Abstract: Systems, devices, and methods related to generating instructive actions based on categorization of input data are described. In an example, a method can include receiving, from an edge device and at a processing resource of a device, a plurality of input data associated with a plurality of sources communicatively coupled to the edge device and categorizing each piece of the plurality of input data as private or public based on an associated one of the plurality of sources. The categorizing can include writing each piece of data with metadata that indicates that it is private or public and/or selecting a first data path indicated as private or a second data path indicated as public. The method can include writing each piece of the plurality of input data categorized as private to a dedicated buffer or a dedicated address space of a memory resource.

Abstract: Aspects of the embodiments described herein are related to systems, methods, and computer products for performing automatic check fraud detection. Aspects of embodiments described herein provide artificial intelligence systems and methods that analyze an image of an incoming check, compare the features of the image to the associated features on a reference check, and generate a check fraud score based on the comparison, and either approve the incoming check or flag the incoming check for manual review.

Abstract: Methods, systems, and devices for operating emergency prevention sensor systems are described. Devices can include a plurality of components including a sensor component, a processor, and memory. In an example, a method can include receiving at a processor signaling from a plurality of environmental sensing devices, each having at least one biodegradable component, in an area of concern, wherein the area of concern corresponds to a particular set of coordinates in a database, determining environmental characteristics of an emergency associated with the area of concern based, at least in part, on the signaling, and determining a preventive action based on the determined characteristics. In another example, a number of components of the sensing devices are biodegradable.

Abstract: Systems, devices, and methods related to generating instructive actions based on categorization of input data are described. In an example, a method can include receiving, from an edge device and at a processing resource of a device, a plurality of input data associated with a plurality of sources communicatively coupled to the edge device and categorizing each piece of the plurality of input data as private or public based on an associated one of the plurality of sources. The categorizing can include writing each piece of data with metadata that indicates that it is private or public and/or selecting a first data path indicated as private or a second data path indicated as public. The method can include writing each piece of the plurality of input data categorized as private to a dedicated buffer or a dedicated address space of a memory resource.

Abstract: Methods, systems, and devices associated with an edge device are described. An edge device can include a processing resource and a memory resource having instructions executable to receive, at the processing resource, the memory resource, or both, and from a first source comprising a device in communication with the edge device, first input associated with a user of the device. The instructions can be executable to receive, from a second source, second input associated with a user of the device, determine, based on the first input and the second input, operational instructions for the device and transmit the operational instructions to the device. The instructions can be executable to update, using a machine learning model, the operational instructions responsive to receiving an indication of performance of the operational instructions by the device and responsive to third input received from the first source, the second source, or both.

Abstract: Methods, systems, and devices for access of a memory system based on fragmentation are described. The memory system may receive a first message indicating a set of data that the memory system is to store using a fragmentation-based write procedure. The memory system may, based on the first message, determine blocks of a memory device that satisfy a fragmentation threshold. After determining the blocks, the memory system may transmit to the host system a second message that indicates the memory system is ready to receive the set of data indicated in the first message. The memory system may then store the set of data in the determined blocks based on transmitting the second message.

Abstract: Methods, devices, and systems related to process control in manufacturing are described. In an example, a method can include receiving data from a first process control device affixed to a first manufacturing tool of a first type, identifying one or more attributes of the data via a second processing resource of a second process control device affixed to a second manufacturing tool of a second type different from the first type, determining one or more settings for the second manufacturing tool via the second processing resource in response to identifying the one or more attributes of the data, and sending a command including the one or more settings to the second manufacturing tool from the second process control device.

Abstract: Methods, systems, and devices associated with an edge device are described. An edge device can include a processing resource and a memory resource having instructions executable to receive, at the processing resource, the memory resource, or both, and from a first source comprising a device in communication with the edge device, first input associated with a user of the device. The instructions can be executable to receive, from a second source, second input associated with a user of the device, determine, based on the first input and the second input, operational instructions for the device and transmit the operational instructions to the device. The instructions can be executable to update, using a machine learning model, the operational instructions responsive to receiving an indication of performance of the operational instructions by the device and responsive to third input received from the first source, the second source, or both.

Abstract: Methods, devices, and systems related to process control in manufacturing are described. In an example, a method can include receiving data from a first process control device affixed to a first manufacturing tool of a first type, identifying one or more attributes of the data via a second processing resource of a second process control device affixed to a second manufacturing tool of a second type different from the first type, determining one or more settings for the second manufacturing tool via the second processing resource in response to identifying the one or more attributes of the data, and sending a command including the one or more settings to the second manufacturing tool from the second process control device.

Abstract: Methods, systems, and devices for access of a memory system based on fragmentation are described. The memory system may receive a first message indicating a set of data that the memory system is to store using a fragmentation-based write procedure. The memory system may, based on the first message, determine blocks of a memory device that satisfy a fragmentation threshold. After determining the blocks, the memory system may transmit to the host system a second message that indicates the memory system is ready to receive the set of data indicated in the first message. The memory system may then store the set of data in the determined blocks based on transmitting the second message.

Abstract: Methods, systems, and devices for operating emergency prevention sensor systems are described. Devices can include a plurality of components including a sensor component, a processor, and memory. In an example, a method can include receiving at a processor signaling from a plurality of environmental sensing devices, each having at least one biodegradable component, in an area of concern, wherein the area of concern corresponds to a particular set of coordinates in a database, determining environmental characteristics of an emergency associated with the area of concern based, at least in part, on the signaling, and determining a preventive action based on the determined characteristics. In another example, a number of components of the sensing devices are biodegradable.

Abstract: Methods, systems, and devices associated with an edge device are described. An edge device can include a processing resource and a memory resource having instructions executable to receive, at the processing resource, the memory resource, or both, and from a first source comprising a device in communication with the edge device, first input associated with a user of the device. The instructions can be executable to receive, from a second source, second input associated with a user of the device, determine, based on the first input and the second input, operational instructions for the device and transmit the operational instructions to the device. The instructions can be executable to update, using a machine learning model, the operational instructions responsive to receiving an indication of performance of the operational instructions by the device and responsive to third input received from the first source, the second source, or both.

Abstract: Apparatuses, and methods related machine learning (ML) with sensor information relevant to a location of a roadway are described. Memory systems including processing resource and memory resources receive sensor information from a sensor associated with a vehicle and a relevant to a location on a roadway. The received sensor information from the vehicle can be operated upon, using a ML algorithm, and an instruction can be transmitted based on ML algorithm. In an example, a method can include receiving, at a processing resource, sensor information from a sensor associated with a first vehicle and relevant to a location on a roadway, operating on the received sensor information associated with the first vehicle using a ML algorithm stored in a memory resource accessible by the processing resource, transmitting instructions relevant to the location, based on the sensor information associated with the first vehicle that was operated upon by the ML algorithm.

Abstract: Systems, devices, and methods related to generating instructive actions based on categorization of input data are described. In an example, a method can include receiving, from an edge device and at a processing resource of a device, a plurality of input data associated with a plurality of sources communicatively coupled to the edge device and categorizing each piece of the plurality of input data as private or public based on an associated one of the plurality of sources. The categorizing can include writing each piece of data with metadata that indicates that it is private or public and/or selecting a first data path indicated as private or a second data path indicated as public. The method can include writing each piece of the plurality of input data categorized as private to a dedicated buffer or a dedicated address space of a memory resource.

Abstract: Methods, devices, and systems related to process control in manufacturing are described. In an example, a method can include receiving data from a first process control device affixed to a first manufacturing tool of a first type, identifying one or more attributes of the data via a second processing resource of a second process control device affixed to a second manufacturing tool of a second type different from the first type, determining one or more settings for the second manufacturing tool via the second processing resource in response to identifying the one or more attributes of the data, and sending a command including the one or more settings to the second manufacturing tool from the second process control device.