Thursday, March 21, 2019

Machine learning creates new data management challenges; NYPD crime analysis tool faces AI bias concerns

AI, Analytics and Big Data Digest

Artificial intelligence, BI and data management content from TechTarget | March 21, 2019

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Machine learning approaches gain critical mass for data pros

Jack Vaughan, Senior News Writer

Machine learning is bringing big changes to both analytics and data management, database luminary Michael Stonebraker said at Enterprise Data World 2019. Others at the conference agreed that managing those changes will require new efforts from data professionals.
(SearchDataManagement.com)

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NEWS
 

NYPD's Patternizr crime analysis tool raises AI bias concerns

The NYPD has rolled out Patternizr, a machine learning algorithm that helps analysts identify crime patterns but highlights the complexity of eliminating AI bias in real-world systems.
(SearchBusinessAnalytics.com)

 
Tableau-VoiceBase deal brings speech analytics data to users

Tableau's partnership with AI speech analytics vendor VoiceBase aims to enable users both inside and outside of call centers to easily derive insights from speech analytics data.
(SearchBusinessAnalytics.com)

 

Oracle 19c database software promises stability, compatibility

Oracle Database 19c offers automatic indexing and support for external data partitions. But it also brings upgrade issues like application certification and index creation agreement.
(SearchOracle.com)

 

Researchers eye quantum AI as quantum computing advances

Machine learning is likely to be an early application for quantum computers, as researchers and developers look for the key to unlock more human-like forms of AI.
(SearchEnterpriseAI.com)

EXPERT ADVICE
 

Enterprises need to develop an AI strategy now

Business leaders who approach AI as a future concern are likely to miss the boat on this influential technology. The time to explore AI implementation for business use is now.
(SearchEnterpriseAI.com)

 

Big data management practices gain attention amid risks

Many data pros have yet to solidify traditional data management practices. Now they face a new set of challenges to ensure privacy and avoid misuse, as discussed in this Q&A.
(SearchDataManagement.com)

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