Systems and methods for managing a database back end as a service are described. In some aspects, the described systems and methods provide for a cloud-based resource for servicing a request for data from an application to a remote database and/or a service. In some aspects, the described systems and methods provide for a cloud-based application client for requesting data from a remote database and/or a service.

A system is provided herein that can correlate service issues with system telemetry associated with the software session associated with those service issues. Using a statistical approach, the system can evaluate data across numerous software sessions to rank the importance of the reported service issues. To accomplish the ranking, the system can parse the reports of service issues on a periodic basis, can extract telemetry identifiers (IDs) from the logs, can query the telemetry, may compute the relative importance of detected issues (in the context of calls going on for that day), and then can report this impact hack to the service issue database.

Embodiments are disclosed for merging data structure definitions. The techniques include generating a first memory layout definition based on a first data structure definition that is written in a first programming language. The techniques further include generating a second memory layout definition based on a second data structure definition that is written in a second programming language. Additionally, the techniques include merging the first memory layout definition and the second memory layout definition into a merged memory layout definition. Further, the techniques include generating a merged data structure definition based on the merged memory layout definition.

The present disclosure relates to systems, methods, and non-transitory computer readable storage media for implementing a scalable, secure, efficient, and adaptable distributed digital ledger transaction network. Indeed, the disclosed systems can reduce storage and processing requirements, improve security of implementing computing devices and underlying digital assets, accommodate a wide variety of different digital programs (or “smart contracts”), and scale to accommodate billions of users and associated digital transactions. For example, the disclosed systems can utilize a host of features that improve storage, account/address management, digital transaction execution, consensus, and synchronization processes. The disclosed systems can also utilize a new programming language that improves efficiency and security of the distributed digital ledger transaction network.

The present disclosure provides a specification description program and a specification description method that allows a user to create processing contents of a plurality of processes in a simple manner when designing the plurality of processes to be executed in a plurality of devices. A specification description program causes a computer to execute a receiving process for receiving processing contents of a plurality of processes to be executed in a plurality of devices. The receiving process further provides a user with a unique representation method as a selectable function. The unique representation method indicates that processing contents are targeted for one or more devices of a same type among the plurality of devices.

The present disclosure provides to transparent and controllable human-AI interaction via chaining of machine-learned language models. In particular, although existing language models (e.g., so-called “large language models” (LLMs)) have demonstrated impressive potential on simple tasks, their breadth of scope, lack of transparency, and insufficient controllability can make them less effective when assisting humans on more complex tasks. In response, the present disclosure introduces the concept of chaining instantiations of machine-learned language models (e.g., LLMs) together, where the output of one instantiation becomes the input for the next, and so on, thus aggregating the gains per step.

An example computer implemented method for generating an artificial intelligence (AI) model from a self-creating script coded in a programming language includes receiving an objective for the AI model and obtaining at least first action code corresponding to a first action, where the first action is associated with an action objective similar to the objective. The method further includes generating at least a second action code based on one of the first action code and a specification of the programming language and comparing a first outcome of the first action code and a second outcome of the second action code. The method further includes inserting one of the first action code and the second action code into the self-creating script based on the comparing the first outcome of the first action code and the second outcome of the second action code and executing the self-creating script including the one of the first action code and the second action code to satisfy the objective.

The disclosure provides an access method, an access apparatus, an electronic device and a computer storage medium, and relates to a field of computer technologies, in particular to a field of artificial intelligence technologies such as chip and deep learning. The method includes: determining a computational graph for calling an access device based on operator representations in a target model; optimizing the computational graph based on information of the access device; and performing relevant running operations of the target model on the access device based on the computational graph and an interface for the access device to access to a model framework of the target model, the interface being determined based on kit data of the access device.

An application server may load a set of elements configured for use in an application. In some examples, a subset of the set of elements may include metadata enabling dynamic interactions between the subset of the set of elements. The application server may receive a selection of a source element and an event associated with the source element. In some examples, the event may include transmission of a data packet from the source element in response to a trigger at the source element, and the event and a payload of the data packet may be configured in accordance with the metadata associated with the source element. The application server may receive a selection of a target element and an input field. The application server may then store a dynamic interaction between the source element and the target element for the application.

A document to be stored on a network-based storage system is identified. The document includes one or more macros in a first programming language. An object referenced by a function defined by a macro of the one or more macros is identified. The function is converted into one or more sets of operations represented in a second programming language. Each set of operations corresponds to one of one or more candidate object types associated with the object. At least one of the one or more sets of operations is to be performed with respect to the object responsive to indication of a corresponding candidate object type for the object during execution of the macro. The document including the one or more sets of operations represented in the second programming language is stored on the network-based storage system.