IBM Power Systems Enterprise AI Solutions
A draft IBM Redpaper publication
Updated 13 September 2019
IBM Form #: REDP-5556-00
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Authors: Scott Vetter, Glen Corneau, Andrew Laidlaw, Marcos Quezada
This IBM® Redpaper™ publication will assist the line of business, data science and IT teams develop an information architecture for their enterprise AI environment. It discusses the challenges 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 AI solutions including:
- IBM Watson Machine Learning Community Edition
- IBM Watson Machine Learning Accelerator
- 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
- Planning for the future
- Machine learning
- AI teaming and collaboration
This publication targets readers from lines of business, data science teams, and information technology departments, as well as anyone interested in better understanding how to build an information architecture 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
These pages are Web versions of IBM Redbooks- and Redpapers-in-progress. They are published here for those who need the information now and may contain spelling, layout and grammatical errors. This material has not been submitted to any formal IBM test and is published AS IS. It has not been the subject of rigorous review. Your feedback is welcomed to improve the usefulness of the material to others.
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