When it comes to truly understanding the potential business benefits of AI, you need to take into account the subtle, but critical differences on the evolution of various techniques.
Early research into reading comprehension started in the late 1950s and has since evolved into the subject of Natural Language Processing (NLP). The objectives are to process significant amount of information, interpret questions correctly and answer them accurately.
The advances in text based machine learning techniques can potentially help in -
a) Intelligent Product Classification by understanding product names and descriptions etc.
b) Efficient Trade Compliance by identifying product category and corresponding tariff schedules
c) Add context to analytics around business processes by displaying notes/remarks as user tries to understand the analytics e.g. "Why a shipment is late?"
In regards to supply chain management, text-based Machine Learning techniques can inspire many use cases in Supply Chain Management. Intelligent Product Classification By running analysis over product names and descriptions, retail companies will be able to streamline the process of acquiring new merchandise, categorizing them, and then populating them on the correct pages of their online catalog Trade Compliance Accurate product classification is a compliance requirement when conducting international trade. Being able to decipher the human language as it relates to product information and tariff schedules – as well as being able to identify the accurate product category and recommend tariff codes will save enormous amount of time for companies.