Skip to content

Monthly buzz – n°7

Last month Nokia Devices and Services were bought by Microsoft.

Before letting Microsoft build their own Lumia and Asha devices, Nokia still had to release their latest products:

Apple also hosted an event this month revealing their latest products and software updates.

  • The brand new iPad is now called the iPad Air and is thinner, lighter, smaller and a lot more powerful than its predecessor: it has the latest 64bit chip from Apple, the A7, with the contextual co-processor M7 because, you know, you may want to go running with your iPad Air as a pedometer…
  • The iPad mini has been refreshed with Retina display and the same guts than in the iPad air, the only difference between the two beasts is the size and the battery life.

Apple also decided that software should only be used to sell hardware:

  • the update of OS X Mavericks is now free for all
  • iWork and iLife are free in their mobile and desktop version for everyone buying a new Apple device.

While waiting for an update of Android (KitKat), Google told us that the next version of Android will not have a default SMS app, any developer will be able to release one. Google also will extend its Hangouts app to have SMS capabilities. It’s not the first time that Google tries to decouple its service from the core of Android OS, a move I analysed as a way to better update its service on non stock Android devices (EOMs ones). But this excellent article explained that it is also a way to control the open source project that is Android, avoiding competitors to build their own Android without Google (at least for smartphones and tablets).


Finally, LinkedIn introduced Intro, an app that displays contact information from LinkedIn in the native iOS mail app, what was though as almost impossible. Unfortunately, this app was not well received by security Experts, pushing LinkedIn to justify itself.


Charles Bonneau
Twitter: @charlesbonneau

Releated Posts

Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings

In this paper, we study graph representation learning and show that data augmentation that preserves semantics can be learned and used to produce interpretations. Our framework, which we named INGENIOUS, creates inherently interpretable embeddings and eliminates the need for costly additional post-hoc analysis.
Read More

SANGEA: Scalable and Attributed Network Generation

In this paper, we present SANGEA, a sizeable synthetic graph generation framework that extends the applicability of any SGG to large graphs. By first splitting the large graph into communities, SANGEA trains one SGG per community, then links the community graphs back together to create a synthetic large graph.
Read More