IBM's Watson Developer Cloud

Originally published at: http://www.sitepoint.com/ibm-watson-developer-cloud/

IBM made its debut in the artificial intelligence field several years ago with Watson, an artificial intelligence computer system that can answer questions posed in natural language.

Watson now includes a collection of Web APIs that enable web developers to leverage Watson's cognitive capabilities in their web applications. These REST APIs are publicly available through IBM's Bluemix cloud services platform, dubbed the Watson Developer Cloud.

IBM Watson Developer Cloud

IBM’s CTO for Watson, Rob High, has been quoted as saying that developers can utilize these APIs without needing to understand anything about machine learning.

Demo Apps at the Developer Cloud

Personality Insights Demonstration

The IBM Watson Personality Insights service provides an API that enables applications to derive insights from social media, enterprise data or from digital communications.

Watson gives the personality insights in the form of percentages of what's known as the "Big Five". These are the human characteristics of Openness, Conscientiousness, Extraversion, Emotional Range, and Agreeableness. Other than the Big Five, it also gives some insights into the Needs and Values of a person's personality.

Their website suggests that –

These insights help businesses to understand their clients' preferences and improve customer satisfaction by anticipating customer needs and recommending future actions. This allows businesses to improve client acquisition, retention, and engagement, and to strengthen relations with their clients.

It also provides a beautiful visualization of its results in the form of a chart, created with the help of D3.js:

Its documentation is available here, its REST API can be accessed from here, and you can hack on the code by forking this GitHub repository.

Question and Answer

The Watson Question and Answer service interprets and answers questions related to the Travel and Health industries by obtaining meaningful information based on primary data sources (brochures, web pages, manuals, records, and so on).

Each answer has an associated confidence level, and it links to supporting evidence for the answer. This application is currently in Beta, since it hasn't been trained currently through machine learning.

Its documentation is available here, and you can hack on the code by forking this GitHub repository.

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