Abstract: While AI models, like large language models, are powerful tools with multiple applications, they can be complex to use and can require a lot of resources to operate. The disclosed systems and methods provide tools to generate customized models (or AI agents) that are configured with features like tailored knowledge, capabilities, and instructions that make them faster, more efficient, and use less computational resources. AI agents may offer several technical advantages of improved efficiency, resource use, and connectivity. This disclosure describes systems and methods to configure, evaluate, generate, and deploy the custom models that can more efficiently run specific tasks. Disclosed systems and methods are configured to, for example, receive a query to generate a custom model, generate the AI agent custom model with the information in the query, and then resolve user queries more efficiently using the custom model.

Abstract: While AI models, like large language models, are powerful tools with multiple applications, they can be complex to use and can require a lot of resources to operate. The disclosed systems and methods provide tools to generate customized models (or AI agents) that are configured with features like tailored knowledge, capabilities, and instructions that make them faster, more efficient, and use less computational resources. AI agents may offer several technical advantages of improved efficiency, resource use, and connectivity. This disclosure describes systems and methods to configure, evaluate, generate, and deploy the custom models that can more efficiently run specific tasks. Disclosed systems and methods are configured to, for example, receive a query to generate a custom model, generate the AI agent custom model with the information in the query, and then resolve user queries more efficiently using the custom model.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A selection of a time-lapse amount can be received. A subset of frames from the original set of frames can be identified based on the time-lapse amount. An orientation-based image stabilization process can be applied to the subset of frames to produce a stabilized subset of frames. A stabilized time-lapse media content item can be provided based on the stabilized subset of frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A selection of a time-lapse amount can be received. A subset of frames from the original set of frames can be identified based on the time-lapse amount. An orientation-based image stabilization process can be applied to the subset of frames to produce a stabilized subset of frames. A stabilized time-lapse media content item can be provided based on the stabilized subset of frames.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. Motion data associated with the original set of frames can be acquired. A motion pattern can be determined based on the motion data. A subset of frames that are associated with the motion pattern can be identified out of the original set. A time-lapse media content item can be provided based on the subset of frames that are associated with the motion pattern.

Abstract: Highlights from a community of users highlighting portions of an electronic digital work may produce aggregated highlights. Users may have access to public and purchase versions of the aggregated highlights. Reconciliation of highlights across multiple versions of the same digital work may also take place, with the reconciled highlights incorporated into the aggregated highlights.