Meta Platforms

A method for context-based insertion of a three-dimensional (3D) object into a photograph includes analyzing, by a machine-learning model, a scene of the photograph to determine contextual attributes of the scene. The method also includes selecting, based on the contextual attributes, a 3D asset from a set of 3D assets. The method further includes posing the 3D asset using geometric information determined from the scene such that the posed 3D asset conforms to one or more of perspective, orientation, or surface geometry of the photograph. The method also includes adding a 3D element contextually associated with the scene, the 3D element being selected and positioned in accordance with the contextual attributes. The method further includes generating an output photograph that comprises the posed 3D asset and the 3D elements integrated into the photograph.

A system and method to verify a communication may include receiving sensor data from a sensor of a first device in accordance with a communication being generated using an application executed on the first device. The method may also include determining, based on the sensor data, whether the communication is generated by a human source. The method may further include generating a label indicating whether the communication is generated by the human source.

Systems or methods disclosed herein may provide artificial intelligence-based aggregation of social media content across multiple platforms. In an example, a computing system may receive content queries and may retrieve relevant content from various social media platforms. The computing system may generate consolidated content feeds that include first-party content from platforms owned by a primary entity and third-party content from external messaging platforms. The consolidated feeds may be arranged into content slots with sponsored content intelligently placed between organic content slots based on user engagement metrics. The computing system may implement machine learning models to optimize content selection or arrangement based on user interaction patterns.

Methods, systems, or computing devices are disclosed for enabling shared social media sessions that may allow multiple users to synchronously experience personalized content across different devices. The system may leverage artificial intelligence to create dynamic, constraint-free content streams that incorporate preferences from multiple users while maintaining individual privacy controls. Users may initiate shared sessions through messaging interfaces or standalone applications, with content sourced from multiple platforms and tailored to the collective preferences of session participants.

Systems, methods, and devices are described for AI platform that may utilize a machine learning model configured to generate one or more watch face images associated with a received input. In an example, systems and methods of generating one or more watch face images may include receiving an input. The input may be natural language text or audio. Based on determining the input, the machine learning model may generate one or more watch face images. An indication of a change in contextual information may initiate the machine learning model to generate a second watch face image to update a first watch face image based on the indication of the change in contextual information and the input received. The second watch face image may be provided.

In one embodiment, a method includes receiving, at a microphone of the headset associated with a first user, a user request to record an activity associated with the first user; determining a trigger condition based on the user request; accessing, from the headset, one or more sensor signals captured by one or more sensors comprising a camera and the microphone; detecting, based on one or more machine learning models and using at least one of the one or more sensor signals, a change in a context associated with the activity of the first user, wherein the change in the context satisfies the trigger condition associated with the activity; and automatically capturing, responsive to the detected change in the context, visual data by the camera.

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Zusammenfassung wird geladen …

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