Cortical.io has developed a unique approach to natural language understanding (NLU) called Semantic Folding, that combines high accuracy, efficiency, flexibility and transparency.
Semantic Folding describes a method of converting language from its symbolic representation (text) into an explicit, semantically grounded representation called a semantic fingerprint. This change in representation can solve many complex NLU problems by applying Boolean operators and a generic similarity function like Euclidian Distance.
Many practical problems of statistical NLU systems and, more recently, of Transformer models, like the necessity of creating large training data sets, the high cost of computation, the fundamental incongruity of precision and recall, the complex tuning procedures, etc., can be elegantly overcome by applying Semantic Folding. This white paper shows how Semantic Folding transforms Natural Language Understanding.
