Abstract: Systems and methods are disclosed for expanding the output modalities of a gameplay session. Gameplay input data, such as audio data, video data, haptics data, and Gameplay context data, can be processed using machine learning (ML) models to generate output state vectors, which can be used to drive state changes in remote devices, such as smarthome devices (e.g., smart lightbulbs, smart light switches, smart fans, smart thermostats, smart blinds, smart speakers, etc.). To generate the output state vectors, first gameplay features are extracted from the gameplay input data, then the gameplay features are processed by a state vector generation model to generate the state vectors. Each modality of gameplay input data can be processed by a corresponding feature extractor. Gameplay sessions can be evaluated to train the ML models.

Abstract: A method for plasma deposition of materials onto a 2-dimensional layer of a first substrate, the method comprising: depositing a protective layer directly onto the 2-dimensional layer in a pulsed plasma deposition process; and depositing a second layer onto the protective layer in a second plasma deposition process.

Abstract: Methods and systems are provided for verifying an input provided at a controller including detecting a finger gesture on a surface of the controller. Responsive to detecting the finger gesture, multi-modal data is collected from a plurality of sensors and components tracking the finger gesture. The multi-modal data is used to generate an ensemble model using machine learning algorithm. The ensemble model is trained in accordance to training rules defined for different finger gestures. An output is identified from the ensemble model for the finger gesture. The output is interpreted to define an input for an interactive application selected for interaction.

Abstract: Application context may be interpolated between application state updates from structured and unstructured application state data. Irrelevant unimodal modules may be deactivated based on the structured application state data while relevant unimodal modules remain active. Unimodal features are generated from the unstructured application using the relevant modules. A neural module selection network module may be trained with a machine learning algorithm. Each unimodal modules may generate unimodal feature vectors from unstructured application data. A context state update module may determine which unimodal modules are irrelevant from structured application state data and deactivate the irrelevant modules but not the relevant ones. A multimodal neural network may take the active unimodal feature vectors and predict structured context data and send it to a uniform data system.

Abstract: A system for generating gameplay context information for a game may include a game screen classification module trained to classify contextually relevant data from gameplay data, one or more game object recognition modules trained to detect game icons from gameplay data, and a multimodal context generation neural network module trained to generate structured gameplay context information from the contextually relevant data and icons within the gameplay data. The multimodal context generation neural network module at least partially generates structured gameplay context information. The modules may include neural networks trained by suitable machine learning algorithms using suitable masked data and labeled data.

Abstract: System, process and device configurations are provided for analyzing and modifying a game environment. A method can include generating at least one game scenario for an electronic game including control settings for an audio configuration, a video configuration and a gameplay configuration. The method may include outputting the at least one game scenario using the control settings, and detecting user interest for the at least one game scenario. User interest for the at least one game scenario may be detected using a kernel function including a kernel element for each of a visual style, an audio style and a gameplay style. User profile data may be updated for the at least one user based on detected user interest for the at least one game scenario. Output of a game state may be controlled for the electronic game using the user profile.

Abstract: A method for managing gameplay of a video game is provided, including: executing a session of a video game by a cloud gaming resource; streaming video generated by the session over a network to a client device associated to a player of the video game, to enable gameplay of the session by the player; detecting a loss of network connectivity between the client device and the session; responsive to detecting the loss of network connectivity, then initiating transmission of updates regarding the session, via an alternative communication channel, to a secondary device associated to the player.

Abstract: Methods and systems are provided for verifying an input provided at a controller including detecting a finger gesture on a surface of the controller. Responsive to detecting the finger gesture, multi-modal data is collected from a plurality of sensors and components tracking the finger gesture. The multi-modal data is used to generate an ensemble model using machine learning algorithm. The ensemble model is trained in accordance to training rules defined for different finger gestures. An output is identified from the ensemble model for the finger gesture. The output is interpreted to define an input for an interactive application selected for interaction.

Abstract: A network provides for encoding and decoding messages. An encoder neural network (NN) generates a tag description based on an input message. A compute module generates a distorted signature based on the tag description and a noise model. A decoder NN generates an output message based on the distorted signature. A controller compares of the input message and the output message. If an error is detected in the output message, the controller causes the encoder NN to be updated based on the error.

Abstract: Video and audio from a computer simulation are processed by a machine learning engine to identify candidate segments of the simulation for use in a video summary of the simulation. Text input is then used to reinforce whether a candidate segment should be included in the video summary.

Abstract: Video and audio from a computer simulation are processed by a machine learning engine to identify candidate segments of the simulation for use in a video summary of the simulation. Text input is then used to reinforce whether a candidate segment should be included in the video summary. Metadata can be added to the summary showing game summary information.

Abstract: Systems and methods for migrating a plurality of virtual machines (VMs) from a private cluster to a public cloud include identifying the plurality of VMs currently residing in the private cluster to be migrated to the public cloud. A communication graph indicative of communications involving the plurality of VMs is determined. A migration sequence for the plurality of VMs based on the communication graph is generated. The plurality of VMs is migrated from the private cluster to the public cloud according to the migration sequence.

Abstract: Systems and methods for creating and using a hybrid system include determining, by a capacity allocation system associated with a virtual computing system, capacity of a reserve portion and capacity of an allocation portion of a first site based upon a probability of failure associated with a plurality of second sites. The systems and methods also include allocating, by the capacity allocation system, the capacity of the allocation portion among the plurality of second sites for operating a portion of the plurality of second sites from the first site, determining, by the capacity allocation system, that a number of failures at the plurality of second sites exceeds a first pre-determined threshold, and dynamically adjusting, by the capacity allocation system, the capacity of the reserve portion and the capacity of the allocation portion of the first site based upon the number of the failures.

Abstract: Systems and methods for creating and using a hybrid system include determining, by a capacity allocation system associated with a virtual computing system, capacity of a reserve portion and capacity of an allocation portion of a first site based upon a probability of failure associated with a plurality of second sites. The systems and methods also include allocating, by the capacity allocation system, the capacity of the allocation portion among the plurality of second sites for operating a portion of the plurality of second sites from the first site, determining, by the capacity allocation system, that a number of failures at the plurality of second sites exceeds a first pre-determined threshold, and dynamically adjusting, by the capacity allocation system, the capacity of the reserve portion and the capacity of the allocation portion of the first site based upon the number of the failures.

Abstract: Systems and methods for creating and using a hybrid system include determining, by a capacity allocation system associated with a virtual computing system, capacity of a reserve portion and capacity of an allocation portion of a first site based upon a probability of failure associated with a plurality of second sites. The systems and methods also include allocating, by the capacity allocation system, the capacity of the allocation portion among the plurality of second sites for operating a portion of the plurality of second sites from the first site, determining, by the capacity allocation system, that a number of failures at the plurality of second sites exceeds a first pre-determined threshold, and dynamically adjusting, by the capacity allocation system, the capacity of the reserve portion and the capacity of the allocation portion of the first site based upon the number of the failures.

Abstract: Systems and methods for creating and using a hybrid system include determining, by a capacity allocation system associated with a virtual computing system, capacity of a reserve portion and capacity of an allocation portion of a first site based upon a probability of failure associated with a plurality of second sites. The systems and methods also include allocating, by the capacity allocation system, the capacity of the allocation portion among the plurality of second sites for operating a portion of the plurality of second sites from the first site, determining, by the capacity allocation system, that a number of failures at the plurality of second sites exceeds a first pre-determined threshold, and dynamically adjusting, by the capacity allocation system, the capacity of the reserve portion and the capacity of the allocation portion of the first site based upon the number of the failures.

Abstract: Systems and methods for migrating a plurality of virtual machines (VMs) from a private cluster to a public cloud include identifying the plurality of VMs currently residing in the private cluster to be migrated to the public cloud. A communication graph indicative of communications involving the plurality of VMs is determined. A migration sequence for the plurality of VMs based on the communication graph is generated. The plurality of VMs is migrated from the private cluster to the public cloud according to the migration sequence.

Abstract: Systems and methods are provided for generating a mesh assembly. A specification of a system having first and second objects is received. The specification includes, for each of the first and second objects, geometric data for the object and mesh data comprising settings for creating a mesh representation of the object. The first object is associated with a first mesh, and the second object is associated with a second mesh. The associating includes, for each of the first and second objects, determining whether a mesh with geometric data and mesh data corresponding to that of the object has been previously generated. If the mesh has been previously generated, the object is associated with the mesh, and if the mesh has not been previously generated, the object is meshed to generate a new mesh that is associated with the object. A mesh assembly including the first and second meshes is generated.

Abstract: In a system for facilitating mesh generation corresponding to a volumetric, prismatic object, generalized polyhedrons representing at least a portion of a layer of the volumetric object are transformed into a set of convex polyhedrons based on, at least in part, the prismatic properties of the volumetric object. The convex polyhedrons corresponding to a layer are decomposed into a set of tetrahedrons by accounting for an intersecting and/or overlapping edge of a polyhedron in an adjacent layer, so that the set of tetrahedrons automatically, i.e., without having to enforce any continuity requirements after tetrahedron generation, forms a mesh of that is continuous with tetrahedrons corresponding to the adjacent layer.

Abstract: A method for Internet delivery in a delivery network established at network locations, the delivery network comprising a plurality of content servers for serving resources. The servers include a plurality of subsets, each subset being located at one of a plurality of Internet data centers. For each Internet Protocol (IP) address block from which requests for content resources are expected to be received, the method generates a candidate list of data centers to be used to service the requests. For the IP address block, the method selects at least one of the data centers from the candidate list. The selected Internet data center for the IP address block is written into a network map. In response to a DNS query, the map is used to identify one of the Internet data centers from the candidate list to be used to service a request for a content resource.