The companies unveiled their flagship model of the OLED device at CES.
Amazon and Panasonic Holdings have announced that they are collaborating on a project for the production of a smart TV line that will be able to recommend content to viewers based on their watch history.
The Japanese electronics company has been working on a strategy to enhance its TV software.
Earlier this month at CES, the companies unveiled their flagship smart TV model, which is an organic light-emitting diode (OLED) screen equipped with the Fire TV streaming technology from Amazon. That television model is slated for launch in Japan and Europe in Spring 2024.
Panasonic subsidiary Panasonic Entertainment & Communication, with its focus on consumer electronics, is working with Amazon on the development of the television’s internal systems. The software incorporated into the device will provide viewers with suggestions based on their watch history from the streaming services they use. That said, it will also base its suggestions on other data such as shows the user has previously recorded, and the broadcast television shows they watch.
Each individual can create an account with the smart TV, making it possible to customize suggestions.
Each member of the household will be able to create an account with the television so that the software can analyse the watch habits and keyword searches of each person.
Though initial models of the television will require viewers to select their accounts before watching or receiving suggestions, the companies have indicated that future models will include tech such as fingerprint and voice authentication so that the smart TV can detect who is watching and automatically use that account.
Panasonic is also working on the development of a link that the televisions can use with in-vehicle displays. That way, if passengers have started watching something at home, they can continue to watch it in the car. The company is also seeking to create a link between the television and smartphones, for further analysis of the types of videos that users are watching across multiple apps and devices. The goal is to further fine-tune content suggestions for each person.
