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IBM Watson Assistant provides better intent classification than other commercial products according to published study | by Nicolo Cosimo Albanese | Jan, 2021

And how the better performances of IBM Watson Assistant tackle the most common pain points in the adoption of a conversational solution

Nicolo Cosimo Albanese
Photo by Alex Knight on Unsplash
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Example of intents and utterances. Table from Casanueva et al. (2020)¹²
Intent detection accuracy from different technologies on the same data set (HINT3). Image from Qi et al. (2020)¹¹.
Average In-scope Accuracy on HINT3 using commercial solutions. Table from Qi et al. (2020)¹¹.
Training time (minutes) vs accuracy reached by different NLU engines on the same dataset (CLINC150). In the conditions reported by the study, IBM Watson Assistant completed the training in 1.81 minutes, against the 70 minutes from BERT-base and the 270 minutes from BERT-large. Image from Qi et al. (2020)¹¹.

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