Mikio Braun looks back on the past 20 years of machine learning research to explore aspects of artificial intelligence. He then turns to current examples like autonomous cars and chatbots, putting together a mental model for a reference architecture for artificial intelligence systems.

In order to train deep learning and machine learning models, you must leverage applications such as TensorFlow, MXNet, Caffe, and XGBoost. Wangda Tan discusses new features in Apache Hadoop 3.x to better support deep learning workloads and demonstrates how to run these applications on YARN.

Chatbots are fun! They are also universally useful no matter what kind of developer you are. Whether you are building out a customer service bot or automating daily tasks through your preferred Chat p …

AI-powered chatbots are increasingly becoming viable solutions for customer service use cases. Technology leaders must consider adopting a multichannel chatbot strategy to avoid siloed chatbot solutions. Sharad Gupta shares a framework to ensure long-term strategic investment in chatbots.

Laurie Hannon introduces you to Mycroft, an open source virtual assistant similar to Siri, Alexa, and the Google Assistant. Laurie explains what it takes to code your own custom skill for Mycroft and details how Microsofts open source Bot Framework can be used for cross-platform chatbots.

Chat is becoming more integrated in our day-to-day lives, but it can feel convoluted in the office. The growth in popularity and ease of use for conversational UI means it is no longer reserved just for the social user. Meredith Hassett explains how chatbot technology can increase productivity and simplify work streams in the office.

Deep reinforcement learning is a thriving area and has wide applications in industry. Arsenii Mustafin shares his experience developing deep reinforcement learning applications on BigDL and Spark.