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    Patent Issued for Systems and methods for managing assignments of tasks for mini ng equipment using machine learning (USPTO 12158765)

    103-108页
    查看更多>>摘要:Patent number 12158765 is assigned to Caterpillar (Peoria, Illinois, United Stat es).The following quote was obtained by the news editors from the background informa tion supplied by theinventors: “Certain applications, such as strip mining, inv olve the transportation of aggregate material,such as ore, from a mining site t o a processing or shipping facility. Typical mining operations use guidedhaul t rucks that carry the extracted material from an extraction area or material sour ce to a depositionarea or a material sink. A typical large-scale mining operati on may include more than one material sourceand more than one material sink. Th e haul trucks used to transport the material may be autonomouslyguided, i.e., o perate without a driver. A fleet of haul trucks servicing a mine site may perfor m hundredsof trips daily, as some mining operations operate around the clock. T he loading of the aggregate materialonto the haul trucks is typically accomplis hed by use of wheeled loaders or excavators, material conveyors,shovels, and th e like. Detailed plans are put in place to manage these activities, ensuring tha t operatorsare moving the right amount of material to the right place at the ri ght time. Efficient assignment ofpersonnel and machines to various tasks may be a complex problem that may be very computationallyintensive.

    Patent Issued for Systems and methods for managing assignments of tasks for mini ng equipment using machine learning (USPTO 12158765)

    103-108页
    查看更多>>摘要:Patent number 12158765 is assigned to Caterpillar (Peoria, Illinois, United Stat es).The following quote was obtained by the news editors from the background informa tion supplied by theinventors: “Certain applications, such as strip mining, inv olve the transportation of aggregate material,such as ore, from a mining site t o a processing or shipping facility. Typical mining operations use guidedhaul t rucks that carry the extracted material from an extraction area or material sour ce to a depositionarea or a material sink. A typical large-scale mining operati on may include more than one material sourceand more than one material sink. Th e haul trucks used to transport the material may be autonomouslyguided, i.e., o perate without a driver. A fleet of haul trucks servicing a mine site may perfor m hundredsof trips daily, as some mining operations operate around the clock. T he loading of the aggregate materialonto the haul trucks is typically accomplis hed by use of wheeled loaders or excavators, material conveyors,shovels, and th e like. Detailed plans are put in place to manage these activities, ensuring tha t operatorsare moving the right amount of material to the right place at the ri ght time. Efficient assignment ofpersonnel and machines to various tasks may be a complex problem that may be very computationallyintensive.

    Patent Issued for Methods for efficient 3D SRAM-based computein- memory (USPTO 1 2159683)

    108-111页
    查看更多>>摘要:The patent’s inventors are Fouda, Mohammed Elneanaei Abdelmoneem (Irvine, CA, US ).This patent was filed on May 2, 2024 and was published online on December 3, 202 4.From the background information supplied by the inventors, news correspondents o btained the followingquote: “Artificial intelligence (AI), or machine learning, utilizes learning networks (e.g. deep neuralnetworks) loosely inspired by the brain in order to solve problems. Learning networks typically include layersof weights that weight signals (mimicking synapses) interleaved with activation lay ers that apply activationfunctions to the signals (mimicking neurons). Thus, a weight layer provides weighted input signals to anactivation layer. Neurons in the activation layer operate on the weighted input signals by applying someacti vation function to the input signals and provide output signals corresponding to the statuses of theneurons. The output signals from the activation layer are p rovided as input signals to the next weightlayer, if any. This process may be r epeated for the layers of the network. Learning networks are thusable to reduce complex problems to a set of weights and the applied activation functions. The structure ofthe network (e.g., number of layers, connectivity among the layers, dimensionality of the layers, the typeof activation function, the weights or p arameters for the network, etc.) are together known as a model.The values of th e parameters (e.g. the weights used for particular tasks) for the model are iden tified viatraining of the learning network. Moreover, learning networks can lev erage hardware, such as graphicsprocessing units (GPUs) and/or AI accelerators, which perform operations usable in machine learning inparallel. Such tools can dramatically improve the speed and efficiency with which data-heavy and other tasks can be accomplished by the learning network.

    Patent Issued for Methods for efficient 3D SRAM-based computein- memory (USPTO 1 2159683)

    108-111页
    查看更多>>摘要:The patent’s inventors are Fouda, Mohammed Elneanaei Abdelmoneem (Irvine, CA, US ).This patent was filed on May 2, 2024 and was published online on December 3, 202 4.From the background information supplied by the inventors, news correspondents o btained the followingquote: “Artificial intelligence (AI), or machine learning, utilizes learning networks (e.g. deep neuralnetworks) loosely inspired by the brain in order to solve problems. Learning networks typically include layersof weights that weight signals (mimicking synapses) interleaved with activation lay ers that apply activationfunctions to the signals (mimicking neurons). Thus, a weight layer provides weighted input signals to anactivation layer. Neurons in the activation layer operate on the weighted input signals by applying someacti vation function to the input signals and provide output signals corresponding to the statuses of theneurons. The output signals from the activation layer are p rovided as input signals to the next weightlayer, if any. This process may be r epeated for the layers of the network. Learning networks are thusable to reduce complex problems to a set of weights and the applied activation functions. The structure ofthe network (e.g., number of layers, connectivity among the layers, dimensionality of the layers, the typeof activation function, the weights or p arameters for the network, etc.) are together known as a model.The values of th e parameters (e.g. the weights used for particular tasks) for the model are iden tified viatraining of the learning network. Moreover, learning networks can lev erage hardware, such as graphicsprocessing units (GPUs) and/or AI accelerators, which perform operations usable in machine learning inparallel. Such tools can dramatically improve the speed and efficiency with which data-heavy and other tasks can be accomplished by the learning network.

    'Ai Face Decoration Texture Generation In Social Media Platform' in Patent Appli cation Approval Process (USPTO 20240404170)

    111-113页
    查看更多>>摘要:This patent application has not been assigned to a company or institution.The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Many social media platforms provide tools for u sers to add effects to images and videosbefore publishing content online. Some of these effects are applied over human faces, such as filters,stickers, and te xtures designed to make it appear as though objects or materials are present in the imagesand videos, when they actually are not, or otherwise alter or augment real world objects. These effectsare typically provided in a library of effect s, and some social media platforms allow users to create neweffects themselves. Creation is typically done manually, e.g., in image editing software, and there fore isalso typically limited to advanced users. Meanwhile, artificial intellig ence (AI) is becoming increasinglywidespread as a tool for generating images wi thout a human manually drafting the images from scratch.Attempts to use AI-gene rated images in the creation of new effects in social media thus far have requir edfurther manual adjustment to finalize the effects, limiting the usefulness of AI in this area and preventinglaypersons from creating effects.”

    'Ai Face Decoration Texture Generation In Social Media Platform' in Patent Appli cation Approval Process (USPTO 20240404170)

    111-113页
    查看更多>>摘要:This patent application has not been assigned to a company or institution.The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Many social media platforms provide tools for u sers to add effects to images and videosbefore publishing content online. Some of these effects are applied over human faces, such as filters,stickers, and te xtures designed to make it appear as though objects or materials are present in the imagesand videos, when they actually are not, or otherwise alter or augment real world objects. These effectsare typically provided in a library of effect s, and some social media platforms allow users to create neweffects themselves. Creation is typically done manually, e.g., in image editing software, and there fore isalso typically limited to advanced users. Meanwhile, artificial intellig ence (AI) is becoming increasinglywidespread as a tool for generating images wi thout a human manually drafting the images from scratch.Attempts to use AI-gene rated images in the creation of new effects in social media thus far have requir edfurther manual adjustment to finalize the effects, limiting the usefulness of AI in this area and preventinglaypersons from creating effects.”

    Patent Issued for Compliant perimeter end effectors (USPTO 12157222)

    113-115页
    查看更多>>摘要:Patent number 12157222 is assigned to Softwear Automation Inc. (Cumming, Georgia , United States).The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “In automated production of sewn materials, impr oper handling of the material by robotic end effectors to manipulate materials o n a worksurface can result in production of out-of-spec products,which has an i mmediate economic impact. For example, slip between the material being sewn and the endeffector controlling the movement of the material can produce flawed and unacceptable product. Materialslip can be especially prevalent for products wi th non-slip or high friction backings (as is common inmats and rugs) as the end effector must apply substantially more force to the product to move it across aworksurface.

    Patent Issued for Compliant perimeter end effectors (USPTO 12157222)

    113-115页
    查看更多>>摘要:Patent number 12157222 is assigned to Softwear Automation Inc. (Cumming, Georgia , United States).The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “In automated production of sewn materials, impr oper handling of the material by robotic end effectors to manipulate materials o n a worksurface can result in production of out-of-spec products,which has an i mmediate economic impact. For example, slip between the material being sewn and the endeffector controlling the movement of the material can produce flawed and unacceptable product. Materialslip can be especially prevalent for products wi th non-slip or high friction backings (as is common inmats and rugs) as the end effector must apply substantially more force to the product to move it across aworksurface.

    Patent Application Titled 'Using Generative Artificial Intelligence (Ai) For Aut omated Digital Flyer Content Generation' Published Online (USPTO 20240403923)

    116-119页
    查看更多>>摘要:No assignee for this patent application has been made.Reporters obtained the following quote from the background information supplied by the inventors:“An online system is an online platform that connects users an d retailers. A user can place an order forobtaining items, such as groceries, f rom participating retailers via the online system, with the shoppingbeing done by a picker. After the picker finishes shopping, the order is delivered to the u ser’s address. Insome instances, the online system provides a communication int erface that allows a user to communicatewith a fulfillment user that is servici ng the user’s order. Oftentimes, a retailer distributes flyers, whichadvertise one or more items and provide information about the sale of those items to users of the onlinesystem.

    Patent Application Titled 'Using Generative Artificial Intelligence (Ai) For Aut omated Digital Flyer Content Generation' Published Online (USPTO 20240403923)

    116-119页
    查看更多>>摘要:No assignee for this patent application has been made.Reporters obtained the following quote from the background information supplied by the inventors:“An online system is an online platform that connects users an d retailers. A user can place an order forobtaining items, such as groceries, f rom participating retailers via the online system, with the shoppingbeing done by a picker. After the picker finishes shopping, the order is delivered to the u ser’s address. Insome instances, the online system provides a communication int erface that allows a user to communicatewith a fulfillment user that is servici ng the user’s order. Oftentimes, a retailer distributes flyers, whichadvertise one or more items and provide information about the sale of those items to users of the onlinesystem.