Abstract: This relates to intelligent automated assistants and, more specifically, to intelligent context sharing and task performance among a collection of devices with intelligent automated assistant capabilities. An example method includes, at a first electronic device participating in a context-sharing group associated with a first location: receiving a user voice input; receiving, from a context collector, an aggregate context of the context-sharing group; providing at least a portion of the aggregate context and data corresponding to the user voice input to a remote device; receiving, from the remote device, a command to perform one or more tasks and a device identifier corresponding to a second electronic device; and transmitting the command to the second electronic device based on the device identifier, wherein the command causes the second electronic device to perform the one or more tasks.

Abstract: Various embodiments include a filling apparatus that can be connected to a valve on a keg, such as a Sankey-D valve, and can be used to pour alcohol and other liquids into the keg, which may be pre-filled with a non-alcoholic drink mix. The filling apparatus has an upper structure which is coupled to a lower portion configured to mate with a keg valve. The filling apparatus may be designed to depress portions of the keg valve to allow for both filling and venting of the keg simultaneously. The filling apparatus may further be designed with features to prevent liquid escape during degassing of the keg. The filling apparatus may include a Sankey-D coupler or a coupler with a probe portion as the lower body portion.

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

Abstract: This relates to intelligent automated assistants and, more specifically, to intelligent context sharing and task performance among a collection of devices with intelligent automated assistant capabilities. An example method includes, at a first electronic device participating in a context-sharing group associated with a first location: receiving a user voice input; receiving, from a context collector, an aggregate context of the context-sharing group; providing at least a portion of the aggregate context and data corresponding to the user voice input to a remote device; receiving, from the remote device, a command to perform one or more tasks and a device identifier corresponding to a second electronic device; and transmitting the command to the second electronic device based on the device identifier, wherein the command causes the second electronic device to perform the one or more tasks.

Abstract: A farming machine is configured to autonomously operate in a field to accomplish a farming objective. While doing so the farming machine can dynamically modify treatment plans and/or generate experimental treatment plans. Dynamically modifying treatment plans includes modifying, delaying, accelerating, adding, and/or removing farming actions in a treatment plan. Generating an experimental treatment plan includes intentionally modifying a treatment plan to induce a variance in a result, measuring the result, and determining whether the result from the experimental treatment plan is better than the unmodified treatment plan. The farming machine is also configured to generate user interactable feedback, and receive user generated instruction, to dynamically modify treatment plans and/or generate experimental treatment plans.

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

Abstract: Historical information is accessed that describes a previous state of a field, previous environmental conditions for the field, and previous farming machine actions performed in the field. A tank management model is applied to the historical information to determine expected weed densities within field portions and an amount of treatment fluid required to treat plants within the field. While the farming machine is treating plants in the field, current information describing a current state of the field is accessed. The tank management model is applied to the current information to determine updated weed densities within field portions not yet treated. The farming machine performs a modified plant treatment action based on the updated weed densities and a comparison of a remaining amount of treatment fluid within a tank of the farming machine and an updated amount of treatment fluid for treating plants within field portions not yet treated.

Abstract: A vehicle moves through an environment (e.g., a farming, construction, mining, or forestry environment) and performs one or more actions in the environment. Portions of the environment may include moisture, such as puddles or mud patches. A control system associated with the vehicle may include a traversability model or a moisture model to help the vehicle operate in the environment with the moisture. In particular, the control system may employ the traversability model to reduce the likelihood of the vehicle attempting to traverse an untraversable portion of the environment, and the control system may employ the moisture model to reduce the likelihood of the vehicle performing an action that will damage a portion of the environment.

Abstract: Embodiments of a system as described herein may receive financial institution product information from a plurality of financial institutions distributed across a computing network. The system may also receive data from the plurality of financial institutions distributed across the computer network and create or update an ontology. A relevance score may be generated for a set of financial institution products which may, in conjunction with a campaign definition provided by a financial institution administrator, be used to associate users with a list of campaigns which may be stored as campaign data. An online banking application at a user device may request campaign data for a user. In response, the system may return campaign data for the user to the online banking application. Using the campaign data, the online banking application may select one or more products to recommend to the user and display content for the selected products on the user device.

Abstract: A system may generate a prescription file including a plurality of data fields, assign the prescription file to a first queue for processing, provide a first queue GUI that includes the plurality of data fields grouped in a plurality of information modules and indicates an approval status of each information module, and receive user input editing one or more data fields. The system may assign the prescription file to a second queue, provide a second queue GUI that includes the plurality of information modules and indicates the approval status of each information module, and receive user input setting the approval status of each information module. If an information module is not approved, the system may reassign the prescription file to the first queue. If all information modules are approved, the system may assign the prescription file to a third queue for further processing.

Abstract: Embodiments of a system as described herein may receive financial institution product information from a plurality of financial institutions distributed across a computing network. The system may also receive data from the plurality of financial institutions distributed across the computer network and create or update an ontology. A relevance score may be generated for a set of financial institution products which may, in conjunction with a campaign definition provided by a financial institution administrator, be used to associate users with a list of campaigns which may be stored as campaign data. An online banking application at a user device may request campaign data for a user. In response, the system may return campaign data for the user to the online banking application. Using the campaign data, the online banking application may select one or more products to recommend to the user and display content for the selected products on the user device.

Abstract: The disclosed computer-implemented method may include (1) identifying an artificial neural network comprising a set of nodes interconnected via a set of connections, and (2) training the artificial neural network by, for each connection in the set of connections, determining a quantized weight value associated with the connection. Determining the quantized weight value associated with the connection may include (1) associating a loss function with the connection, the loss function including a periodic regularization function that describes a relationship between an input value and a weight value of the connection, (2) determining a minimum of the associated loss function with respect to the weight value in accordance with the periodic regularization function, and (3) generating the quantized weight value associated with the connection based on the determined minimum of the loss function. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A fuel system for an internal combustion engine includes a pressurized fuel supply, and a fuel injector fluidly connected to the pressurized fuel supply. The fuel injector includes a valve seat plate forming a valve seat, an injection control valve, and a nozzle cavity. A filter, which can include a 2-dimensional filter, is positioned partially within the valve seat plate and partially within an injector body to filter an incoming flow of high-pressure fuel. The valve seat plate and filter are integrated in a valve seat plate and filter assembly.

Abstract: A smoking device has an inner cylinder receivable within an outer cylinder, the inner cylinder having a combustion chamber, an air chamber, a mouthpiece, and one or more air chamber slots and combustion chamber slots; the outer cylinder having a bore hole for receiving the inner cylinder, a smoke channel, and one or more bore slots. In some examples, the inner cylinder and outer cylinder have one or more magnets for securing the inner cylinder to the outer cylinder and for aligning the air and combustion chamber slots with the bore slots. A user may rotate the inner cylinder in relation to the outer cylinder, thereby changing which air and combustion slots are aligned with the bore slots and the smoke channel. As a result of the various alignments, a user is able to vary the temperature, taste, fuel-to-air ratio, and other factors.

Abstract: A treatment mechanism for dispensing treatment fluid onto one or more plants in a field is described. The treatment mechanism includes a valve for regulating the dispensing of treatment fluid and a nozzle holder comprising a plurality of nozzles. Each nozzle is configured to dispense treatment fluid and to couple to the valve. The treatment mechanism further includes a control system configured to receive a plant treatment instruction for treating the plants. The plant treatment instruction includes a treatment position for the nozzle holder. The control system is further configured to determine a current position of the nozzle holder and adjust the current position of the nozzle holder to the treatment position for the nozzle holder. The control system is further configured to actuate the treatment mechanism such that the plants are treated via a nozzle of the plurality of nozzles.