US-20260129265-A1 - SYSTEMS AND METHODS FOR MODIFYING A CONTENT FEED PACE USING ARTIFICIAL INTELLIGENCE

Abstract

A method includes identifying, by a processing device of a content sharing platform, a request to load a content feed for a user of the content sharing platform. Based on the one or more features and using an artificial intelligence (AI) model, a content feed pace for the user is identified. A set of media items is selected based on the content feed pace. The set of media items is provided, via the content feed, for user consumption.

Inventors

• Hao Li
• Zhen Chen
• Omkar Pathak
• Sourabh Bansod
• Zhen Zhang
• Zerong Yao
• Mengyu FU
• Liang Liu
• Kai Chen
• David McPeek
• Lina LIN
• Qixing Liang

Assignees

• GOOGLE LLC

Dates

Publication Date

20260507

Application Date

20251103

Claims (20)

1. 1 . A method comprising: identifying, by a processing device of a content sharing platform, a request to load a content feed for a user of the content sharing platform; identifying, based on the one or more features and using an artificial intelligence (AI) model, a content feed pace for the user; selecting a set of media items based on the content feed pace; and providing, via the content feed, the set of media items for user consumption.
2. 2 . The method of claim 1 , wherein an output of the AI model reflects whether the user is to have a positive or negative experience with content of a certain duration.
3. 3 . The method of claim 1 , wherein each of the one or more features reflects at least one of: a type of current location of a client device of the user, a current local time, or a type of client device on which the request was initiated.
4. 4 . The method of claim 1 , wherein the request comprises loading a user interface of an application associated with the content sharing platform or refreshing the user interface.
5. 5 . The method of claim 1 , wherein the content feed pace reflects a desired duration of the media items in the content feed.
6. 6 . The method of claim 1 , further comprising: identifying a value from an output of the AI model; and in response to determining that the value satisfies a threshold criterion, generating the content feed pace.
7. 7 . The method of claim 1 , wherein the AI model is trained to provide as output at least one of a probability of a user preferring content of a certain duration, a prediction of user engagements with media items of different lengths, or a determination of a type of content feed pace preferred by the user.
8. 8 . A system comprising: a memory; and a processing device, coupled to the memory, the processing device to perform operations comprising: identifying a request to load a content feed for a user of a content sharing platform; identifying, based on the one or more features and using an artificial intelligence (AI) model, a content feed pace for the user; selecting a set of media items based on the content feed pace; and providing, via the content feed, the set of media items for user consumption.
9. 9 . The system of claim 8 , wherein an output of the AI model reflects whether the user is to have a positive or negative experience with content of a certain duration.
10. 10 . The system of claim 8 , wherein each of the one or more features reflects at least one of: a type of current location of a client device of the user, a current local time, or a type of client device on which the request was initiated.
11. 11 . The system of claim 8 , wherein the request comprises loading a user interface of an application associated with the content sharing platform or refreshing the user interface.
12. 12 . The system of claim 8 , wherein the content feed pace reflects a desired duration of the media items in the content feed.
13. 13 . The system of claim 8 , wherein the operations further comprise: identifying a value from an output of the AI model; and in response to determining that the value satisfies a threshold criterion, generating the content feed pace.
14. 14 . The system of claim 8 , wherein the AI model is trained to provide as output at least one of a probability of a user preferring content of a certain duration, a prediction of user engagements with media items of different lengths, or a determination of a type of content feed pace preferred by the user.
15. 15 . A non-transitory computer-readable medium comprising instructions that, responsive to execution by a processing device, cause the processing device to perform operations comprising: identifying a request to load a content feed for a user of a content sharing platform; identifying, based on the one or more features and using an artificial intelligence (AI) model, a content feed pace for the user; selecting a set of media items based on the content feed pace; and providing, via the content feed, the set of media items for user consumption.
16. 16 . The non-transitory computer readable storage medium of claim 15 , wherein an output of the AI model reflects whether the user is to have a positive or negative experience with content of a certain duration.
17. 17 . The non-transitory computer readable storage medium of claim 15 , wherein each of the one or more features reflects at least one of: a type of current location of a client device of the user, a current local time, or a type of client device on which the request was initiated.
18. 18 . The non-transitory computer readable storage medium of claim 15 , wherein the request comprises loading a user interface of an application associated with the content sharing platform or refreshing the user interface.
19. 19 . The non-transitory computer readable storage medium of claim 15 , wherein the content feed pace reflects a desired duration of the media items in the content feed.
20. 20 . The non-transitory computer readable storage medium of claim 15 , wherein the operations further comprise: identifying a value from an output of the AI model; and in response to determining that the value satisfies a threshold criterion, generating the content feed pace.

Description

RELATED APPLICATION This application claims the benefit of U.S. Provisional Application No. 63/716,005, filed Nov. 4, 2024, the entire content of which is hereby incorporated by reference TECHNICAL FIELD The disclosed implementations relate to methods and systems for modifying a content feed pace using artificial intelligence. BACKGROUND Content sharing platforms allow users to connect to and share information with each other. Many content sharing platforms include a content sharing aspect that allows users to upload, view, and share content, such as video items, image items, audio items, and so on. Other users of the content sharing platform can comment on the shared content, discover new content, locate updates, share content, and otherwise interact with the provided content. The shared content can include content from professional channel owners, e.g., movie clips, TV clips, and music video items, as well as content from amateur channel owners, e.g., video blogging and short original video items. SUMMARY The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later. An aspect of the disclosure provides a computer-implemented method which includes identifying, by a processing device of a content sharing platform, a request to load a content feed for a user of the content sharing platform. Based on the one or more features and using an artificial intelligence (AI) model, a content feed pace for the user is identified. A set of media items is selected based on the content feed pace. The set of media items is provided, via the content feed, for user consumption. A further aspect of the disclosure provides a system comprising: a memory; and a processing device, coupled to the memory, the processing device to perform a method according to any aspect or implementation described herein. A further aspect of the disclosure provides a non-transitory computer-readable medium comprising instructions that, responsive to execution by a processing device, cause the processing device to perform operations according to any aspect or implementation described herein. BRIEF DESCRIPTION OF THE DRAWINGS Aspects and implementations of the present disclosure will be understood more fully from the detailed description given below and from the accompanying drawings of various aspects and implementations of the disclosure, which, however, should not be taken to limit the disclosure to the specific aspects or implementations, but are for explanation and understanding only. FIG. 1 illustrates an example of system architecture, in accordance with implementations of the disclosure. FIGS. 2A-2B are illustrations of example graphical user interfaces (GUIs) showing a content feed recommendation on different user interfaces, in accordance with implementations of the disclosure. FIG. 3 depicts a flow diagram of an example method for training an artificial intelligence model to predict a user's preferred feed pace, in accordance with implementations of the present disclosure, in accordance with implementations of the disclosure. FIG. 4 is a flow diagram of an example method for generating a feed pace recommendation using an AI model, in accordance with implementations of the disclosure. FIG. 5 depicts a block diagram of an example computing device operating in accordance with one or more aspects of the present disclosure. DETAILED DESCRIPTION The content served by content sharing platforms can include video content, image content, audio content, text content, and so on (which may be collectively referred to as “media items”). Such media items can include audio clips, movie clips, TV clips, and music videos, as well as amateur content such as video blogging, short original videos, pictures, photos, other multimedia content, etc. The content can be presented in a stream, referred to a “content feed,” that users can scroll through. Typically, the content feed displays recommended media items in similar looking blocks that repeat one after another (e.g., appearing in a listing layout or a grid layout). Once a user stops scrolling, the displayed media item can autoplay for the user. In some systems, the content feed can include a collection of video items that are tailored to a user's interests. In particular, when a user loads a user interface (UI) for the content feed, a selection of recommended video items can be generated to populate the content feed. The selection can be sourced using one or more algorithms that determine which video items are shown to the user. The algorithms can use, for example, the user's browsing history (e.g., by comparing t