Abstract: A system for generating training data to train agents to automate tasks otherwise done by users includes an intermediary disposed between an interface and a user. The intermediary is configured to: intercept one or more user-actuated actions directed towards the interface by the user, the user-actuated actions, if received by the interface, execute a task on the interface; preserve a state of the interface prior to the execution of the task; translate the user-actuated actions into one or more actuation commands, the actuation commands configured to trigger one or more machine-actuated actions that replicate the user-actuated actions on the interface to cause automation of the task; and generate a training dataset to train an agent to automate the task, wherein the training dataset requires the agent to process, as input, the state of the interface prior to the execution of the task, and to generate, as output, the actuation commands.

Abstract: A system for interface automation includes an agent. The agent is configured to process an input that specifies an interface workflow, wherein the interface workflow is otherwise implementable by one or more user-actuated actions directed towards an interface by a user. The agent is also configured to generate an output that specifies a sequence of actuation commands, wherein the sequence of actuation commands triggers one or more machine-actuated actions that replicate the user-actuated actions on the interface and cause automation of the interface workflow.

Abstract: A system for generating training data to train agents to automate tasks otherwise done by users includes an intermediary disposed between an interface and a user. The intermediary is configured to: intercept one or more user-actuated actions directed towards the interface by the user, the user-actuated actions, if received by the interface, execute a task on the interface; preserve a state of the interface prior to the execution of the task; translate the user-actuated actions into one or more actuation commands, the actuation commands configured to trigger one or more machine-actuated actions that replicate the user-actuated actions on the interface to cause automation of the task; and generate a training dataset to train an agent to automate the task, wherein the training dataset requires the agent to process, as input, the state of the interface prior to the execution of the task, and to generate, as output, the actuation commands.

Abstract: A system for providing artificial intelligence agents that automate software usage includes training servers configured to train agents during training, production servers configured to execute the trained agents during inference, a plurality of training datasets, and data flow logic. The data flow logic is configured to, provide, during the training, the agents and the plurality of training datasets to the training servers to cause the training servers to train the agents on the plurality of training datasets and thereby produce the trained agents, configure the production servers with the trained agents for use during the inference, provide, during the inference, prompts issued by clients to the production servers to cause the production servers to translate the prompts into agent calls to the trained agents that in turn cause the trained agents to generate outputs that are responsive to the prompts, and make the outputs available to the clients.

Abstract: Artificial Intelligence Agents to Automate Multimodal Interface Task Workflows A system for interface automation includes an agent. The agent is configured to process an input that specifies an interface workflow, wherein the interface workflow is otherwise implementable by one or more user-actuated actions directed towards an interface by a user. The agent is also configured to generate an output that specifies a sequence of actuation commands, wherein the sequence of actuation commands triggers one or more machine-actuated actions that replicate the user-actuated actions on the interface and cause automation of the interface workflow.

Abstract: A system for generating training data to train agents to automate tasks otherwise done by users includes an intermediary disposed between an interface and a user. The intermediary is configured to: intercept one or more user-actuated actions directed towards the interface by the user, the user-actuated actions, if received by the interface, execute a task on the interface; preserve a state of the interface prior to the execution of the task; translate the user-actuated actions into one or more actuation commands, the actuation commands configured to trigger one or more machine-actuated actions that replicate the user-actuated actions on the interface to cause automation of the task; and generate a training dataset to train an agent to automate the task, wherein the training dataset requires the agent to process, as input, the state of the interface prior to the execution of the task, and to generate, as output, the actuation commands.

Abstract: An example technique for image analysis is provided. An example image analysis method includes obtaining an instructive sequence descriptive of an instructive query, an instructive response, and an instructive trace of intermediate states from the instructive query to the instructive response. The example image analysis method includes inputting, to a machine-learned model, the instructive sequence and an operative image processing query that comprises image data, wherein the machine-learned model is configured to process the operative query with attention over the instructive sequence. The example method can include generating, using the machine-learned model and responsive to the operative query, an operative image processing response that comprises an analysis of the image data.