Meta Platforms Technologies Products Meta Horizon Worlds World Catalog And World Detail Page AI system

UPDATED APR 2, 2025
The content you see on your Meta Platforms Technologies Products Meta Horizon Worlds World Catalog And World Detail Page is selected, ranked and delivered to you by an artificial intelligence (AI) system. Within one AI system, multiple machine learning models work together to deliver your experience. These models and their input signals are dynamic and they change frequently as the system learns and improves over time.

Overview of Meta Platforms Technologies Products Meta Horizon Worlds World Catalog And World Detail Page

When you view and interact with Meta Horizon Worlds, you generally land in a World Catalog page where we show you multiple shelves. These Shelves are Recently Visited (Worlds which you recently visited), Highlighted Worlds (Recommended to you based on machine learning models) and Genre Shelves (Art, Action, Adventure etc.).
When you click on the World, you go into the World Detail page where you can get details about the World such as Creator name, People active right now. You can also click on tabs to see Similar & Highlighted Worlds.
How Meta Platforms Technologies Products Meta Horizon Worlds World Catalog And World Detail Page works
The AI system behind Meta Horizon Worlds’ World Recommendations on Catalog & Detail Page automatically gathers inventories that might be interesting to you, run predictions to evaluate relevance, and deliver recommendations on each shelf. Here’s how it works:
  1. Gather Inventory
    First, the system gathers public Horizon Worlds that are eligible to be recommended. These might include Worlds that are currently popular and trending, Worlds your friends have visited, Worlds other users like you have enjoyed, or Worlds that are similar to what you’ve recently engaged with or World detail page to find a similar set of Worlds based on similarity model.
  2. Make Predictions
    Second, the AI system runs predictions on how likely you will enjoy the content and spend meaningful time, and assign scores to the content based on the predictions.
  3. Apply Filters
    Third, the system applies integrity processes to remove content that is non-recommendable for quality reasons or that may go against our Code of Conduct for Virtual Experiences. We also remove worlds rated 18+ for certain age groups.
  4. Deliver Content
    Lastly, the scores obtained from the previous step are then used to decide what is recommended to you, and in what order you will see them.
How to customize what you see
Your experience on Meta Platforms Technologies Products Meta Horizon Worlds World Catalog And World Detail Page is personalized based on your activity, and you have options to control or customize what you see. Below, we describe how to do this with different in-product features. Options shown here may not be available to everyone.
Visit
You can visit a World to see recommendations of similar Worlds.
Report a World
You can report other users in the world if you think something goes against our Community Guidelines for violating the Code of Conduct for Virtual Experiences and the Meta Horizon Worlds Worlds Mature and Prohibited Worlds Policy and report a World as a whole.
Like a World
You can like a World. This helps the system show you similar Worlds in the future that are similar to the worlds you liked.
Following People
You can follow other users in Meta Horizon Worlds and see which Worlds they are currently active at, if they choose to make their presence visible. This information is available on the shelf with Friends Active Worlds. The system also uses this signal to rank the Worlds that are suggested to you. When you unfollow a user, your recommendations may change.
Save a World
You can save a World to your own collection. This can help the system show you similar Worlds in the future based on what worlds you are saving.
How the AI delivers content to you
We want you to see content you enjoy and find interesting. To achieve this, the AI system has models that help it make predictions about content you'll find most relevant and valuable. These prediction models use underlying input signals to help select content you're most likely to engage with.
Below are some of the significant predictions–and input signals that inform them–that we use in this AI system.
How much time you will spend during the World visit
Signals influencing this prediction include:
  • Your total number of visits to the World
  • Your engagements in the World, such as like, save, and following other people in the World
  • The number of clicks, visits, time spent and saves you have made across all Worlds.
  • The number of encounters and high-fives you have made with other users across all Worlds
  • The popularity of the World based on your saves / likes and the current count of users in the World
  • Your total number of visits to the World
Other worlds you might be interested in exploring and visiting in the Meta Horizon Worlds
Signals influencing this prediction include:
  • The Worlds visited and enjoyed by the people you are following
  • The different World door entries present in the Worlds you have visited
  • The genre, description, and other basic information of all Worlds you have visited
  • The events you have subscribed to
  • The Worlds you have visited, saved, or liked