For decades, digitalization has been transforming how companies and individuals co-ordinate and communicate with one another. Datafication, on the other hand, promises to completely redefine nearly every aspect of our existence as humans.
Digitalization has unleashed a wave of transformation across a range of industries. The pace of change has been mind boggling and will only continue to accelerate. Everything from business models and product categories to financing and human resources will transform in order to take advantage of the possibilities of the Networked Society.
The world of games is being transformed. A new Ericsson ConsumerLab report says this transformation is being driven largely by a wave of new devices, more stable internet access and ever-increasing interest.
This report is the third installment from Ericsson ConsumerLab investigating matters of user privacy, integrity and security online.
The latest interim update to the Ericsson Mobility Report highlights the continued rapid growth of smartphones and connectivity.
Across domains, many machine learning problems involve data which naturally comprises multiple views. Multi-view Learning is a machine learning technique that can utilize multiple views. Here we focus on co-training style multi-view learning algorithm under semi-supervised conditions which leverages both labeled and unlabeled data. In many domains, amount of (unlabeled) data available is very huge in size, which makes it impossible to learn serially in a single machine. In this work, we study various distributed multi-view learning using both consensus and complementary principles. We also propose an efficient computational design on Hadoop for learning multiple classifiers.
Ericsson ConsumerLab has identified some of the most important consumer trends for 2014 and beyond.
Ericsson has released its first regional consumer insight report focusing on trends and analysis of the mobile ecosystem in Sub-Saharan Africa.