Symanto Brain is based on zero- and few-shot technologies in accordance with the latest neural language models. Specifically, it uses semantic matching methods from a neural network with more than 300 million parameters and dozens of neural layers (deep neural network), trained with texts in more than 50 languages and fine-tuned for natural language inference, paraphrasing and other series of classification tasks (e.g., feeling, emotions, topic extraction, personality traits, etc.) in all types of data sources (e.g., social networks, reviews, news, etc.).
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Classes or also called labels, between which to discriminate (classify) the text, e.g.
Status colour Red title Negative Status colour Green title positive Patterns, also known as label descriptors, allow the semantic matching between the analysed text and the different labels, e.g.
This text is {}
Input: The product has no issues but the packaging causes so much extra to squirt out and you can't stop it. For how expensive it is it's such a waste.
Result:
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The key to Symanto Brain, and where the research is focused, is the adequate definition of the task to be addressed, that is, the adequate definition of semantically appropriate classes and the patterns that allow the matching. |
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