Abstract: A method for connecting an appliance (100) to an external server (120) connected to the internet is provided. The method comprises setting-up, with the appliance, a first appliance access point (AP1) for allowing wireless communication with the appliance using a first wireless technology and a second appliance access point (AP2) for allowing wireless communication with the appliance using a second wireless technology, said first technology comprising Wi-Fi technology, and said second technology being different from said first technology. The method further comprises setting-up a wireless link between a mobile device (130) and a selected appliance access point between said first and said second appliance access points (AP1; AP2).

Abstract: A method for connecting an appliance (100) to an external server (120) connected to the internet is provided. The method comprises setting-up, with the appliance, a first appliance access point (AP1) for allowing wireless communication with the appliance using a first wireless technology and a second appliance access point (AP2) for allowing wireless communication with the appliance using a second wireless technology, said first technology comprising Wi-Fi technology, and said second technology being different from said first technology. The method further comprises setting-up a wireless link between a mobile device (130) and a selected appliance access point between said first and said second appliance access points (AP1; AP2).

Abstract: A hyperscale artificial intelligence and machine learning infrastructure includes a plurality of racks, where: at least one or more of the racks include one or more GPU servers; at least one or more of the racks include one or more storage systems; each of the racks include one or more switches coupled to at least one switch in another rack; and the one or more GPU servers are configured to execute one or more artificial intelligence or machine learning applications, wherein data stored within the one or more storage systems is used as input to the one or more artificial intelligence or machine learning applications.

Abstract: Performing disaster recovery in a cloud-based storage system, including: creating, by a storage system a snapshot of a dataset; uploading, from the storage system to a cloud computing environment, the snapshot; storing, by the cloud computing environment, the snapshot; detecting, by the cloud computing environment, that the dataset is not available on the storage system; and creating, by the cloud computing environment using the snapshot that is stored within the cloud computing environment, a cloud-based storage system that includes the dataset.

Abstract: A method for connecting an appliance (100) to an external server (120) connected to the internet is provided. The method comprises setting-up, with the appliance, a first appliance access point (AP1) for allowing wireless communication with the appliance using a first wireless technology and a second appliance access point (AP2) for allowing wireless communication with the appliance using a second wireless technology, said first technology comprising Wi-Fi technology, and said second technology being different from said first technology. The method further comprises setting-up a wireless link between a mobile device (130) and a selected appliance access point between said first and said second appliance access points (AP1; AP2).

Abstract: A dynamic object model system identifies, from a first object data definition file, a first object definition of a first object of a first entity type; and identifies, from a second object data definition file, a second object definition of a second object of a second entity type. The first object definition defines an entity identifier for the first object, and the second object definition includes the entity identifier of the first object. The dynamic object model system determines, based on an object model definition, that objects of the second entity type refer to objects of the first entity type by entity identifier. Based on the object model definition, and based on the second object definition including the entity identifier of the first object, the dynamic object model system establishes a reference relationship between the first object and the second object within an object database.

Abstract: A system for real time correction during a network device provisioning process is provided. The system includes a network device which maintains an access point connection with a user device while simultaneously attempting to establish a connection to a home network. The network device transmits status information regarding the provisioning process to the user device in real time and notifies the user of any failure in the provisioning process via an initial access point connection. The user is then given the opportunity to correct the issue without disconnecting entirely from the network device.

Abstract: Various embodiments include methods for performing maintenance on a gas turbine bearing area. In some cases, a method includes: separating sections of an inlet bellmouth of the gas turbine without removing the sections of the inlet bellmouth from the gas turbine; removing a housing from over a bearing of the gas turbine; mounting a bearing maintenance apparatus adjacent the inlet bellmouth and the bearing; and performing maintenance on the bearing area while the sections of the inlet bellmouth remain separated.

Abstract: A cantilever umbrella has an upstanding mast and a cantilever arm adapted to support a canopy. The mast has an interior region defined by a longitudinally extending channel with a longitudinally aligned opening extending from the interior to the exterior of the mast. A carriage resides within the channel and is adapted for travel within the channel. Raising the carriage within the channel causes the cantilever to transition to the open position, and lowering of the carriage causes the cantilever to transition to the closed position.

Abstract: Performing disaster recovery in a cloud-based storage system, including: creating, by a storage system a snapshot of a dataset; uploading, from the storage system to a cloud computing environment, the snapshot; storing, by the cloud computing environment, the snapshot; detecting, by the cloud computing environment, that the dataset is not available on the storage system; and creating, by the cloud computing environment using the snapshot that is stored within the cloud computing environment, a cloud-based storage system that includes the dataset.

Abstract: A hyperscale artificial intelligence and machine learning infrastructure includes a plurality of racks, where: at least one or more of the racks include one or more GPU servers; at least one or more of the racks include one or more storage systems; each of the racks include one or more switches coupled to at least one switch in another rack; and the one or more GPU servers are configured to execute one or more artificial intelligence or machine learning applications, wherein data stored within the one or more storage systems is used as input to the one or more artificial intelligence or machine learning applications.

Abstract: The present technology provides systems, methods and computer program instructions implementing machine learning techniques to enable program processes to learn more effective feedback mechanisms to achieve desired results (e.g., reduce errors, improve form, duration, speed, and so forth) of motions and poses comprising tasks being taught or guided. In implementations an automated technology for automated creation of movement assessments from labeled video and continually learning audio, video or other feedback for use with machine learning techniques enable program processes to learn more effective feedback mechanisms to achieve desired results (e.g., reduce errors, improve form, duration, speed, and so forth) of motions and poses comprising tasks being taught or guided.

Abstract: The present technology provides systems, methods and computer program instructions implementing an automated technology for automated creation of movement assessments from labeled video and continually learning audio, video or other feedback for use with machine learning techniques enable program processes to learn more effective feedback mechanisms to achieve desired results (e.g., reduce errors, improve form, duration, speed, and so forth) of motions and poses comprising tasks being taught or guided. In implementations machine learning techniques enable program processes to learn more effective feedback mechanisms to achieve desired results (e.g., reduce errors, improve form, duration, speed, and so forth) of motions and poses comprising tasks being taught or guided.

Abstract: A system and method for an adaptive graphic user interface (AGUI) (501) that can identify the characteristics of one or more users and display candidates and dynamically select display content and generate an interface (502-506 . . . ) customized to one or more users and display candidates and dynamically arrange, modify, map and adapt an AGUI display to any object (350,730), device, clothing, equipment, furniture, appliance, room, building, vehicle, person, or other passive or active display surface, screen, space or other display candidate and embodiments of an AGUI apparatus (500) that can network, coordinate and/or operate with the AGUI platform (1302) to identify one or more users and display candidates and enabling one or more users to interface with a single AGUI display across multiple display candidates.

Abstract: A system and method for an adaptive graphic user interface (AGUI) (501) that can identify the characteristics of one or more users and display candidates and dynamically select display content and generate an interface (502-506 . . . ) customized to one or more users and display candidates and dynamically arrange, modify, map and adapt an AGUI display to any object (350,730), device, clothing, equipment, furniture, appliance, room, building, vehicle, person, or other passive or active display surface, screen, space or other display candidate and embodiments of an AGUI apparatus (500) that can network, coordinate and/or operate with the AGUI platform (1302) to identify one or more users and display candidates and enabling one or more users to interface with a single AGUI display across multiple display candidates.

Abstract: Storage layer data obfuscation, including: determining a subset of a dataset to obfuscate in accordance with a security policy; generating, based at least in part on the security policy, an obfuscated snapshot of the dataset that is representative of the dataset with the subset of the dataset obfuscated; and sending, to a target computer system, the obfuscated snapshot from which a restored version of the dataset includes the subset of the dataset obfuscated.

Abstract: A system and method for an adaptive graphic user interface (AGUI) (501) that can identify the characteristics of one or more users and display candidates and dynamically select display content and generate an interface (502-506 . . . ) customized to one or more users and display candidates and dynamically arrange, modify, map and adapt an AGUI display to any object (350,730), device, clothing, equipment, furniture, appliance, room, building, vehicle, person, or other passive or active display surface, screen, space or other display candidate and embodiments of an AGUI apparatus (500) that can network, coordinate and/or operate with the AGUI platform (1302) to identify one or more users and display candidates and enabling one or more users to interface with a single AGUI display across multiple display candidates.

Abstract: A system and method for an adaptive graphic user interface (AGUI) (501) that can identify the characteristics of one or more users and display candidates and dynamically select display content and generate an interface (502-506 . . . ) customized to one or more users and display candidates and dynamically arrange, modify, map and adapt an AGUI display to any object (350,730), device, clothing, equipment, furniture, appliance, room, building, vehicle, person, or other passive or active display surface, screen, space or other display candidate and embodiments of an AGUI apparatus (500) that can network, coordinate and/or operate with the AGUI platform (1302) to identify one or more users and display candidates and enabling one or more users to interface with a single AGUI display across multiple display candidates.

Abstract: An apparatus and method for light and optical depth mapping, 3D imaging, modeling, networking, and interfacing on an autonomous, intelligent, wearable wireless wrist computing, display and control system for onboard and remote device and graphic user interface control. Embodiments of the invention enable augmentation of people, objects, devices and spaces into a virtual environment and augmentation of virtual objects and interfaces into the physical world through its wireless multimedia streaming and multi-interface display and projection systems.

Abstract: A gateway provides duplex-directional, multimedia ad hoc mesh networking, peer-to-peer direct communications, power optimization, dynamic configuration, and data management, while operating within various devices and network topologies. A multitasking virtual machine monitor for mobile networked devices, that is capable of functional expandability and portability to various operating environments, interoperability with a variety of operating systems, the Gateway Control System (GCS) performs functional capabilities in both a local and a networked topology using local and remote hardware and software. Software within the GCS is partitioned into sequentially, autonomous code, referred to herein as “modules,” each module being configured to communicate with hardware and other gateway modules. Collectively, all gateway modules are referred to herein as the gateway stack (GS). Each member of the GS can be turned on or off, downloaded from a remote site, and dynamically configured.