IBM has been my home since 1990. Over the years I have been a part of some incredible technology application projects that led to my start with Watson in 2010. Since Watson’s commercial success, I have been around the world talking to an entire global developer community and some of the largest companies on the planet about developing cutting edge technology and how to duplicate our efforts for specific uses in their industries.
I’ve dedicated the last seven years to building the artificial intelligence and deep learning circuitry, and have recently been involved with the development of a similar platform to serve the healthcare industry.
We all know Watson’s Machine Learning capabilities are quite powerful. It can be used to analyze and gain cognitive insights into all of your data including unstructured text, images and speech.
We will demonstrate a state-of –the-art Enterprise Java application running in production, using Watson’s Deep Learning services. Specifically, we will investigate how enterprise developers can leverage Alchemy’s Natural Language Processing to extract entities, concepts, relations and extend that to include custom type entities based on domain specific dictionaries, using Watson’s Knowledge Studio, for unstructured text analysis.
In this session, you will design Conversation workspaces using easy to use tooling, enriching your Enterprise Java application to handle intricate human conversations! And add Document Conversion service to ingest documents in various formats. All these capabilities will enable you to create powerful business applications.
And along the way, we’ll give you some best practices on testing cognitive applications.
Watson has come a long way since the Jeopardy! win in 2011 and the journey continues. As IBM has emerged as a cognitive solutions and cloud platform company, Watson has evolved into the cognitive platform for IBM. In the early days of Watson, many of our solutions were both on-premise and monolithic in nature. This had to change. We've embarked on a journey towards a more nimble microservice architecture with a continuous delivery model. We would like to share with you a microcosm of our journey in the evolution of NLP (Natural Language Processing) microservices and applying them to Healthcare. What problems have we solved? What benefits have we seen? What are the challenges ahead?
We will demonstrate an analytic NLP Pipeline, with ability to define sequential or asynchronous analytic flows, and the ability to configure the behavior of an analytic, the NLP pipeline service is a key component of our adaptable NLP service strategy within Watson Health.
We will work our way from NLP microservices to their use in our Watson for Oncology offering, demonstrating the pluggable architecture we have built for Watson Health
Please join us and connect with us at the conference.