As we have already observed, Facebook has developed a recognition model with 10 trillion parameters. Some of the Facebook’s DLRMs tend to be larger than dense generative models such as GPT-3 (175 billion parameters).
A recognition model determines to what class a pattern belongs to corresponding to the observed value x of the random variable X. In wars, planes were identified using these models. The model combines pattern matching and mental simulation.
Recognition and classification models both identify the patterns in the data. However, recognition focuses on identifying and locating specific objects or patterns in the given input. Classification assigns an input to a category based on its content. Recognition is more about detection, and classification more about categorization.
Recognition models are applied in handwriting recognition, speech recognition, image recognition, object recognition, human activity recognition, document processing and recognition.
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