CloudMade powering Faurecia’s Cockpit of the Future

At Mondial de l’Automobile 2016, Faurecia, a global supplier of cabin and interior solutions to automotive OEMs, announced a major new initiative.  The Cockpit of the Future will transform the connected and autonomous car experience for drivers and passengers.  CloudMade is central to the advanced machine learning that Faurecia is using to deliver their vision of an intelligent future.

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After consultation with OEMs as well as extensive primary user research, Faurecia has concluded that there are 3 key technology areas required to deliver the Cockpit of the Future.

  1. Connectivity
  2. Adaptable interfaces
  3. Predictive interfaces

Faurecia CEO Patrick Koller demos the Cockpit of the Future powered by CloudMade

Faurecia CEO Patrick Koller demos the Cockpit of the Future powered by CloudMade

Faurecia uses CloudMade’s Predictive Learning System to enable adaptive interfaces, powered by machine learnt inferences.  Some examples include:

  1. Pre-conditioning the cabin to the occupants’ desired temperature based on their learnt departure time.
  2. Learning the occupants’ cabin settings such as seating position, mirror positions and steering position and then predictively applying these settings.
  3. Anticipating a driver’s safety level and adjusting interactions such as cockpit displays and autonomous hand overs accordingly.
  4. Anticipating a driver’s comfort level and adjusting seating settings like massages, lumbar supports and air bladders.

This short video gives an overview of CloudMade’s vision of the Intelligent Vehicle of the future. 

To book a workshop with CloudMade send a mail to sales@cloudmade.com.

October 2nd, 2016 - Posted by Nick Black in connected car, context-aware car, for OEMs, self-learning car, technologies

Secrets of Self Learning Cars at Nvidia GTC 2016

The secrets of the self learning car are revealed in this video, shot at Nvidia GTC 2016.  

Well, maybe not revealed, but you’ll learn a lot about using machine learning to deliver connected car experiences that are safe, fun and easy to use.

September 30th, 2016 - Posted by Nick Black in connected car, context-aware car, for OEMs, self-learning car, talks

CloudMade’s Self Learning Car Could Buy You Lunch

Chief Product Officer Nick Black talked at November’s Autotech Council about CloudMade’s mission to build artificual intelligence that is so powerful it transforms the car into the most personal space we experience.

Check out the full video below.

February 3rd, 2016 - Posted by in connected car, context-aware car, events, for OEMs, self-learning car

Connected Car: Privacy Concerns and Digital Ethics

In a world where data privacy is a concern and the Connected Car business is rapidly becoming the next battleground for market share within the automotive market, a debate about privacy concerns and digital ethics is becoming extremely important.

A recent study of McKinsey shows that car buyers are broadly concerned about data privacy and the possibility of hacking when it comes to car connectivity. 37% of respondents are reluctant to use connected car services because they want to keep their privacy, 54% said they are afraid that people can hack into their connected car and manipulate it.

Cars are now undergoing a rapid transformation. They are becoming information hubs on wheels that generate, store and analyze huge amounts of data. The connectivity features in cars potentially give automakers access to private data such as places previously visited, routes and destinations, and more personally, the driver’s location (home-/workplace), family information and other sensitive data. Used properly, such data can be used for purposes that bring long-lasting benefits to drivers by delivering them personalized, driver-centric and context-aware driving experiences.

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The massive growth in the amount of data generated raises questions related to privacy, confidentiality, ownership, transparency and security. While working with sensitive private data, OEMs have to identify and enforce appropriate rules about data collection, analysis and retention.

The more car manufacturers use private data for purposes that are beyond their original intent, the greater the chances that privacy issues will arise.

To protect private data, car manufacturers will need to consider:

  • Data ownership. Data should be used primarily for the driver’s own benefit. Car owners need to have control over the information the connected car learns about them and also have the ability to manage the flow of their private data, including the possibility to delete all or part of it.
  • Data storage. When it comes to storing data, cloud storage provides a lot of advantages as drivers can access data from anywhere, keep their information synched across cars, devices and applications or build collaborative datasets. However, drivers should be informed that their personal data is stored in the cloud, know whether it is encrypted, who can decrypt it and for what reason.
  • Data transparency. Sensitive data requires transparency. For private data to work in ethical terms, drivers need to have a transparent view of how their data is being used or sold. While co-operating with insurance companies and other third party companies, OEMs should get an allowance of car owners before sharing the private information and offer distinct benefits for sharing it. People will gladly enabled automakers to know their private data if they give them value back.
  • Data security. As cars get more connected and increase in user-friendliness, the risk of car hack or thief is growing, raising a new problem of data loss incidents. Not keeping the personal data secure can lead to the loss of private data and even to identity theft. OEMs need to work out algorithms on how to secure private data and vehicles so that they cannot be hacked.

December 9th, 2014 - Posted by in context-aware car, self-learning car