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Artificial intelligence is a transformative technology and way ahead from traditional computer programs. Generative AI can augment human intelligence and help businesses in accelerating productivity. Many service providers are leveraging AI technologies and helping businesses in this process of acceleration. One such leader in this space is IBM and their IBM Watson on cloud solution apply AI to workflows and systems which are core to business operations such as SAP, salesforce, and Amazon web services (AWS).
In today’s topic we will learn about IBM Watson on IBM cloud, how IBM Watson AI can be integrated into your applications and we will also look at some real-world examples of AI application in IBM cloud.
About IBM Watson on IBM Cloud
IBM Watson was developed as a part of IBM DeepQA project by its research team. Initially in the year 2011 it was developed to answer questions for the popular quiz show ‘Jeopardy’. In 2013, IBM announced its first commercial application for utilization management decisions in lung cancer treatment at Memorial Sloan Kettering Cancer Centre, New York City with WellPoint. It uses more than 100 different techniques to perform analysis on natural language, identification of sources and find and generate hypotheses, find score evidence and merge and ranking of hypotheses.
Its capabilities have been extended in recent years and has evolved its machine learning capabilities. IBM Watson, a data analytics processor having natural language processing capabilities is a technology which analyses human speech for syntax and meaning. It performs analytics on vast repositories of data which is processed to provide response to human posed questions in a fraction of a second.
IBM Watson cloud services offer:
- Advanced Natural Language Processing (NLP) capabilities allow us to understand and analyze human language efficiently. It can extract insights from unstructured data such as emails, documents and social media posts
- It has robust machine learning tools to simplify deployment, building and training of models. You can also create custom machine learning models and platform supports variety of algorithms and data types
- It has powerful analytics to process and analyse large data sets to uncover patterns, trends and insights from structured and unstructured data sources
Watson AI Integration into Apps
To start using IBM Watson, the first thing is to create an IBM cloud account.
Provide your email, credentials information (password). Next step is to verify the email.
After completion of process you will be redirected to IBM catalogue page where all services will be listed which you can access on IBM cloud. On the left sidebar scroll down to Watson section and click on ‘Watson’ and there you will find the list of all Watson APIs which can be leveraged to build application.
Step 1
IBM cloud catalogue shows services under Watson
Step 2
To access the service, select and create an instance of that service in your account. After service creation you will be redirected to the landing page of the selected service.
Step 3
Click on service credentials option and Add. This step successfully completes the first step to use IBM Watson service.
Step 4
To configure Watson assistant create a new workspace where you can build and train chatbot. Add intent, entities, and dialogue nodes to define chatbot interaction to users.
Step 5
To integrate Watson to your applications use the provided APIs and SDK to connect Watson to your application. Watson documentation provides API documentation and code guidance to integrate applications.