Putting AI to work with 3 of the Watson AI Offerings

IBM's amazing Enterprise AI Portfolio of Offerings includes a wide variety of products to support Clients on their journey to a complete end to end AI Platform. In this article I'd like to give a quick overview of three of these Offerings, and how they are related to and compliment each other.

First, IBM Watson Studio (WS). IBM WS is used to Build Models. It's a Collaborative, self-service platform for building AI models across diverse personas.

Next is IBM Watson Machine Learning (WML). IBM WML is the software used to Train, Deploy & Manage Model Lifecycles. It's software for complete Model lifecycle management and deployment for ML/DL models built from open source or IBM tools

Finally, IBM Watson Machine Learning Accelerator. Need to Accelerate the Training Speed and Accuracy of your AI Models ? Then take a look at WML-A. IBM Watson Machine Learning Accelerator is optimized to Train & Deploy Many Models, Across Many Users, At Large Scale. Incremental benefits realized by using this product include accelerated AI Model training speed, accuracy and overall much more favorable shared resource economics.

More good news - all of these products run on both the x86 and IBM Power Systems platform, On Prem, in a Private Cloud, or in Public Clouds.

In summary - WS to Build Models, WML to Train, Deploy and Manage Models, WML-A to accelerate the speed and accuracy of AI models and also optimize shared resources for your AI Infrastructure.

Learn more by starting here - https://www.ibm.com/watson