Abstract: A shopping cart is configured to roll along a supporting surface and includes a chassis, a basket, a rear leg, a rear wheel, and a rotational brake. The basket is supported above the chassis. The rear leg extends downwardly from the chassis. The rear wheel is rotatably coupled to the rear leg and is configured to rotate about a rotational axis. The rear wheel defines an outside perimeter configured to contact and roll along the supporting surface. A rotational brake is coupled to the rear leg and extending radially away from the rotational axis in a rearward and downward direction beyond an outside perimeter of the rear wheel. The rotational brake is configured to impede rotation of the chassis and the basket about the rotational axis.

Abstract: A shopping cart for use in forming a horizontal stack of shopping carts that includes a support frame, a basket, and a lifting fender. The support frame includes a chassis and support masts extending substantially vertically from the chassis. The chassis is coupled to front wheels and rear wheels and includes a rear cross bar extending across the chassis. The basket is supported by the support masts over the chassis and defines a compartment. The lifting fender is formed separately from the support frame and is selectively coupled to an underside of the rear cross bar. The lifting fender defines a lift section extending below the rear cross bar and defines a bottom surface configured to be the initial contact point for a second, rear shopping cart when the horizontal stack of shopping carts is formed decreasing contact between the second, rear shopping cart and the rear cross bar.

Abstract: An interactive visualization tool for displaying metrics associated with inventory related output from a replenishment simulation for an enterprise supply chain is described. Predicted values for metrics associated with simulation output may be received on a per item, per node, per epoch basis for a plurality of items associated with the supply chain at a plurality of nodes of the supply chain over a plurality of epochs. A visualization tool user interface may be rendered that includes item and node menus enabling user selection of varying granularity levels for viewing the metrics. The metrics may be aggregated according to a presently selected level of granularity, and represented within a single graphical view of the user interface to visualize projected inventory positions of items across nodes of the supply chain. The aggregated metrics may include an expected projection and a worst-case projection for one or more types of the metrics.

Abstract: A spoutless training lid assembly of a sippy cup includes a collar and a valve. The collar is configured to couple to a vessel and has an outer wall, an inner wall, an upper portion configured to be located outside the vessel and including an upper peripheral rim and a lower portion configured to be located inside the vessel and including a lower peripheral edge. The collar includes a peripheral shelf located about the inner wall. The valve is inserted into the collar and includes a flexible gasket over-molded to a rigid baffle to form a single, separable component. The gasket extends from a plate of the baffle and terminates at an outer peripheral edge that engages with the rim of the collar. The baffle secures to the shelf and portions of a perimeter edge of the plate of the baffle abut the inner wall of the collar.

Abstract: The present disclosure provides methods and systems for tracking a shipping vessel travel route through a retail enterprise during a stock cycle. Location information associated with assets can be collected at a retail location, from which a detailed route through the retail location may be recreated and overlaid on map data reflecting a retail location layout. Further analysis may be performed on the route. Additionally, the route may be overlaid on a map, including product information and packaging information, allowing for various metrics and metric visualizations to be generated that can be further analyzed to achieve various objectives.

Abstract: A computer-implemented method is performed in a machine having at least one processor and storage. The at least one processor executes an agent and a host that are both stored in the storage. The at least one processor's execution of the agent causes the at least one processor to create a new partition of the storage while the at least one processor is executing the host. The at least one processor's execution of the agent causes the at least one processor to store a new operating system in the new partition of the storage while the at least one processor is executing the host. The at least one processor's execution of the agent causes the at least one processor to reboot the machine into the new partition to cause the at least one processor to execute the new operating system.

Abstract: Methods and systems for performing multi-task learning of query intent and named entities are provided. One method includes receiving a query comprising query text. The method further includes providing the query text to a neural network model implemented on a computing system, the neural network model having a plurality of layers, wherein at least one layer comprises a plurality of loss functions including a named entity tag learning loss function and an intent classification loss function. The method also includes obtaining, from the neural network model, an identification of a named entity and a query intent derived from the query text. A query response may be formulated based, at least in part, on the named entity and query intent.

Abstract: In some implementations, a system for verifying items in a retail environment includes a physical shopping cart including a first set of sensors, and an automated checkout station including a second, different set of sensors. The physical shopping cart receives item verification data for verifying an item, detects the item as it enters the physical shopping cart, and performs a primary verification of the item. The automated checkout station obtains a virtual shopping cart that corresponds to the physical shopping cart. The virtual shopping cart includes a list of items that have been placed in the physical shopping cart, and a verification status of each item. The second, different set of sensors generate station sensor data that represents the physical shopping cart and the items in the physical shopping cart. A secondary verification of the physical shopping cart and its contents is performed by the automated checkout station.

Abstract: Devices and systems can be used to enhance warehouse material handling operations. For example, this document describes pallet stands that make material handling processes more safe and efficient. In some embodiments, a pallet stand described herein includes a structure comprising a top configured for a pallet to rest on and a pedestal arranged to elevate the structure above a floor. The pedestal has an outer size that is less than the width of the top structure and less than the length of the top structure.

Abstract: A clustering and routing platform that applies capacity constraints at individualized routes as part of the process of clustering deliveries into groups is provided. In particular, vehicle capacity, route length, route efficiency/timing, and various other constraints may be used as part of the clustering process to better group delivery locations into routes.

Abstract: Methods and systems for generating and distributing data visualizations are provided. One method includes displaying a user interface including a canvas and a card builder toolset, the card builder toolset including a plurality of selectable options, each of the plurality of selectable options responsive to user input to present a definition screen including one or more card definition parameter input fields. The method further includes receiving user input into the one or more card definition parameter input fields for each of the plurality of selectable options and, in response, defining at least one aspect of a card to be included within a user dashboard presented on the canvas. The method also includes rendering a card within the canvas in accordance with parameters defined by the user input, the card being included within a dashboard to be displayed to users.

Abstract: Methods, systems, and platforms for managing machine learning models are described. A model registry system receives first data including a model and second data including metadata and at least one metric of the model. Via a local network, the first data is stored to a data storage device and the second data is sent to an application programming interface (API). The first data is retrieved from the data storage device to a model use case program operating in a software development environment native to where the model registry system stores the model. The second data, including the metadata and the at least one metric of the model, is sent to a user interface (UI) via the API. The stored model can be deployed from the model use case program via the API.