Natural language understanding: Difference between revisions

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Natural Language Understanding (NLU) is a a misleading term, highly discussed in the Conversational AI / scientific community.
Natural Language Understanding (NLU) is a a misleading term, highly discussed in the Conversational AI / scientific community.


In recent years, especially in the chatbot engineering industry, we tend to use NLU to mean an intent/entities classifier, based on machine learning techniques (transformers, etc.). The main open source project / state of the art of this approach is probably the RASA DIET classifier.
In recent years, especially in the chatbot engineering industry, we tend to use NLU to mean an intent/entities classifier, based on machine learning techniques (transformers, etc.). The main open source project / state of the art of this approach is probably the [https://rasa.com/blog/introducing-dual-intent-and-entity-transformer-diet-state-of-the-art-performance-on-a-lightweight-architecture/ RASA DIET classifier].


Besides, in terms of linguistic, and psycho-linguistic/cognitive scientific disciplines, there is a great skepticism about naming "language understanding" a ML-based classifier of intents (and entities). A growing number of researcher linguists state that it's even impossible to understand language with machine language techniques (the more famous and currently debated is probably GPT-3). One of the scientist more active in this battle is [https://ontologik.medium.com/ Walid Saba].
Besides, in terms of linguistic, and psycho-linguistic/cognitive scientific disciplines, there is a great skepticism about naming "language understanding" a ML-based classifier of intents (and entities). A growing number of researcher linguists state that it's even impossible to understand language with machine language techniques (the more famous and currently debated is probably GPT-3). One of the scientist more active in this battle is [https://ontologik.medium.com/ Walid Saba].

Revision as of 16:55, 9 December 2021

Natural Language Understanding (NLU) is a a misleading term, highly discussed in the Conversational AI / scientific community.

In recent years, especially in the chatbot engineering industry, we tend to use NLU to mean an intent/entities classifier, based on machine learning techniques (transformers, etc.). The main open source project / state of the art of this approach is probably the RASA DIET classifier.

Besides, in terms of linguistic, and psycho-linguistic/cognitive scientific disciplines, there is a great skepticism about naming "language understanding" a ML-based classifier of intents (and entities). A growing number of researcher linguists state that it's even impossible to understand language with machine language techniques (the more famous and currently debated is probably GPT-3). One of the scientist more active in this battle is Walid Saba.