Abstract: Techniques for dynamic pull planning involve (i) determining an update to a master schedule for a construction project that comprises tasks having respective scheduled start dates, (ii) executing a machine learning model that has been trained with historical construction project schedule data and thereby identifying candidate tasks each available for commencement earlier than its scheduled start date, (iii) causing a client station to display each identified task, its scheduled start date, a respective new start date, and an impact on the master schedule if the task is commenced on the respective new start date, (iv) receiving user input indicating selection of a given task that is to be commenced earlier than its scheduled start date, (v) and causing transmission of a notification to a party responsible for completing the given task indicating that the given task has been nominated for earlier commencement and requesting approval for the earlier commencement.

Abstract: A computing platform is configured to: (i) train a large language model (LLM) by carrying out a first machine learning process on a first training data set that includes first construction-based data associated with one or more of a user, a plurality of reference construction projects, a construction-based application of the computing platform, or combinations thereof, (ii) receive a request to generate a construction activity summary, which includes a context-based prompt, (iii) generate the construction activity summary by inputting the request into the LLM, the construction activity summary including a contextual response, and (iv) retrain the LLM by carrying out a second machine learning process on a second training data set that includes the first training data set and one or more of the context-based prompt, the construction project data, an evaluation, the contextual response, the construction activity summary, a given timeframe, the request, input, or combinations thereof.

Abstract: A computing system is configured to determine an update to a master schedule for a construction project that comprises a plurality of tasks, each task comprising a respective scheduled start date; execute a machine learning model that has been trained with historical construction project schedule data and thereby identify one or more tasks that is each a candidate for commencement earlier than its scheduled start date; cause a client station to display each identified task, its scheduled start date, a respective new start date, and an impact on the master schedule if the task is commenced on the respective new start date; receive user input indicating a selection of a given task that is to be commenced earlier than its scheduled start date; and cause a notification to be transmitted to a party responsible for completing the given task indicating that the given task has been nominated for earlier commencement and requests approval for earlier commencement.

Abstract: An example computing platform is configured to: obtain a two-dimensional drawing of a portion of a construction project; perform an image processing analysis of the two-dimensional drawing to identify one or more location entities within the two-dimensional drawing; derive embeddings for each location entity in the two-dimensional drawing; based on the derived embeddings, determine relationships between the one or more location entities; and based on the determined relationships between the one or more location entities, generate a location entity data taxonomy that includes each identified location entity as a respective node that is related to at least one other location entity.

Abstract: A computing system is configured to determine an update to a master schedule for a construction project that comprises a plurality of tasks, each task comprising a respective scheduled start date; execute a machine learning model that has been trained with historical construction project schedule data and thereby identify one or more tasks that is each a candidate for commencement earlier than its scheduled start date; cause a client station to display each identified task, its scheduled start date, a respective new start date, and an impact on the master schedule if the task is commenced on the respective new start date; receive user input indicating a selection of a given task that is to be commenced earlier than its scheduled start date; and cause a notification to be transmitted to a party responsible for completing the given task indicating that the given task has been nominated for earlier commencement and requests approval for earlier commencement.

Abstract: A shoelace substitute approximates the look and function of a shoelace and includes a length of elastic material and two barbs. The barbs are each placed at and contain one of the ends of the elastic material, being crimped around the end of the elastic material to form a T. The barbs are sized to be inserted through eyelets of the shoe to connect opposite eyelets in the same manner as a shoelace. An associated method allows for replacement of the shoelace with a number of such shoelace substitutes, each connecting a pair of eyelets. The color and shape of the elastic material may be varied to coordinate with various kinds of shoes. The effect is to create a “slip-on” shoe from a “lace-up” shoe.