Lieveye is an institution in Philips. The current Head of Big Data of Philips was part of the team that developed an emblem technology of the Dutch brand two decades ago. Since then, televisions have changed barbarity, moving from silly boxes to Smart TV to today, where an a priori appliance as passive as The TV has become a magnificent data source. And in AI times a huge amount of data is needed.
Leaving aside the algorithmic content recommendations (which have their particular casuistry depending on the manufacturer and SO), we have seen how artificial intelligence reached televisions for such original tasks How to generate imagesbut also for get the best image quality without having to despair with the adjustments. It is just the beginning: TV is a reef To obtain data that improve the user experience and that is, in a nutshell, the mission of Lieve Lonoye and his team in Philips.
Note: Lainye clarifies two types of uses on the television completely different and with work areas that although they collaborate globally, are independent. On the one hand is the one integrated into the SO and its recommendations (Android TV and Titan Os in Philips) and another focused on the technical part, which falls on your Big Data team. The latter is what we will focus.
What interests is how TV is used
Philips head of Big Data summarizes the objective of collection of data on televisions clearly: “To do things.” And although it seems vague and generic, we will see later that its mission is not so much to suggest but act so that The experience of use is always the best possible.
Regarding what information they collect, Lainye explains that “we are not interested in what people are seeing, but in How the TV is being used In general, for example, what resolution or frame rate are using “, as well as other information such as what apps they have been in execution or what codec.
If we take into account all the parameters analyzed and that all this is produced on each television, the result is a huge amount of information related to the habits of use, the million dollar question is: Where are these data to stop?
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To begin Data analysis is optionL: “The form in the big data is implemented allows the user to accept or not share their data, which seems very important to us.” Clarified this point and assuming the acceptance of the user, Lainye explains that everything is done at home, which has its implications in terms of safety and performance:
“We do not upload things to the cloud to execute them there, we have chosen to execute the AI at home, which ensures privacy. But it is also a challenge in that you have to use the available resources of the TV, so you have to make sure that while it is running you can not affect the viewing behavior. It has to make its effect but without consuming too much. It is the great challenge, but a conscious choice to do it.”
In addition, this monitoring has a direct application for them as manufacturers, since it serves them “to make better televisions Testing them in the same way that are used in homes“, but also for those who use brand’s TV at home.
How helps the user in their experience
The most responsible for the Big Data of Philips makes it clear that this technical data is where her team allocates more time and efforts. This information may not say anything at first sight, but it is providential to detect failures:
“In spite of all the testing on televisions, sometimes a problem appears and that is where the data can help to detect. At that time the user calls the support and we can see what has been failing, which helps on the one hand to prevent problems, to confirm them and even verify that the solutions work.”
How do they do it? Lenoye explains that when people call Call Centerthe agent who receives the call has access to certain parts of our data for the Troubleshooting. After the relevant assistance, the data speak for themselves to confirm that the appropriate solution has been found.
This would be a specific case of application before a certain failure of a television of a specific person, but in global it also helps them to know What problems is more people suffering and thus “put engineers to work on it.”
After the arrival of Chatgpt And the artificial intelligence boom in the form of models, multimodality and its integration into different devices, the sensation is that The AI will be even in the soupsometimes with more reason of being and being than others. Saving the distances, servant reminds when everyone gave him to baptize his devices as ‘smart’ when in reality all they did was put Bluetooth.
If the question is AI on TV, you are right to be, Lonoye’s response is a resounding yes. “We always try to contribute innovation that makes sense and that is what we think with the implementation of artificial intelligence in TV because it helps you enjoy TV properly.”
“We do not put the AI to put, we want to make TV easier, we want to relieve viewers of responsibilities. So we have ia executed on TV that, for example, is analyzing the image to establish the adjustments and for customer service.”
Thus, he concludes that “the Big Data section does not work for recommendations, we are interested in how people use TV and when something goes wrong on TV, how it happens or how it could happen. We collect information to ensure that everything works well. “
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