Abstract: When executing a neural network comprising a sequence of plural layers of neural network processing in which at least one of the layers of the sequence of plural layers of the neural network is followed by two or more branches of neural network processing, each branch comprising a different sequence of one or more layers of neural network processing, the branch or branches to use for the neural network processing following the layer of the neural network that is followed by the two or more branches of neural network processing is selected based on a property or properties of the output feature map from the layer that is followed by the two or more branches.

Abstract: A method comprising: obtaining pose data representative of a pose of a portable device during observation of an environment comprising an object; obtaining distance data representative of a distance between the object and a receiver during the observation of the environment, using at least one radio waveform reflected from the object and received by the receiver; and processing the pose data and the distance data to generate a topological model of the object.

Abstract: Systems, apparatuses, devices and methods for body pose tracking are provided that are simple, inexpensive, flexible, accurate and robust. One body pose tracking system includes a mobile device, such as a smartphone, and active or passive marker bands. Images and depth information captured by the smartphone may be analyzed using an Inverse Kinematic (IK) model, and, in certain cases, the IK model solution may be augmented by machine learning. Other body pose tracking systems include an augmented-reality/virtual-reality (AR/VR) head-mounted-display (HMD) and/or AR/VR glasses rather than a smartphone. An AR/VR HMD device may include a depth sensor and multiple environment-facing cameras.

Abstract: A neural network system executable on a processor. The neural network system, when executed on the processor, comprises a merged layer shareable between a first neural network and a second neural network. The merged layer is configured to receive input data from a prior layer of at least one of the first and second neural networks. The merged layer is configured to apply a superset of weights to the input data to generate intermediate feature data representative of at least one feature of the input data, the superset of weights being combined from a first set of weights associated with the first neural network and a second set of weights associated with the second neural network. The merged layer is also configured to output the intermediate feature data to at least one subsequent layer, the at least one subsequent layer serving the first and second neural networks.

Abstract: A method of operating a mobile device, the method comprising: identifying a first image parameter for an image to be displayed on a display of the mobile device; determining a distance between the display of the mobile device and a user of the mobile device; modifying the first image parameter dependent upon the distance between the display of the mobile device and the user of the mobile device; and displaying an image on the display using the modified first image parameter.

Abstract: An AR system includes a user interface, one or more sensors arranged to generate sensor data representing part of an environment in which a user of the AR system is located, and a memory. The memory is arranged to store object association data associating the user with one or more objects in the environment, and object location data indicating a respective location of each of the one or more objects. The AR system is arranged to determine a position of the user; determine an updated location of one of the one or more objects in dependence on the generated sensor data and the determined position of the user, update the stored object location data to indicate the determined updated location of said one of the one or more objects, and output information depending on the updated location of said one of the one or more objects via the user interface.

Abstract: An extended-reality system is described which determines extended-reality data to be obtained from the remote network-connected storage based on a location of the extended-reality system. The extended-reality system determines a communication method by which to obtain the extended-reality data, wherein the extended-reality data may be obtained by one or more requests to the remote network-connected storage or by one or more requests to a local device outside of the extended-reality system. A request is sent to at least one of the local device via a peer-to-peer network and the remote network-connected storage in dependence upon the determination by the extended-reality system.

Abstract: When providing augmented reality display to users in an environment, two or more electronic devices operable to analyse the environment for augmented reality display purposes that are near to each other share data and/or processing relating to the analysis of the environment for augmented reality display purposes, with each device then using the data it receives from the other device when providing an augmented reality display to a user.

Abstract: In a graphics processing system comprising a graphics processor, a main memory, and a memory management unit, when rendering a frame that represents a view of a scene comprising one or more objects using a ray tracing process and the ray tracing process requires a traversal of a ray tracing acceleration data structure indicative of the distribution of geometry for the scene being rendered to determine geometry for the scene that may be intersected by a ray, at least part of the traversal of the ray tracing acceleration data structure is performed by the memory management unit (MMU).

Abstract: There is provided a display apparatus to focus light for a user. The apparatus comprises a tuneable lens having controllable optical properties, an eye-tracker device to determine a position at which the user is looking, and circuitry to control the optical properties of the tuneable lens to bring an object at the depth of the position into focus for the user. A method of focusing light is also provided. The method comprises determining a position at which the user is looking and controlling optical properties of a tuneable lens to bring an object at the depth of the position into focus for the user.

Abstract: A method apparatus and computer readable medium for processing input data using a neural network comprising at least a first layer and a second layer. The method comprising the steps of applying a partitioning scheme to the input data, to partition the input data into a plurality of blocks, each block representing a portion of the input data. At the first layer of the neural network, the blocks of the input data are processed in a first order to generate intermediary data, wherein the intermediary data is partitioned into a plurality of intermediary blocks. At the second layer of the neural network, the intermediary blocks are processed in a second order, wherein the second order differs from the first order.

Abstract: There is provided a data processing apparatus for performing machine learning. The data processing apparatus includes convolution circuitry for convolving a plurality of neighbouring regions of input data using a kernel to produce convolution outputs. Max-pooling circuitry determines and selects the largest of the convolution outputs as a pooled output and prediction circuitry performs a size prediction of the convolution outputs based on the neighbouring regions, wherein the size prediction is performed prior to the max-pooling circuitry determining the largest of the convolution outputs and adjusts a behaviour of the convolution circuitry based on the size prediction.

Abstract: A system-on-chip comprises processing circuitry to process input data to generate output data, and power management circuitry to control power management policy for at least a portion of the system-on-chip. The power management circuitry controls the power management policy depending on metadata indicative of a property of the input data to be processed by the processing circuitry.

Abstract: A vehicle-assist system comprising one or more sensors to monitor an environment of a vehicle and an eye-tracking system, including an eye-tracking sensor, to determine a gaze characteristic of a driver of the vehicle. The vehicle-assist system is to detect a hazard, and determine a hazard location of the hazard, in the environment of the vehicle. Based on the hazard location and the gaze characteristic of the driver, the vehicle-assist system is to output an indication of the hazard to the driver.

Abstract: Circuitry comprises processing circuitry to access a hierarchy of at least two levels of cache memory storage; memory circuitry comprising plural storage elements, at least some of the storage elements being selectively operable as cache memory storage in respective different cache functions; and control circuitry to allocate storage elements of the memory circuitry for operation according to a given cache function.

Abstract: A method for optimizing machine learning processing is provided. The method comprising retrieving, neural network architecture information for a neural network, the neural network architecture information comprising layer information and kernel information for the neural network. The network architecture information is analyzed to identify convolutional layers in the neural network which have associated strided layers. A first kernel for a convolutional layer identified as having an associated strided layer, and a second kernel for the strided layer associated with the convolutional layer are retrieved. A composite kernel is then generated, based on the first and second kernel, that performs the functions of the first and second kernel. Finally, the composite kernel is stored for further use by a neural network.

Abstract: Herein described is a method of operating an accumulation process in a data processing apparatus. The accumulation process comprises a plurality of accumulations which output a respective plurality of accumulated values, each based on a stored value and a computed value generated by a data processing operation. The method comprises storing a first accumulated value, the first accumulated value being one of said plurality of accumulated values, into a first storage device comprising a plurality of single-bit storage elements; determining that a predetermined trigger has been satisfied with respect to the accumulation process; and in response to the determining, storing at least a portion of a second accumulated value, the second accumulated value being one of said plurality of accumulated values, into a second storage device.

Abstract: When a graphics processor is processing data for an application on a host processor, the graphics processor generates in advance of their being required for display by the application a plurality of frame sequences corresponding to a plurality of different possible “future states” for the application. The graphics processing system, when producing a frame in a sequence of frames corresponding to a given future state for the application, determines one or more region(s) of the frame that are to be produced at a first, higher quality, and producing the determined region(s) of the frame at a first, higher quality, whereas other regions of the frame are produced at a second, lower quality.

Abstract: An AR system includes one or more image sensors arranged to capture image data representing a scene located within a field of view of the one or more image sensors, a display arranged to enable a user of the AR system to observe a representation or view of the scene, and an augmentation engine. The augmentation engine is arranged to process the captured image data to determine one or more visual characteristics for the captured image data and to determine, in dependence on the determined one or more visual characteristics, one or more properties for an image element to be presented on the display. The augmentation engine is arranged to present the image element, with the determined one or more properties, on the display to overlay the representation or view of the scene.

Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to enhance capabilities of peer devices. In an implementation, at least one agent to: identify one or more learnable capabilities enabled by one or more parameters that are accessible via receipt of one or more message at the one or more communication devices from one or more other computing devices; and determine a utility of augmenting at least one of the one or more learning engines with at least one of the one or more learnable capabilities.