Grammarly, Inc.

A computer-implemented method executed using an assistant application and a web browser hosted or executed using a first computer, the computer-implemented method comprising receiving a first signal that first application is executing, with text within a workspace of the first application; receiving a second signal that a control was selected; instantiating and causing displaying an app actions window comprising at least one app label respectively corresponding to at least one second application; receiving input from the first computer specifying a selection of the at least one app label; updating the app actions window to display one or more app-specific widgets corresponding to widgets, fields, or functions available in the second application; receiving data entered into and/or selection(s) of one or more of the one or more app-specific widgets; programmatically invoking one or more application programming interface (API) calls of the second application using the data and/or selections; receiving one or more response(s) from API call(s) to the second application; updating the workspace of the first application based upon the one or more response(s). The method enables a user's computer to access functions of a second application from within a compact window over a first application without switching context to interact with the second application in a separate window or tab.

In an embodiment, non-transitory computer-readable storage media store one or more sequences of instructions which, when executed using one or more processors, cause the one or more processors to execute: executing a document processing application; receiving a digitally stored electronic document, alone or in combination with one or more other relevant documents, and an engineered prompt; transmitting an application programming interface (API) call to an API of a pre-trained large language model (LLM), wherein the call comprises the engineered prompt, wherein the engineered prompt comprises a plurality of objective instructions to the pre-trained LLM specifying transforming the electronic document according to a style guide to cause the pre-trained LLM to execute an inference stage over the electronic document and automatically generate output text based on the electronic document and the plurality of objective instructions that transforms the electronic document to conform to the style guide; storing the output text using a storage device of a user computer, a hosted storage environment, or in memory associated with the document processing application.

A computer-implemented process is programmed to programmatically receive at a first computer a digital electronic object comprising a source text having been composed at a second computer, send instructions to the second computer for presenting filters via a user interface, which are programmed to adjust the source text when they are selected and executed, receive a selection of a first filter, generate an output set of suggestions based on executing the first filter over the source text, transmit the output set of suggestions to the second computer, receive a specification to apply the suggestions, and in response, automatically apply all the suggestions to the source text and transmit updated presentation instructions to the second computer which when rendered using the second computer cause displaying an updated text with all the suggestions having been applied to the source text.

In an embodiment, the disclosed technologies are capable of receiving, by a digital model, data representing a first text sequence in a first language; using the digital model, modifying the first text sequence to result in creating and digitally storing a second text sequence in the first language; and outputting, by the digital model, the second text sequence in the first language. The modifying may include any one or more of: deleting text from the first text sequence, adding text to the first text sequence, modifying text of the first text sequence, reordering text of the first text sequence, adding a digital markup to the first text sequence. The digital model may have been fine-tuned, after having been machine-learned, using a subset of values of model parameters associated with an encoding layer or an embedding layer or both the encoding layer and the embedding layer.

Systems and methods for publication and external interfacing for a unified document surface are disclosed. An example system may include a document serving circuit structured to access a document data, the document data comprising data for a unified document surface, and provide at least a portion of the document data to a client serving circuit. The client serving circuit may be structured to implement a unified document surface interface in response to the at least a portion of the document data, implement an extension creation interface, provide a pack implementation value to the document serving circuit in response to user interactions with the extension creation interface, and determine an executable object in response to the pack implementation value.

A computer-implemented process is programmed to detect a type or category of document that is being drafted and to suggest one or more phrases or sentences to add to the original and/or substitute for the original, the suggested text being potentially more personable and sincere than the writer's original text. Suggested text phrases are selected from a large corpus of previously manually drafted sentences and phrases. Selected text phrases are ranked and filtered to result in suggesting a manageable set of text phrases. With this approach, adding specially chosen content to existing content can change the warmth or tone of the text while preserving its meaning. Unlike prior approaches, in an embodiment, the process is programmed to artificially understand the intent of the original text as a basis of suggesting other content to add. Furthermore, embodiments may interoperate with a visual or graphical user interface that is programmed to enable users to see what the change to the text will be and whether they want it before they engage with the suggestion.

A method of electronic communication assistance is provided. The method includes receiving, via an artificial intelligence assistant computing facility, an electronic communication from a first user intended to be received by a second user; and determining, via the artificial intelligence assistant computing facility, a capacity of the second user to receive the electronic communication. The method further includes determining, via the artificial intelligence assistant computing facility and based at least in part on the capacity of the second user, a time to send the electronic communication; and transmitting, via the artificial intelligence assistant computing facility, the time to the first user.

In an embodiment, the disclosed technologies are capable of identifying a target word within a text sequence; displaying a subset of candidate synonyms for the target word, determining a synonym selected from the subset of candidate synonyms, and replacing the target word with the selected synonym, where the subset of candidate synonyms has been created using syntactic dependency data for the target word.

A method of electronic communication assistance involves receiving a partial electronic communication at an AI assistant computing facility from a first electronic identifier linked to a first user. This communication includes content associated with both the first user and a second user. The method extracts the communication context and encodes the partial communication for processing, creating an encoded version. It retrieves the first user's communication profile from a database using their identifier, containing user attributes, and retrieves the second user's profile similarly. The encoded communication is then processed by a processor to generate a compositional change using at least one of the communication context, the first user communication attribute, or the second user communication attribute. Finally, a revised electronic communication is generated from the partial communication and the compositional change.

In one embodiment, a computer-implemented method for dynamically presenting information in digital documents comprises receiving text data; identifying in the text data a target domain-specific term based on a set of domain-specific term records, each domain-specific term record including a domain-specific term and a term description; providing an interactive element corresponding to the target domain-specific term; receiving a signal indicating a user interacting with the interactive element; accessing a target domain-specific term record from the set of domain-specific term records corresponding to the target domain-specific term, to retrieve a target term description being a term description for the target domain-specific term, in response to the signal; and displaying the target term description using a domain-specific term associated knowledge card.