Bert Loomis was a visionary. This general session will highlight how Bert Loomis and people like him inspire us to build great things with small inventions. In their general session at 19th Cloud Expo, Harold Hannon, Architect at IBM Bluemix, and Michael O'Neill, Strategic Business Development at Nvidia, will discuss the accelerating pace of AI development and how IBM Cloud and NVIDIA are partnering to bring AI capabilities to "every day," on-demand. They will also review two "free infrastructure" programs available to startups and innovators. Speaker Bios Harold Hannon has worked in the field of software development as both an architect and developer for more than 15 years, with a focus on workflow, integration, and distributed systems.

Before building the chatbot, let us first understand the technology that is powering this chatbot. IBM Bluemix is a Platform As A Service cloud offering from IBM. It enables developers to quickly create, deploy, and manage applications on the cloud by abstracting other layers. Watson is a cognitive system that can understand all forms of data, interact naturally with people, and learn and derive insights out of it, at scale. Watson is available as a set of open APIs and SaaS products.

Craftworkz specializes in building applications that embed artificial intelligence. These applications can learn, discover, see, hear and interpret like humans. For several clients, Craftworkz has built custom chatbots using their own AI framework built in Python. To build this solution, Craftworkz has designed a microservices architecture that is deployed on IBM Bluemix. This highly available architecture consists of several Node.js and Python runtimes, Redis by Compose and several IBM containers.

We have all heard, if not aware of IBM's cognitive system, Watson. It enables a link between people and computers enabling them to partner mutually. In order to strengthen this symbiotic relationship between human and a computer, IBM has come up with Watson Conversations. This application helps to deploy messaging platform on any device by using natural language algorithms. The best part about this app is, one need not be conversant in technology but few simple clicks can build, test and deploy bots across messaging platforms, physical robots or even mobile devices.

Below is a quick overview of samples that demonstrate how to use the machine learning capabilities in Spark on IBM Bluemix. David Taieb posted the slides of his hands-on session how to predict flight delays based on historical data and whether predictions. The sample uses the machine learning algorithms Logistic Regression, Random Forrest, Decision Tree and Naive Bayes. When playing rock-paper-scissor everyone has his/her own strategies, e.g. The sample recognizes these patterns and leverages the patterns and history data to predict moves (via the FPGrowth algorithm).