Abstract: Methods and systems for smart buttons for automation rules in collaboration platforms are described. The method may include, causing display of a frontend including an editor displaying user-generated content of an electronic document hosted by a first collaboration platform. In response to a text-command input provided to the editor at a particular location within the electronic document, a set of graphical user elements may be displayed in the frontend, each graphical user element corresponding to a respective configurable automation rule template of a set of configurable automation rule templates. A user then selects a graphical user element of the set of graphical user elements, one of which is displayed within the electronic document. When the button element is selected, the automation rule is executed to perform an action of the automation rule on an object of the collaboration system.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: In one example in accordance with the present disclosure, an image capturing device and monitor is described. The image capturing device includes a microcontroller, an imaging sensor, and a network controller communicatively coupled to the microcontroller to: (1) capture an image from a monitor; (2) extract a sub-image from the image; (3) determine whether a nonfungible token (NFT) corresponds with the sub-image; and (4) omit, responsive to the determining, the sub-image from a stored image.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: Embodiments described herein relate to systems and methods for deploying automated assistant services or conversational bots using an automation service. The automations service includes a series of automation components that are executed in accordance with a workflow in response to a trigger condition being satisfied. The automation service includes one or more automated assistant service components, which may invoke use of generative output engine having a large-language model in order to produce generative content. The generative content may be used by subsequent automation components to produce the automation service result. Content creation and modification may be performed using the permissions of a respective system user and attributed to the automated assistant service.

Abstract: Embodiments described herein relate to systems and methods for suggesting automation rules in collaboration platforms. A graphical user interface of the content collaboration platform may be displayed. In response to a first user input to the graphical user interface, an automation rule template may be selected. A rule suggestion interface having a set of graphical elements may be displayed, each graphical element corresponding to a respective automation component of the automation rule template. In response to a second user input, a value may be assigned to an instance of an automation component associated with a graphical element of the set of graphical elements. In response to a third user input a new automation rule may be created based on the automation components of the automation rule template.

Abstract: Embodiments described herein relate to systems and methods for automation rule creation for collaboration platforms. A natural language user input may be input to a centralized automation rule service that creates prompts for a generative output service to automatically create an automation rule understandable to one or more collaboration platforms of a system. A trigger-selection prompt, component-selection prompt, and rule-selection prompt are generated by the system and provided to the generative output engine. An automation rule can then be identified from the generative response, verified, and used in the system for the one or more collaboration platforms. In some cases, the automation rule creation from natural language input may reduce the burden on a user to craft and manage automation rules in a collaboration platform.

Abstract: Embodiments described herein relate to systems and methods for automation rule creation for collaboration platforms. A natural language user input may be input to a centralized automation rule service that creates prompts for a generative output service to automatically create an automation rule understandable to one or more collaboration platforms of a system. A trigger-selection prompt, component-selection prompt, and rule-selection prompt are generated by the system and provided to the generative output engine. An automation rule can then be identified from the generative response, verified, and used in the system for the one or more collaboration platforms. In some cases, the automation rule creation from natural language input may reduce the burden on a user to craft and manage automation rules in a collaboration platform.

Abstract: In an example implementation according to aspects of the present disclosure, a display monitor comprising a display panel, an embedded processor and a non-volatile memory. The non-volatile memory hosts instructions for the embedded processor to receive an enable signal corresponding to an onscreen display input and adjust an area of the display panel corresponding to a user selection.