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For example, there is a prototype, photonic, quantum memristive device for neuromorphic (quantum-)computers (NC)/artificial neural networks and NC-using quantum materials with some variety of potential neuromorphic computing-related applications, [367] [368] and quantum machine learning is a field with some variety of applications under ...
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...
The high-level architecture of IBM's DeepQA used in Watson [9]. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering.
Applications for this architecture are much less common than MIMD and SIMD, as the latter two are often more appropriate for common data parallel techniques. Specifically, they allow better scaling and use of computational resources. However, one prominent example of MISD in computing are the Space Shuttle flight control computers. [2]
Depth of processing falls on a shallow to deep continuum. [citation needed] Shallow processing (e.g., processing based on phonemic and orthographic components) leads to a fragile memory trace that is susceptible to rapid decay. Conversely, deep processing (e.g., semantic processing) results in a more durable memory trace. [1]
Multi-Agent systems, e.g. artificial life, the study of simulated life; Electric power systems, e.g. Condition Monitoring Multi-Agent System (COMMAS) applied to transformer condition monitoring, and IntelliTEAM II Automatic Restoration System [7] DAI integration in tools has included: ECStar is a distributed rule-based learning system. [8]
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DeepDream is a computer vision program created by Google engineer Alexander Mordvintsev that uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia, thus creating a dream-like appearance reminiscent of a psychedelic experience in the deliberately overprocessed images.