In our mission to help our clients achieve remarkable customer experiences, we’ve focused some of our attention into tackling the repetitive questions your customer support teams receive. The Kylie.ai Bubble is a quick and easy way to divert those repetitive FAQ questions that bog down your customer support agents.
This blog post was originally posted on MIT Technology Review by Will Knight
From Alexa and Siri to countless chatbots and automated customer support lines, computers are gradually learning to talk. The only trouble is they are still very easily confused.
A research team at Salesforce has come up with a clever way to improve the performance of many modern language programs—teaching an algorithm to speak another language before training it to do other tasks.
You already know that a decision that is backed by some analysis and data is usually better than a decision that comes purely from the gut. So when you need to make a decision on ways of improving your customer success experience, you need some data to work with. Most organizations employ some twitter usage in their customer success, some more than others. That’s why it’s important to do some analysis on incoming tweets and how well they are replied to.
Evaluating artificial intelligence in the enterprise can seem like a daunting task. The Kylie.ai team has worked with several leading organizations and has learned key insights in how to approach evaluating A.I. The following points can provide guidance and best practices in how to formulate an A.I. strategy.
Topics: Artificial Intelligence
This blog post was originally posted on MonkeyLearn by Rodrigo Stecanella
Since the beginning of the brief history of Natural Language Processing (NLP), there has been the need to transform text into something a machine can understand. That is, transforming text into a meaningful vector (or array) of numbers. The de-facto standard way of doing this in the pre-deep learning era was to use a bag of words approach.