The mobile applications sector is one of the world’s great markets for technology. This is something that cannot be denied, there are some data for you to understand a bit the magnitude of the matter

  • At the end of 2017 there were 5,000 million users with a Smartphone.
  • In the year 2017, nothing more and no less than 197 billion applications were downloaded.
  • In March 2017, 2,800 million applications were reported on Google Play and 2,200 million on the App Store.
  • In Spain 22 million people use mobile applications every day and every day we download 4 million applications for mobile phones, tablets and TVs.
  • It is expected that by 2020 the apps market will generate around 189 billion dollars in revenue.

They are incredible numbers, right? The application development sector is unstoppable, so whether you are already a developer or if you want to be … we leave you with some trends of the world, so you are up to date, you know that in the technological field you always have to be attentive, with the blaster prepared.

Trends in iOS


This framework came with iOS 11 and allows developers to create applications and content in Augmented Reality for iPhone and Ipad. It combines data from the cameras and information from the motion sensor to analyze the environment and show objects from it. Thanks to this it will seem that we are really interacting with the real world, taking the utility of mobile applications to another level.

Augmented Reality to work its magic you need to know to create and maintain a correspondence between the real and virtual worlds. For this task, ARkit uses a technique called Inertial Visual Odometry (VIO), which is responsible for combining the information of the motion sensors with the camera of the devices. In this way you can achieve as amazing things as a robot dancing in your living room. It seems that it is really there, to look at the shadow and how it respects space.

Core ML

This library that allows apps to use automatic learning within the device itself. In this way our iPhone or iPad will be able to record successes and errors to improve your answers.

CoreML initially disappointed developers because Google solved the integration of Machine Learning on their Android through cloud services, but Apple did not, everything happened on our iPhone or iPad device in order to protect the user’s privacy. What’s wrong with this? Well, what happens is that the possibility of integrating automatic learning processes in the apps was a bit hacked, since it was discovered that CoreML was a kind of interpreter of trained models, that is, that by itself it did not have the capacity to expand the training or create it.

But everything began to change after the purchase of Turi Create, which allows us to create models based on recommendations of content seen by the user, object detection, classification of images, search of similarities in images … in this way you can start to create our own models.

Apple does not want to be left behind in the Machine Learning race, so CoreML continued to advance after its agreement with IBM Watson . IBM contributed its own cloud to simplify the connection between the construction process of the Watson model and the insertion of that same model in the application of Apple devices.


Siri is Apple’s personal assistant since 2010. He uses natural language processing to answer user questions, offer recommendations or perform actions on the web. It is important to keep in mind that Siri is not a simple assistant, it is the Artificial Intelligence of the device, which remembers what we ask, what we are looking for etc. and uses that knowledge to recommend other things.

Due to the limitations of the patent and its functionalities, Siri had never been used in third-party applications. So far and thanks to the SiriKIT framework. It can be used to create reminders or lists, open QR codes, request a trip in a taxi service such as Uber or Cabify, to search for photos in the apps, send text messages that have that option as WhastsApp, control the climate of a room, car radio, voice calls, restaurant reservations … a pegoton of things, come on. And surely in the near future many more options will come. We’ll be alert.

Trends in Android

Reactive functional programming with RxKotlin

What is reactive programming? It is a style of microarchitecture and paradigm focused on working with finite or infinite data flows asynchronously. Its conception has evolved from the hand of the Reactive Manifesto, whose bases are:

  • Responsive: quality of service and response time. Responsive apps are collaborative, attractive and run in real time.
  • Resilient: responsive even when there are failures and errors. A resilient app can face programming errors and are even capable of repairing itself.
  • Scalable: they remain responsive to increases in workload. A scalable application can be expanded depending on its use.
  • Event-driven: flexible applications that help reduce maintenance costs.

RXKotlin is Kotlin’s own implementation for Reactive Functional Programming and fits perfectly with new components taken by Google, such as “Android Live Data”.