Some implementations are directed to adapting a client application on a feature phone based on experiment parameters. Some of those implementations are directed to adapting an assistant client application, where the assistant client application interacts with remote assistant component(s) to provide automated assistant functionalities via the assistant client application of the feature phone. Some implementations are additionally or alternatively directed to determining whether an invocation, of an assistant client application on a feature phone, is a request for transcription of voice data received in conjunction with the invocation, or is instead a request for an assistant response that is responsive to the transcription of the voice data (e.g., includes assistant content that is based on and in addition to the transcription, and that optionally lacks the transcription itself).

Some implementations are directed to adapting a client application on a feature phone based on experiment parameters. Some of those implementations are directed to adapting an assistant client application, where the assistant client application interacts with remote assistant component(s) to provide automated assistant functionalities via the assistant client application of the feature phone. Some implementations are additionally or alternatively directed to determining whether an invocation, of an assistant client application on a feature phone, is a request for transcription of voice data received in conjunction with the invocation, or is instead a request for an assistant response that is responsive to the transcription of the voice data (e.g., includes assistant content that is based on and in addition to the transcription, and that optionally lacks the transcription itself).

Techniques herein processes type assignments for a generic class to generate a concrete class. In an embodiment, a computer analyzes a client class to detect a dependency on a generic class having type parameters. The client class contains a specialization context that specifies type assignments for the type parameters. Each type parameter is associated with particular type entries in the generic class that identify an erasure type to use in case the type parameter is erased. The computer generates instantiation metadata for the generic class including, for each type entry, performing the following. In response to determining that the specialization context specifies binding a particular type to the type parameter associated with the type entry, the computer generates an entry for the instantiation metadata that identifies the particular type. Otherwise, the computer generates an entry for the instantiation metadata that identifies an erasure type of the type entry.

Technologies for reliable software execution include a computing device having a memory that includes multiple ranks. The computing device trains the ranks of the memory and determines a consolidated memory score for each rank. Each consolidated memory score is indicative of a margin of the corresponding rank. The computing device identifies a higher-margin address range using the consolidated memory scores. The higher-margin memory address range is mapped to a higher-margin memory rank. The computing device loads high-priority software into the higher-margin memory address range. The high-priority software may include an operating system or a critical application. A pre-boot firmware environment may publish the consolidated memory scores to a higher-level software component, such as the operating system. The pre-boot firmware environment may map a predetermined address range to the higher-margin memory rank. A critical application may request to be loaded into a higher-margin address range. Other embodiments are described and claimed.

Method for defining a code to be executed by programmable control devices comprising: providing a programming language; providing a code written in that programming language; compiling such code in machine language; transferring said machine language code on a program memory for its execution by the control device, wherein said machine language code is divided into core code and application code, said application code being loaded into the program memory regardless of the core code, without performing a linking operation of the two codes before said transfer. A corresponding system is also disclosed.

A recurrent neural network including an input layer, a hidden layer, and an output layer, wherein the hidden layer includes hybrid memory cell units, each of the hybrid memory cell units including a first memory cells of a first type, the first memory cells being configured to remember a first cell state value fed back to each of gates to determine a degree to which each of the gates is open or closed, and configured to continue to update the first cell state value, and a second memory cells of a second type, each second memory cell of the second memory cells including a first time gate configured to control a second cell state value of the second memory cell based on phase signals of an oscillatory frequency, and a second time gate configured to control an output value of the second memory cell based on the phase signals, and each second memory cell of the second memory cells being configured to remember the second cell state value.

Disclosed are system and method for controlling execution of a computer program. An example method includes determining whether code instructions or data of interest are found in a portion of a page in an original virtual address space, when the code instructions or data are found in the portion of the page of a first type, tagging it as non-executable and tagging the portion of no interest as executable, when the code instructions or data are found in the portion of the second type, tagging it using an opcode and tagging the portion of no interest as executable, when the code instructions or data are found in the portion of the first type, duplicating the original virtual address space and tagging the portion of interest as executable and tagging the portion of no interest as non-executable and transferring execution of the computer program to a memory location other than the one in which a notification was received.

The disclosed embodiments provide a system that facilitates the execution of a software program. During operation, the system determines a structure of a software program and an execution context for the software program from a set of possible execution contexts for the software program, wherein the software program includes one or more object instances. Next, the system uses the structure and the execution context to identify a portion of an object instance from the one or more object instances that is determined to inefficiently use memory space in the software program. The system then provides a refactoring of the object instance that reduces use of the memory space in the object instance.

Systems and apparatus including consumer electronic devices, including Internet of Things (IoT) connectivity and a reconfigurable embedded rules engine, include: a code base that has been minimized to reduce a memory footprint of the code base in a memory device; and wherein the code base performs operations comprising effecting cross-platform network communications functionality using a computer communications network interface, providing access to the cross-platform network communications functionality through a communications application programming interface (API), triggering network communications, using the communications API, in accordance with encoded device-operation rules comprising at least one encoded communication triggering rule, allowing changes to the encoded device-operation rules through a rules updating API, and checking whether the changes to the encoded device-operation rules received through the rules updating API comply with at least one of the processing resource constraints associated with a hardware processor and a memory device.

The present application relates to a system hosting a monotonic counter and a method of operating the system. The system comprises a non-volatile memory (110) for holding a save counter value and a volatile memory (120) for maintaining a current counter value. The system (100) is configured during a startup phase to retrieve the saved counter value of the monotonic counter from the non-volatile memory (110); to detect whether a previous shutdown of the system (100) was an uncontrolled shutdown; and to adjust the retrieved counter value in accordance with a step size (130) provided at the system (100) in case an previous uncontrolled shutdown is detected.