Abstract:
Aspects of the present disclosure provide an apparatus that can execute an artificial intelligence (AI) model with IO changing. For example, the apparatus can include a first secured processor, a secured application embedded in the first secured processor and associated with an AI model, a secured memory configured to store an AI executable binary associated with the AI model, a second secured processor configured to execute the AI executable binary, a sub-system configured to trigger IO changing and trigger the second secured processor to execute the AI executable binary, IO meta data stored in the secured memory, an IO verifier configured to verify IO changing by determining the IO meta data, and an IO pre-fire module configured to patch the IO changing to the AI executable binary running on the second secured processor when the IO verifier determines that the IO changing matches the IO meta data.
Abstract:
A method for accessing a network in an electronic system and associated portable device are provided. The portable device includes; a transceiver, supporting a plurality of predetermined communication protocols; and a processor, configured to connect the portable device to a connectivity service device in an electronic system via the transceiver when the portable device enters a coverage region of the connectivity service device. The connectivity service device retrieves service information from a plurality of electronic devices that are connected to the connectivity service device, to build a service list. The processor retrieves the service list from the connectivity service device, and determines a service from the service list to be used for communicating with the plurality of the electronic devices.
Abstract:
A dynamic data distribution method in a private network and an associated electronic device are provided. The private network includes: a first pairing connection between a first electronic device, a second electronic device, and a second pairing connection between the first electronic device and a third electronic device. The method includes the steps of: receiving sensor data from the second electronic device by the first electronic device; notifying the second electronic device to build a third pairing connection with the third electronic device according to a determination result between the first electronic device and the third electronic device; and terminating the first pairing connection and retrieving the sensor data from the second electronic device through the third electronic device by the first electronic device when the third pairing connection has been built.
Abstract:
An electronic device and associated method is provided. The electronic device includes: a first sensor; and a processing unit, coupled to the first sensor, wherein the electronic device enters a remote sensor mode when the electronic device is connected to a remote electronic device having a second sensor for generating sensor data, wherein the processing unit executes an application which utilizes the sensor data from the remote electronic device in the remote sensor mode.
Abstract:
A portable electronic device including a touch sensor and a processing unit is provided. The touch sensor is disposed on or under a display, and uses a power level to generate first touch data for a touch detected thereon when the display is in a sleep state. The processing unit configures the touch sensor to increase the power level to generate second touch data for the touch when determining that the touch corresponds to a predetermined gesture with a first similarity probability greater than a first threshold according to the first touch data, and wakes the display from the sleep state when determining that the touch corresponds to the predetermined gesture with a second similarity probability greater than a second threshold according to the second touch data, wherein the second threshold is greater than the first threshold.
Abstract:
Aspects of the present disclosure provide an apparatus, which can include a first secured processor and secured applications embedded in the first secured processor. Each of the secured applications can be associated with an artificial intelligence (AI) model. The apparatus can further include first secured memories each configured to store an AI executable binary associated with a corresponding one of the AI models, a second secured processor configured to execute the AI executable binaries stored in the first secured memories, a sub-system, and an AI session manager configured to receive from the sub-system an AI session that identifies one of the AI models, and prepare and store an AI executable binary associated with the AI model to one of the first secured memories that corresponds to the AI executable binary. The sub-system can trigger the second secured processor to execute the AI executable binary stored in the first secured memory.
Abstract:
Aspects of the disclosure provide an apparatus for executing a program that involves a plurality of operators. For example, the apparatus can include an executor and an analyzer. The executor can be configured to execute the program with at least a first one of the operators loaded on a second memory from a first memory that stores the operators and to generate a signal based on a progress of the execution of the program with the first operator. The analyzer can be coupled to the executor, the first memory and the second memory, and configured to load at least a second one of the operators of the program next to the first operator stored in the first memory to the second memory before the executor finishes execution of the program with the first operator based on the signal from the executor and an executing scheme stored in the second memory.
Abstract:
Aspects of the disclosure provide a method and an apparatus for executing a program, e.g., a neural network (NN) inference. For example, the apparatus can include an executor and a dynamic loading agent. The executor can be coupled to a second memory, and be configured to execute a portion of the NN inference loaded on the second memory from a first memory that stores the NN inference, and to generate a signal based on a progress of the execution of the NN inference. The dynamic loading agent can be coupled to the executor, the first memory and the second memory, and be configured to load a next portion of the NN inference stored in the first memory to the second memory and to manage power supplied to the first memory based on the signal from the executor and an inference executing scheme stored in the second memory.
Abstract:
A sensor hub coupled to one or more sensors and an application processor of a communications apparatus includes a sensing module and a micro-processor. The sensing module receives raw data from the sensors. The raw data is generated by the sensors when sensing one or more events. The micro-processor constructs an adaptive model according to a plurality of parameters and identifies user activity according to the raw data based on the adaptive model. The sensor hub is an always-on sub-system for assisting the application processor to identify user activity according to the raw data. The micro-processor further receives updated parameters and updates the adaptive model according to the updated parameters.
Abstract:
A power-saving method and associated electronic device are provided. The electronic device is connected with a first external electronic device and a second external electronic device, and a first sensor and a second sensor are deployed on the first external electronic device and the second electronic device, respectively. The electronic device includes: a third sensor, and a processor, wherein the first, second, and third sensors have the same type. The processor gathers information from the first pedometer sensor, the second pedometer sensor, the first external electronic device, and the second external electronic device, and determines whether to turn off at least one of the first, second, and third pedometer sensors according to the information gathered.