits, including:

* Improved security by controlling access to deep learning devices
* Enhanced authorization and authentication mechanisms for deep learning operations
* Prevention of unauthorized or malicious use of deep learning capabilities
* Increased control and management of deep learning resources within a computing architecture.


==Original Abstract Submitted==

Methods, systems, and devices for deep learning access and authentication in a computing architecture are described. A computing system a processor, a deep learning device, and a memory system. The deep learning device may be operable to perform operations associated with the processor using a neural network. The memory system enable or disable access to the deep learning device by the processor. For example, the memory system may verify whether the processor is authorized to access the deep learning device and enable or disable access based on the verification. If access is enabled, the deep learning device may perform the one or more operations associated with the processor. If access is disabled, the deep learning device may be restricted from performing the one or more operations associated with the processor.



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