We may be years away from the “AI-enabled Coworker,” but the first implementations of machine-learning capabilities are finding their way into the everyday data-analysis tools used by businesses of all types. Cognitive assistance promises to reshape business processes, but only if app development and deployment tools are adapted to support machine learning.
While it has become fashionable to hypeAIas the next game-changing technology promising to have an impact greater than either mobile or cloud, the reality is that machine learning will be a long time coming to everyday business analytics. As with any sea change, cognition is likely to sneak its way into applications and processes in drips and drops. It looks like this year could be the year many businesses get their first hands-on experience with cognitive-learning business apps.
For example, IBM’s Watson elicited plenty of “oohs” and “aahs” when it beat the Jeopardy champions, but the AI-based platform drew praise of another sort with the introduction of business solutions at the recentWorld of Watson event, as NewsFactor pointed out . Watson’s professional series applies cognitive learning to the analysis of large data sets; it works in tandem with enhancements to IBM’s DB2 for transactional processing in analytical databases.
IBM may have gotten a bit of a jump on the field of vendors racing to bring machine-learning capabilities to business processes, but the contest has just begun. The real winners are line managers, who stand to benefit the most from AI-enabled business applications.
What you will find in this article:
- Business Tackles Cognitive Implementation Challenges
- Vendors Collaborate on AI Best Practices
- Looking at the ‘Human Side’ of Machine Learning
- Sophisticated Analytics Power in Managers’ Hands
This article was written by Brian Wheeler. Brian oversees the technology team at Morpheus Data. Prior to Morpheus, Brian founded a software development consulting firm which designed and developed solutions for a variety of industries including power grid management, ticketing systems, online trading, social networking and gaming, SOX compliance, and e-commerce. Brian holds a bachelor’s degree in Chemistry from Pomona College.
To check out all this information, click here. For other article about machine learning, click here.
Top DSC Resources
- Article: What is Data Science? 24 Fundamental Articles Answering This Question
- Article: Hitchhiker’s Guide to Data Science, Machine Learning, R, Python
- Tutorial: Data Science Cheat Sheet
- Tutorial: How to Become a Data Scientist – On Your Own
- Categories: Data Science – Machine Learning – AI – IoT – Deep Learning
- Tools: Hadoop – DataViZ – Python – R – SQL – Excel
- Techniques: Clustering – Regression – SVM – Neural Nets – Ensembles – Decision Trees
- Links: Cheat Sheets – Books – Events – Webinars – Tutorials – Training – News – Jobs
- Links: Announcements – Salary Surveys – Data Sets – Certification – RSS Feeds – About Us
- Newsletter: Sign-up – Past Editions – Members-Only Section – Content Search – For Bloggers
- DSC on: Ning – Twitter – LinkedIn – Facebook – GooglePlus
Follow us on Twitter: @DataScienceCtrl | @AnalyticBridge