Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: Performing, at a first time, a calibration and configuration of a display magnification management model, including: identifying contextual data associated with contextual inputs of a user including a blink rate and a distance between the user and the display device; identifying display settings of the GUI; training, based on the contextual data and the display settings, the display magnification management model, including generating a configuration policy including configuration rules for performing computer-implemented actions to automatically adjust the magnification level of the GUI; performing, at a second time, a steady-state management of the magnification level of the GUI, including: monitoring the contextual inputs of the of the user, in response, i) accessing the display magnification management model, ii) identifying configuration rules based on the display settings and the monitored contextual inputs, and iii) applying the configuration rules to perform computer-implemented actions to automatical

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.

Abstract: Techniques are described herein that overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.

Abstract: A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.

Abstract: Techniques are described herein that overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.

Abstract: Techniques are described herein that overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: A performance testing and analysis environment performs tests on programming code and identifies any performance regressions. Tests exhibiting performance regressions are rerun, and the initial regressions are confirmed as genuine regressions or not. Analysis of the code under test and the performance under the tests are analyzed. The root causes of the performance regressions are identified. The process is fully automated and is performed quickly.

Abstract: Techniques are described herein that overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.

Abstract: Techniques are described herein that overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.

Abstract: Techniques are described herein that overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.

Abstract: These techniques described herein overcome the limitations of conventional techniques by bridging a gap between user interaction with digital content using a computing device and a user's physical environment through use of augmented reality content. In one example, user interaction with augmented reality digital content as part of a live stream of digital images of a user's environment is used to specify a size of an area that is used to filter search results to find a “best fit”. In another example, a geometric shape is used to represent a size and shape of an object included in a digital image (e.g., a two-dimensional digital image). The geometric shape is displayed as augmented reality digital content as part of a live stream of digital images to “assess fit” of the object in the user's physical environment.