4 results about "Scalable architecture" patented technology

This invention discloses a general cognitive enhancement platform, system, method, and storage medium. The method includes: maintaining a scene registry, which stores the definition of at least one cognitive enhancement scene. Each scene definition includes a scene identifier, functional modules, a processing engine, and a pipeline mode; responding to requests to activate a specific cognitive enhancement scene; loading the corresponding functional modules and processing engine according to the scene definition in the scene registry and configuring the pipeline mode; processing input data through the processing engine to generate enhanced content via the functional modules; and presenting the enhanced content to the user. This invention also provides independent vision correction methods and systems, and real-time translation methods and systems. This invention achieves a scalable architecture for cognitive enhancement applications through a scene registry, solving the technical problems of closed architecture, lack of scalability, and repetitive functional development in existing technologies.

In one embodiment, an apparatus includes a first die adapted on a second die. The first die may have a plurality of cores, each of the plurality of cores associated with a first plurality of through silicon vias (TSVs), and the second die may have dynamic random access memory (DRAM). The DRAM of the second die may have a plurality of local portions, each of the plurality of local portions associated with a second plurality of TSVs, where each of at least some of the plurality of cores are directly coupled to a corresponding local portion of the DRAM by the corresponding first and second plurality of TSVs. Other embodiments are described and claimed.

Disclosed are methods and systems for automated generation of content distribution images, including receiving user input corresponding to a content distribution operation. The user input may be parsed to identify keywords. Image data corresponding to the keywords may be identified. An image processing operation may be performed on the image data. A generative adversarial network may be performed on the processed image data, the execution including running a first neural network on the processed image data to generate first images corresponding to the keywords, the first images being generated based on a likelihood that each of the first images would not have been detected as generated by the first neural network. A user interface may display the first images along with second images, including images that were previously part of the content distribution operation or images designated by an entity as available for the content distribution operation.