Abstract: A method, a blockchain system, an apparatus, a program, and a medium, for blockchain authority management. Receiving, by a first node, a node operation request for a second node, the first node being a node manager in the blockchain system; voting, by the first node, on the node operation request, sending a first voting request to another node manager, obtaining a voting result and a voting signature fed back by the another node manager, packaging the obtained voting result and voting signature into a first block, and broadcasting the first block to the blockchain system; verifying, by at least one blockchain node, the voting result and voting signature in the first block, and adding the first block into a local ledger if the voting result and voting signature pass verification; and responding to the node operation request if the voting result in the first block satisfies a first preset condition.

Abstract: Cache, cache management method, and electronic device.

Abstract: A functional safety display controller and a functional safety display control system are provided in the present disclosure. The functional safety display controller is connected to a central controller, a memory, and a display through communication lines, at least one internal module of the functional safety display controller is provided with a functional safety detection unit, and the functional safety detection unit is configured to detect random errors that occur in a corresponding module. The functional safety display controller, the central controller, the memory, and the display form the functional safety display control system, which can balance issues such as research and development costs, risk control, and system area overhead.

Abstract: Systems, methods, and other embodiments described herein relate to an interface for training a visuomotor policy to be device agnostic and controlling a robotic device using the visuomotor policy. In one embodiment, a method includes collecting sensor data about a robotic manipulator within an environment. The method includes pre-processing the sensor data to compensate for an observation latency of at least one sensor associated with the robotic manipulator. The method includes generating actions for the robotic manipulator to perform a task according to the sensor data and a visuomotor policy. The method includes controlling the robotic manipulator, including compensating for execution latency of the robotic manipulator in performing the actions.

Abstract: The embodiments of the disclosure disclose a method and a system for blockchain access authority control, an apparatus, a program and a medium. The system comprises a plurality of blockchain nodes. For each blockchain node, a corresponding distributed node is further deployed in a node apparatus where the blockchain node is located, and the distributed nodes form a distributed storage system. A first blockchain node receives an access request sent by a first client, determines a possession of a first authority to access the blockchain system by the first client according to role confirmation information, and then determines a distributed node where access content is located from the distributed storage system. After determining a possession of a second authority to access the distributed node where the access content is located by the first client according to authority authentication information, the access content is obtained and returned to the first client.

Abstract: Systems and methods for manipulating deformable objects using air are disclosed. In one embodiment, a system for manipulating a deformable object, the system includes a first robot arm having a first gripper, a second robot arm having a second gripper, a blower robot arm having an air pump, and one or more processors programmed to control the first robot arm and the second robot arm to grasp the deformable object using the first gripper and the second gripper, respectively, and to control the blower robot arm to perform a plurality of blowing actions onto the deformable object until an objective is satisfied.

Abstract: A transistor structure includes a semiconductor substrate; an NFET channel structure atop the substrate; a PFET channel structure atop the substrate; a first dielectric atop the PFET channel structure; a second dielectric atop the NFET channel structure; a shared internal metal gate atop the dielectrics; a shared ferroelectric layer atop the shared internal metal gate; and a shared external gate electrode atop the shared ferroelectric layer. The first and second dielectrics are doped with different metals that provide differing overall work functions for the PFET and the NFET. A method for making a transistor structure includes depositing a shared dielectric onto an NFET channel structure and a PFET channel structure, and converting the shared dielectric to a first high-k dielectric atop the PFET channel structure and a second high-k dielectric atop the NFET channel structure. The first high-k dielectric and the second high-k dielectric are doped with different metals.

Abstract: Technology disclosed herein includes a wearable data collection device for training robotic systems. In an implementation, a wearable data collection device includes a hand element configured to receive a user's hand, multiple finger elements extending from the hand element, and joints coupling the finger elements to the hand element. The finger elements are constrained to movements that match capabilities of a robotic counterpart device. Multiple sensors mounted on the device capture pressure, position, visual, proximity, and acoustic data during recording sessions. The device may integrate with position tracking technologies such as mobile devices or augmented reality headsets. Data collected through the wearable device serves as training input for a neural network that controls the robotic counterpart.

Abstract: Technology disclosed herein includes a wearable data collection device for training robotic systems. In an implementation, a wearable data collection device includes a hand element configured to receive a user's hand, multiple finger elements extending from the hand element, and joints coupling the finger elements to the hand element. The finger elements are constrained to movements that match capabilities of a robotic counterpart device. Multiple sensors mounted on the device capture pressure, position, visual, proximity, and acoustic data during recording sessions. The device may integrate with position tracking technologies such as mobile devices or augmented reality headsets. Data collected through the wearable device serves as training input for a neural network that controls the robotic counterpart.

Abstract: Technology disclosed herein includes a wearable data collection device for training robotic systems. In an implementation, a wearable data collection device includes a hand element configured to receive a user's hand, multiple finger elements extending from the hand element, and joints coupling the finger elements to the hand element. The finger elements are constrained to movements that match capabilities of a robotic counterpart device. Multiple sensors mounted on the device capture pressure, position, visual, proximity, and acoustic data during recording sessions. The device may integrate with position tracking technologies such as mobile devices or augmented reality headsets. Data collected through the wearable device serves as training input for a neural network that controls the robotic counterpart.

Abstract: Technology disclosed herein includes a wearable data collection device for training robotic systems. In an implementation, a wearable data collection device includes a hand element configured to receive a user's hand, multiple finger elements extending from the hand element, and joints coupling the finger elements to the hand element. The finger elements are constrained to movements that match capabilities of a robotic counterpart device. Multiple sensors mounted on the device capture pressure, position, visual, proximity, and acoustic data during recording sessions. The device may integrate with position tracking technologies such as mobile devices or augmented reality headsets. Data collected through the wearable device serves as training input for a neural network that controls the robotic counterpart.

Abstract: Technology disclosed herein includes a wearable data collection device for training robotic systems. In an implementation, a wearable data collection device includes a hand element configured to receive a user's hand, multiple finger elements extending from the hand element, and joints coupling the finger elements to the hand element. The finger elements are constrained to movements that match capabilities of a robotic counterpart device. Multiple sensors mounted on the device capture pressure, position, visual, proximity, and acoustic data during recording sessions. The device may integrate with position tracking technologies such as mobile devices or augmented reality headsets. Data collected through the wearable device serves as training input for a neural network that controls the robotic counterpart.

Abstract: A computer-implemented method for training a neural network for processing tabular data, comprises training a neural network to generate hidden layer connections and hidden layer weights for the tabular data, and training a skip layer to constrain the neural network. The skip layer governs an extent to which particular features of the tabular data participate in the neural network. The skip layer is based on a nonlinear per-feature embedding for each feature of the tabular data.

Abstract: A memory device comprises a physically and electrically connected logic die and a memory die. The logic die comprises a logic dielectric layer, with a plurality of logic openings; a logic device layer is disposed on the logic dielectric layer; and a plurality of logic devices, with logic device connections, disposed on/within the logic dielectric layer. The memory die comprises a memory dielectric layer with a plurality of memory openings; a memory device layer is disposed on the memory dielectric layer; and a plurality of memory devices, with memory device connections, disposed on/within the memory device layer. A backside to backside (B2B) connection interface is disposed between the logic dielectric layer and the memory dielectric layer. Connection paths passing through the B2B connection interface enables short back-to-back connections between logic device connections and the memory device connections.

Abstract: A semiconductor device is provided in which a memory chip stack is stacked vertically on, and hybrid bonded to, a process chip. In the semiconductor device, a hybrid bonding interface including dielectric-to-dielectric bonding and metal-to-metal bonding is present between the memory chip stack and the process chip.

Abstract: A functional safety display controller and a functional safety display control system are provided in the present disclosure. The functional safety display controller is connected to a central controller, a memory, and a display through communication lines, at least one internal module of the functional safety display controller is provided with a functional safety detection unit, and the functional safety detection unit is configured to detect random errors that occur in a corresponding module. The functional safety display controller, the central controller, the memory, and the display form the functional safety display control system, which can balance issues such as research and development costs, risk control, and system area overhead.

Abstract: A backbone node access method and a blockchain system are disclosed. In the backbone node access method, after receiving an access request of a backbone node in a second blockchain system, a first node of a first blockchain system determines a voting node and requests the voting node to vote on the access request; the voting node feeds back a voting result; after determining to approve the access request according to the voting result, the first node determines a second node and sends anchoring message to the second node; and the second node is anchored with the backbone node based on the anchoring message, so that the backbone node accesses to the first blockchain system, the second blockchain system becomes a slave chain system of the first blockchain system, and the first blockchain system becomes a master chain system of the second blockchain system.

Abstract: A method includes receiving observation data comprising sensor data associated with a robot while one or more humans are controlling the robot to perform a specified task, receiving control data comprising control commands input by the one or more humans while controlling the robot to perform the specified task, adding Gaussian noise to the control data to generate noisy control data, and training a neural network, based on the noisy control data to receive the observation data and first Gaussian noise, and output an action sequence, comprising a plurality of action steps, to be performed by the robot to perform the specified task.

Abstract: A computer-implemented method is provided for creating a photolithographic mask. The method includes, in a model building stage, obtaining lithography polygon coordinates from an input lithography target layout. The method further includes, in the model building stage, obtaining mask polygon coordinates from an input mask layout from a test mask. The method also includes, in the model building stage, obtaining correlated mask to lithography features from the lithography polygon coordinates and the mask polygon coordinates. The method additionally includes, in the model building stage, performing linear regression on the correlated mask to lithography features to obtain a machine learning model for predicting an output mask from an input lithography target design. The method further includes, in an inference stage, predicting a given output mask from a given input lithography target design using the machine learning model.

Abstract: Systems, methods, and other embodiments described herein relate to an interface for training a visuomotor policy to be device agnostic and controlling a robotic device using the visuomotor policy. In one embodiment, a method includes collecting sensor data about a robotic manipulator within an environment. The method includes pre-processing the sensor data to compensate for an observation latency of at least one sensor associated with the robotic manipulator. The method includes generating actions for the robotic manipulator to perform a task according to the sensor data and a visuomotor policy. The method includes controlling the robotic manipulator, including compensating for execution latency of the robotic manipulator in performing the actions.