Abstract
This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and deploying enterprise AI solutions, and how they can collaborate for best results.
This publication also highlights the capabilities of the IBM Cognitive Systems and AI solutions:
- IBM Watson® Machine Learning Community Edition
- IBM Watson Machine Learning Accelerator (WMLA)
- IBM PowerAI Vision
- IBM Watson Machine Learning
- IBM Watson Studio Local
- IBM Video Analytics
- H2O Driverless AI
- IBM Spectrum® Scale
- IBM Spectrum Discover
This publication examines the challenges through five different use case examples:
- Artificial vision
- Natural language processing (NLP)
- Planning for the future
- Machine learning (ML)
- AI teaming and collaboration
This publication targets readers from LOBs, data science teams, and IT departments, and anyone that is interested in understanding how to build an IA to support enterprise AI development and deployment.
Table of Contents
Chapter 1. Introduction
Chapter 2. Point of view: Line of business
Chapter 3. Point of view: Data science
Chapter 4. Point of view: Information technology
Chapter 5. Conclusion