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.
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.
Posted by email@example.com (Josh Adragna) on 10/2/17
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.
Posted by Divya Susarla on 9/27/17
Business leaders are becoming more keen to evaluate A.I. solutions. Based on our conversations in the market and being an A.I. provider, here is a list of things to consider when evaluating A.I for customer support.
Posted by Divya Susarla on 9/26/17