Abstract: A method and system having instructions to perform actions include obtaining images of an agricultural environment including a first image comprising at least one background portion and one or more regions of interest, implementing a machine learning (ML) algorithm on a portion of the first image including a portion of the background portion and the one or more regions of interest, detecting a plurality of objects associated with a plurality of real-world objects in the agricultural environment in at least one region of interest in the one or more regions of interest of the first image including detecting a first object and detecting a second object, implementing a second algorithm on the portion of the first image comprising the first object to detect one or more divided features of the first object, tracking a feature of the one or more divided features across subsequent images as the moving platform traverses the agricultural environment, tracking the second object, and selecting a target action configured

Abstract: Techniques described herein are directed to determining that multimedia content displays a representation of an item offered for sale (1) at a first timestamp and (2) at a first location relative to a viewable window of a user device; generating an interactive element comprising an e-commerce tag interactable for purchase of the item; rendering, at the first timestamp, the interactive element on a first portion of the multimedia content and positioned relative to the representation of the item in a predetermined spatial configuration in the viewable window; rendering, at a second timestamp, the interactive element on a second portion of the multimedia content and positioned relative to the representation in the same spatial configuration; detecting an interaction with the interactive element; and based on detecting the interaction, displaying a graphical user interface configured to allow the user to purchase the item.

Abstract: A compute device can access local or remote accelerator devices for use in processing a received packet. The received packet can be processed by any combination of local accelerator devices and remote accelerator devices. In some cases, the received packet can be encapsulated in an encapsulating packet and sent to a remote accelerator device for processing. The encapsulating packet can indicate a priority level for processing the received packet and its associated processing task. The priority level can override a priority level that would otherwise be assigned to the received packet and its associated processing task. The remote accelerator device can specify a fullness of an input queue to the compute device. Other information can be conveyed by packets transmitted between and among compute devices and remote accelerator devices to assist in determining an accelerator to use or other uses.

Abstract: Multi-port Media Control Channel (MAC) with flexible data-path width. A multi-port receive (RX) MAC block includes multiple RX ports and a plurality of RX circuit blocks comprising an RX MAC pipeline for performing MAC Layer operations on RX data received at the RX ports. The RX circuit blocks are connected with variable-width datapath segments, and the RX MAC block is configured to implement a multi-port arbitration scheme such as a TDM (Time-Division Multiplexed) scheme under which RX data received at a given RX port are forwarded over the variable-width datapath segments using datapath widths associated with that RX port. A multi-port transmit (TX) MAC block implementing a TX MAC pipeline comprising TX circuit blocks connected with variable-width datapath segments is also provided. The RX and TX MAC blocks include CRC modules configured to calculate CRC values on input data received over datapaths having different widths.

Abstract: Techniques described herein are directed to receiving audio input during playback of multimedia content to trigger purchase and payment for an item represented in the multimedia content. In an example, multimedia content is sent to a user device. The multimedia content may contain a representation of an item and an indication that the item can be purchased. Based on receipt of an indication that trigger words were spoken during playback, a recording is initiated. A purchase intent of the user for the item is determined based on the recording. A graphical user interface is displayed via the user device to initiate payment by the user for the item.

Abstract: A method and system having instructions to perform actions include obtaining images of an agricultural environment including a first image comprising at least one background portion and one or more regions of interest, implementing a machine learning (ML) algorithm on a portion of the first image including a portion of the background portion and the one or more regions of interest, detecting a plurality of objects associated with a plurality of real-world objects in the agricultural environment in at least one region of interest in the one or more regions of interest of the first image including detecting a first object and detecting a second object, implementing a second algorithm on the portion of the first image comprising the first object to detect one or more divided features of the first object, tracking a feature of the one or more divided features across subsequent images as the moving platform traverses the agricultural environment, tracking the second object, and selecting a target action configured

Abstract: A composition for detoxifying insect pollinators from one or more organophosphate pesticides, the composition containing microparticles comprising: (i) a phosphotriesterase; (ii) nanoparticles; and (iii) a surface active agent. Also disclosed herein is an aqueous suspension comprising the above-described detoxifying microparticles in an external aqueous medium, which may also contain an insect pollinator attractant. Also described herein is a method for detoxifying insect pollinators of one or more organophosphate pesticides, the method comprising placing the detoxifying aqueous suspension in a location accessible to the insect pollinators to permit the insect pollinators to ingest the detoxifying aqueous suspension, wherein the detoxifying aqueous suspension comprises microparticles, as described above, suspended in an external aqueous medium, typically also including an insect pollinator attractant in the external aqueous medium.

Abstract: Multi-port Media Control Channel (MAC) with flexible data-path width. A multi-port receive (RX) MAC block includes multiple RX ports and a plurality of RX circuit blocks comprising an RX MAC pipeline for performing MAC Layer operations on RX data received at the RX ports. The RX circuit blocks are connected with variable-width datapath segments, and the RX MAC block is configured to implement a multi-port arbitration scheme such as a TDM (Time-Division Multiplexed) scheme under which RX data received at a given RX port are forwarded over the variable-width datapath segments using datapath widths associated with that RX port. A multi-port transmit (TX) MAC block implementing a TX MAC pipeline comprising TX circuit blocks connected with variable-width datapath segments is also provided. The RX and TX MAC blocks include CRC modules configured to calculate CRC values on input data received over datapaths having different widths.

Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.

Abstract: Welded headgear sections can be produced by using a weld tool having pins protruding from a weld region contact surface to deliver high-frequency electromagnetic energy to a weld region defined by overlapping top and bottom headgear straps. The pins fully penetrate the top strap and at least partially penetrate the bottom strap. The pins concentrate the electromagnetic energy to achieve a weld joint of acceptable weld strength and aesthetic appeal.

Abstract: A method implemented by a treatment system disposed on a vehicle, the treatment system having one or more processors, a storage, and a treatment mechanism, includes capturing a first image of a region of an agricultural environment, detecting, by implementing a first machine learning (ML) algorithm on a first portion of the first image, a presence of at least a portion of a first object in the first image, determining whether the first object detected is a treatment candidate, determining, upon determining that the first object is a treatment candidate, a first three dimensional (3D) location of at least a portion of the first object in the agricultural environment, and applying, a treatment to at least the portion of the first object by activating the treatment mechanism to interact with the first object.

Abstract: Techniques described herein are directed to e-commerce tags in multimedia content. In an example, multimedia content is received and item-recognition techniques are performed to identify one or more items referenced in the content. An interactive element is generated that indicates information about a given referenced item, and that interactive element is displayed while the multimedia content is output. Selection of the interactive element may cause a purchasing user interface to be displayed with item and/or or payment information prepopulated based at least in part on identified attributes of the item and/or user preferences determined from historical purchase data associated with the user.

Abstract: Techniques described herein are directed to interactive elements displayed in multimedia content. In an example, it is determined that multimedia content displays an item offered for sale by a merchant. Based on so determining, an interactive element is rendered that displays a representation of the item offered for sale by the merchant in place of a portion of the multimedia content. When an interaction by a user with the interactive element is detected, a graphical user interface is displayed that is configured to allow the user to purchase the item.

Abstract: Welded headgear sections can be produced by using a weld tool having pins protruding from a weld region contact surface to deliver high-frequency electromagnetic energy to a weld region defined by overlapping top and bottom headgear straps. The pins fully penetrate the top strap and at least partially penetrate the bottom strap. The pins concentrate the electromagnetic energy to achieve a weld joint of acceptable weld strength and aesthetic appeal.

Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.

Abstract: A modular slide for use on a staircase includes at least a first slide module with an entry section having an entry surface defining a seat and a gripping surface substantially opposite the entry surface. The modular slide also has a ramp section with an elongated surface extending from the entry section towards a terminal end of the ramp section, an underside being configured to rest upon portions of the staircase, and two opposing sidewalls spanning both the ramp section and the entry section and having an upper edge defining a handrail. An identical second slide module is configured to overlap and integrate with an upper portion of the first slide module to form a continuous slide surface and a continuous handrail of an extended modular slide.

Abstract: A method of processing agricultural images includes comparing object detections performed by multiple image processing schemes to determine a set of ground truth images from which at least one machine learning (ML) models used by at least one ML algorithm included in the multiple image processing schemes is trained, wherein the multiple image processing schemes include two or more of (a) an image processing scheme that includes a cascade of multiple ML algorithms; (b) an image processing scheme that includes image annotation based on user feedback; or (c) an image processing scheme that includes a cascade of an ML algorithm or a computer vision (CV) algorithm and a user feedback.

Abstract: A computer-implemented method of sensor input processing, implemented by an agricultural platform comprising a processor and a sensor includes receiving sensor input from the sensor; processing the sensor input by multiple machine learning (ML) algorithms, each using a corresponding ML model for generating labels for objects identified in the sensor input; combining labels generated by each ML algorithm to generate a super-imposed labeled sensor input frame; comparing outputs of the ML algorithms to determine similarities or differences; and using results of the comparing for improving an operational characteristic of the sensor input processing.

Abstract: A computer-implemented method includes performing, using a processor onboard a vehicle, a machine learning (ML) processing on sensor input from sensors onboard an agricultural vehicle, identifying, according to a rule, a subset of data resulting from the ML processing and generating and displaying, in real-time, the subset of data to a user interface, thereby enabling a user interaction with the subset of data.