To Build a Smarter Chatbot, First Teach It a Second Language

Posted by Shayaan Abdullah on 10/4/17

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.

Read More

Topics: Artificial Intelligence, Machine Learning, Sentiment Analysis

Formulating an A.I. Strategy

Posted by Josh Adragna on 10/2/17

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.

Read More

Topics: Artificial Intelligence

The Beginner’s Guide to Text Vectorization

Posted by Divya Susarla on 9/27/17

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.

Read More

Topics: Machine Learning, natural language processing, text vectorization

Evaluating A.I. for Customer Support

Posted by Divya Susarla on 9/26/17

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.

Read More

Topics: Artificial Intelligence, Customer Support

The Machine Learning BIOD-ome

Posted by Sinan Ozdemir on 9/25/17

Business leaders from a wide variety of industries and from companies both large and small are feeling the pressure to implement viable and effective AI strategies to keep up with the many innovations happening in the field.

As a CTO and a former consultant in the data science and machine learning space, I often get asked the question, “How do I go about planning out and deploying a machine learning project at my company?” Most of the time, managers do not have intimate familiarity with machine learning or how to apply machine learning to their business problems. When I get asked this, I almost always reply with a simple answer, “BIOD”.

Read More

Topics: Artificial Intelligence, Machine Learning, Customer Support