Aauto Quicker Extreme Edition is not only simpler than the regular edition, but also makes money. Compared with the ordinary version of Aauto, it is faster and removes the function of publishing works. When we click the shoot button in the upper right corner, we will be prompted to enter the normal version of the APP to shoot, which means that in the extreme version, we only have the right to watch but not the right to post, but the data of the two are exactly the same, including your account and people who follow you. You can log in to Extreme Edition directly with your Aauto Quicker account to view all kinds of works.
In a auto quickless and a auto quickless Extreme Edition, as long as users log in with the same account, the attention and friends in the account will be synchronized. Aauto quickey is a short video application app developed by Aauto quickey Technology, formerly known as GIF Aauto Quicker, which was born in 20 1 1. It is a tool to convert video into GIF format pictures, through which users can make and share short videos, and also browse and praise other people's works faster on Aauto, and interact with other short video authors.
Autopilot works faster:
On Aauto Quicker, users can record their lives with photos and short videos, or interact with fans in real time through live broadcast. The content of Aauto Quicker covers all aspects of life, with users all over the country. Here, people can find things they like, people they are interested in, see a more real and interesting world and let the world discover themselves.
At the beginning of 20 16, Aauto Quicker launched the live broadcast function, and put the live broadcast in the attention column in a low-key way. Live broadcast has only auxiliary functions in Aauto faster. Aauto Quicker's recommendation algorithm is described in a shortened version. The core of the algorithm is understanding, including understanding the attributes of content, understanding the attributes of people, and the historical interaction data between people and content. Then, through a model, the matching degree between content and users is estimated.