Micron Technology Incorporated

Libo Wang

Di Wu

Debra M Bell

James S Rehmeyer

Anthony D Veches

Carla L Christensen

Reshmi Basu

Xiao Li

Swetha Barkam

Lavanya Sriram

Anshika Sharma

Bethany M Grentz

Sumana Adusumilli

Brett Kenneth Dodds

James D Huffaker

Kim M Hartnett

Ajay Raghunathan

Linmiao Zhang

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.

Instructive actions based on categorization of input data

A size comparison system may generate a size comparison by determining a size of an item based on extracted size data corresponding to the item. A comparison item is selected and the size comparison is generated between the item and the comparison item based on the size of the item. A visual rendering of the item and the comparison item is generated based on the size comparison and is displayed to a user.

Size comparison methods including online commerce examples utilizing same

Systems for weather sensing and forecasting, and associated devices and methods, are disclosed herein. In some embodiments, a system for predicting a subject's perception of weather conditions is provided. The system can generate an individual profile for the subject, the individual profile including health information of the subject. The system can receive weather data including a first weather condition for a target location. The system can compare the individual profile to a plurality of different user profiles to identify one or more similar user profiles. Each similar user profile can (1) be associated with a user having similar health information as the subject, and (2) include weather perception data indicating how the user perceived a set of second weather conditions. Based on the weather data and the similar user profile(s), the system can generate a prediction of the how the subject will perceive the first weather condition.

Systems for generating personalized and/or local weather forecasts

Methods and systems associated with data modification are described. Examples can include receiving, at a controller of a device, data associated with a read or write command transmitted to a memory resource and modifying the data using logic before transmitting the data to a host or image sensor or before writing the data to the memory resource. The modification can include removing one or more bits from the data, reordering one or more bits of the data, changing a format of the data, or any combination thereof. The modified data can be transmitted to the host or image sensor or written to the memory resource. In some examples, a plurality of memory devices can combine modified data for transmitting to a host.

Data modification

Systems, apparatuses, and methods related log compression are described. In an example, a system log that identifies targeted data may be compiled in a memory resource during an execution of an operation using that memory resource. The system log may be analyzed utilizing a portion of the memory resource that would otherwise be available to be utilized in the execution of the operation. The system log may be compressed during the execution of the operation, the level or timing of such compression may be based on the analysis that occurs contemporaneous to or as a result of executing the operation. In some examples, compressing the system log may include discarding a portion of the system log. Compressing the system log may also include extracting the targeted data from the system log as the system log is being compiled and converting the extracted targeted data to structured data.

Log compression

Embodiments of the disclosure are drawn to apparatuses, systems, methods, and memories that are capable of performing pattern matching operations within a memory device. The pattern matching operations may be performed on data stored within the memory based on a pattern stored in a register. The result of the pattern matching operation may be provided by the memory. The data on which the pattern matching operation is performed may not be output from the memory during the pattern matching operation.

Apparatuses and methods for on-memory pattern matching

Tracking circuitry may be used to determine if commands and/or command sequences include illegal commands and/or illegal command sequences. If the commands and/or command sequences include illegal commands and/or illegal command sequences, the tracking circuitry may activate signals that prevent execution of the commands and/or notice of the detected illegal commands and/or command sequences.

Apparatuses and methods for detecting illegal commands and command sequences

Embodiments of the disclosure are drawn to apparatuses, systems, methods for an internet of things (IoT) system to include edge devices that perform at least some functions without communicating with a cloud computing system. An edge device may include a memory with on-memory pattern matching capabilities. The edge device may perform pattern matching operations on data collected by the edge device or sensors in communication with the edge device. Based on results of the pattern matching operations, the edge device may perform various functions, such as transmitting data to the cloud computing system, activating an alarm, and/or changing a frequency at which data is transmitted.

Apparatuses and methods for inference processing on edge devices

Embodiments of the disclosure are drawn to apparatuses, systems, methods, and memories that are capable of performing pattern matching operations within a memory device. The pattern matching operations may be performed on data stored within the memory based on a pattern stored in a register. The result of the pattern matching operation may be provided by the memory. The data may be retrieved from a memory array for the pattern matching operation by a read operation, a refresh operation, an error correction operation, and/or a pattern matching operation. The data may be retrieved from incoming data input lines instead of or in addition to the memory array. How the data is stored or retrieved for pattern matching operations may be controlled by a memory controller.

Apparatuses and methods for interfacing on-memory pattern matching

Embodiments of the disclosure are drawn to apparatuses, systems, methods for performing operations associated with machine learning. Machine learning operations may include processing a data set, training a machine learning algorithm, and applying a trained algorithm to a data set. Some of the machine learning operations, such as pattern matching operations, may be performed within a memory device.

Growing community of inventors

Boise, ID, United States of America

Libo Wang