AI Models to the rescue

Product Recall is a big deal for food, medicine, manufacturing, and consumer electronic companies. In order to save an organization from losing its credibility and money, it is essential to utilize AI neural networks like the Recurrent Neural Network (RNN) and Latent Dirichlet Allocation (LDA) models that help process online customer reviews and fasten product changes.

RNNs are able to distinguish between positive and negative customer reviews along with reviews that contain product defects. LDAs can detect negative reviews and product defect information.

This week, I was successful in interpreting the results of Product Recall in manufacturing companies and how AI contributes to product efficiency.

Some challenges I faced were understanding new terminology and concepts such as neural networks, how RNN and LDA models work, and Receiver Operating Characteristic curves. I was able to learn these new terms and concepts by reading about them on Google and other sites. Thus, it took some time to really understand what was being presented in the article.

I would like to gain more insights into how AI helped businesses meet their customer demands efficiently. In addition, I am looking forward to the Business Symposium next week. I hope to gain more knowledge about the field, meet new students, and interact with professionals.