Abstract: Techniques for a natural language interface for searching and retrieval of digitally-stored information are disclosed. In one embodiment, a computerized method is disclosed comprising receiving, at a computing device, natural language input from a user; generating, by the computing device, a prompt using the natural language input; submitting, by the computing device, the prompt to a large language model (LLM); receiving, by the computing device, from the LLM, a response to the submitted prompt, the response comprising a logical expression of the natural language input generated by the LLM using the prompt; generating, by the computing device, for a data source, a query using the logical expression; retrieving, by the computing device, a query result set from the data source using the query; and generating, by the computing device, a response to the natural language input using the query result set.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A technique for translating text strings includes receiving a source language text string from an application, determining that a translated text string that includes a translation in a target language of the source language text string is not available for use by the application, transmitting the source language text string to a translation service for translation, receiving the translated text string from the translation service, and causing the translated text string to be available for use by the application.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include receiving, as an input, segmented video scenes, where each video scene includes a specified length of video content. The method may further include scanning the video scenes to identify objects within the video scene and also determining a relative importance value for the identified objects. The relative importance value may include an indication of which objects are to be included in a cropped version of the video scene. The method may also include generating a video crop that is to be applied to the video scene such that the resulting cropped version of the video scene includes those identified objects that are to be included based on the relative importance value. The method may also include applying the generated video crop to the video scene to produce the cropped version of the video scene. Various other methods systems and computer-readable media are also disclosed.

Abstract: A technique for translating text strings includes receiving a source language text string from an application, determining that a translated text string that includes a translation in a target language of the source language text string is not available for use by the application, transmitting the source language text string to a translation service for translation, receiving the translated text string from the translation service, and causing the translated text string to be available for use by the application.

Abstract: A technique for translating text strings includes receiving a source language text string from an application, determining that a translated text string that includes a translation in a target language of the source language text string is not available for use by the application, transmitting the source language text string to a translation service for translation, receiving the translated text string from the translation service, and causing the translated text string to be available for use by the application.

Abstract: A technique for translating text strings includes receiving a source language text string from an application, determining that a translated text string that includes a translation in a target language of the source language text string is not available for use by the application, transmitting the source language text string to a translation service for translation, receiving the translated text string from the translation service, and causing the translated text string to be available for use by the application.