Abstract: An apparatus that forms bundles of glass articles includes a glass article infeed station including an infeed conveyor that continuously transports individual glass articles to a layer separating conveyor. The layer separating conveyor includes a conveyor belt that forms a layer of side-by-side glass articles. A robotic lift assembly is configured to place the layer of side-by-side glass articles together on a layer separation insert. The layer separation insert has side-by-side slots that each receive a single glass article of the layer of side-by-side glass articles.

Abstract: In embodiments, a computer system produces a first resource for a first dataset having a time indicator, by applying a first digital rule. A first notification can be caused to be transmitted about an aspect of the first resource to a remote device. A second dataset can be stored, which has values derived from the first dataset, and encodes a parameter of the first resource. A second digital rule may be stored to replace the first digital rule, at an updating time (Tupd). The second digital rule may have an effective time (Teff) prior to the actual updating time Tupd. A second resource may be produced by applying the second digital rule. A second notification can be caused to be transmitted about an aspect of the second resource to a remote device.

Abstract: A system may learn what parameters are required for an item in order to compute tax for the item based on preliminary data regarding the item and/or the transaction. The system may determine a classification code based on such preliminary data and use that classification code to search or query a database storing information indicative of parameters required to compute tax for items having such a classification code. The system may map the received preliminary data into the learned required parameters and determine whether there are any required parameters for which there has not been any preliminary data mapped into them. The system may prompt the customer (e.g., seller of the item) or other user for data values of such missing required parameters or otherwise obtain data values of such parameters in order to compute the tax for the item.

Abstract: A system may learn what parameters are required for an item in order to compute tax for the item based on preliminary data regarding the item and/or the transaction. The system may determine a classification code based on such preliminary data and use that classification code to search or query a database storing information indicative of parameters required to compute tax for items having such a classification code. The system may map the received preliminary data into the learned required parameters and determine whether there are any required parameters for which there has not been any preliminary data mapped into them. The system may prompt the customer (e.g., seller of the item) or other user for data values of such missing required parameters or otherwise obtain data values of such parameters in order to compute the tax for the item.