Disclosed herein are system, method, and computer program product embodiments for automatic non-code test suite generation of an application programming language (API) specification. An embodiment operates by receiving a specification of an API, wherein the API comprises a plurality of endpoints. The embodiment generates, using a parser, an abstraction model corresponding to the specification of the API, wherein the abstraction model comprises a plurality of entities corresponding to the plurality of endpoints. The embodiment identifies, based on the abstraction model, an operation that is applicable to an entity of the plurality of entities. The embodiment then generates a functional test based on a use case corresponding to the entity and the operation.
Methods and systems for distributed denial of service (DDoS) protection management are described. The system may aggregate, from a web application firewall (WAF) bridge service that interfaces with one or more WAF services, one or more DDoS event records associated with one or more DDoS events. The system may analyze the one or more DDoS event records via an analysis of one or more headers and one or more payloads of the one or more DDoS event records, logging information, and a threat intelligence feed. The system may generate a security configuration that indicates one or more parameters of the one or more WAF services to be set. The system may validate the security configuration and may transmit the security configuration to the one or more WAF services based at least in part on the validation.
A computing platform is configurable to cause initiating a communication session with a user, the user having a user account associated with a workflow data object implemented in an on-demand application hosted by the computing platform, the workflow data object being configured to represent a plurality of operations associated with the user and an organization, and further associated with a vaccination status of the user. The computing platform is configurable to cause identifying a verified status indicator used by at least one of the plurality of operations represented in the workflow data object, the verified status indicator comprising a verified credential associated with at least one of the plurality of operations. The computing platform is configurable to cause identifying a transfer operation associated with the verified status indicator and identifying a target entity based on the user account, and implementing the identified transfer operation based on the identified target entity.
A computer-implemented method of decision optimization in a multi-record environment is disclosed. The method includes receiving a request to make a recommendation in relation to a data record and defining the recommendation in terms of an optimization problem including decision objectives including objective contribution functions and constraints including constraint contribution functions. The method also includes extracting input data from a data source, the input data including individual instances of data and attributes describing the individual instances of data. The method also includes identifying a context of the optimization problem based upon the individual instances of data. The context relates to a behavior of the input data given the decision objectives and the constraints. The method further includes solving the optimization problem by satisfying the decision objectives and the constraints, in the context, to generate a solution and providing the recommendation based on the solution.
In view of the need for a conversational recommender system (CRS) in guiding purchasing processes of complex items, embodiments described herein provide a CRS system that creates a realistic purchase scenario and agent evaluation for fulfilling the recommendation objective. Specifically, the CRS system utilizes existing buying guides as a knowledge source for the recommendation model.
Embodiments described herein provide a system for training a neural network model using a teacher-student framework. The system includes a communication interface configured to communicate with a teacher model; a memory storing a student model and a plurality of processor-executable instructions; and a processor executing the processor-executable instructions to perform operations. The operations include: generating, by the student model, a first task output in response to a task input; obtaining, from an evaluation environment, a feedback relating to an accuracy of the first task output; obtaining a refinement output generated by the teacher model based on an input of the first task output and the feedback; and training the student model based on a training input of the first task output and the feedback and a training label of the refinement output.
A computer system receives, from a programmatic interface of a client device via one or more external API calls, a query that specifies a data source and one or more data fields of the data source. The computer system, in accordance with receiving the query, generates a query specification according to the one or more data fields of the data source, wherein the query specification is an extended version of the API calls. The computer system transmits the query specification to a data service and causes the data service to execute one or more database queries to retrieve data against a database to retrieve query results from the data source, according to the query specification. The computer system receives the query results from the data service, configures the query results to obtain configured data, and transmits the configured data to the client device for display in the programmatic interface.
A non-transitory computer readable medium having computer instructions stored therein that when executed by a computer system cause the computer system to perform operations including receiving a first user input defining a dialog session comprising one or more steps of a natural language conversation flow, receiving a second user input defining a positive outcome of the dialog session, receiving, via a chat interface, a natural language input, initiating the dialog session in response to an association between the natural language input and the dialog session, receiving, via the chat interface, a subsequent natural language input, and updating a data entry associated with the custom metric in an outcome log in response the subsequent natural language input being indicative of the positive outcome of the dialog session.
A database with virtual partitioning. A computer system used to implement the database receives a request for a database operation to be performed on data stored in a portion of the database, where the data has a group of logical partitions (e.g., tenants of a multi-tenant database), and where the portion of the database is not further physically partitioned. The computer system identifies a virtual partitioning scheme for the database operation, the virtual partitioning scheme defining sub-groups of the group of logical partitions. The computer system then performs the database operation for the sub-groups defined by the virtual partitioning scheme. Multiple virtual partitioning schemes can be active at the same time, and virtual partitioning schemes can be created dynamically in some instances.
A system may receive, via a cloud-based platform supporting a plurality of tenants, one or more access events from a user of a host platform associated with a tenant, the one or more access events comprising one or more keystroke events at the host platform and one or more commands inputted by the user at the host platform, wherein the one or more access events are captured by a continuous authentication agent associated with the host platform. The system may identify fraudulent access events based at least in part on executing a machine learning model to perform a pattern matching between previously authenticated browsing behavior of the user and the one or more access events at the host platform. The system may generate a challenge question for reauthenticating the user of the host platform based at least in part on identifying the at least one fraudulent access event.
Techniques are disclosed pertaining to performing upgrades by upgrade controllers. A node upgrade controller determines to upgrade a first set of nodes, of a plurality of nodes, on which executes a first set of pods that facilitate access to an instance of a particular component. The node upgrade controller obtains a lock on the plurality of nodes to prevent a pod upgrade controller from upgrading a second set of pods that execute on a second set of the plurality of nodes and facilitate access to another instance of the particular component. The unavailability of the first and second sets of pods causes a requisite number of instances of the particular component to be unavailable. The node upgrade controller upgrades the first set of nodes and releases the lock to allow the pod upgrade controller to obtain a lock on the plurality of nodes.
Embodiments described herein provide a framework that integrates a retriever model and the LLM to feed retrieved passages to an LLM to generate an answer conditioned on the retrieved passages in response to a query. For example, in one embodiment, a single-round approach is implemented, which involves directly transmitting the retrieved passages to the LLM. For another example, a multi-round methodology is implemented, which involves initially presenting the retrieved passages to the Language Model, collecting its responses, and then adjusting our interaction with the Language Model based on this acquired feedback.
G06N 3/006 - Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
A client device receives one or more inputs for generating a data visualization according to a data source. The device determines one or more requirements for generating the data visualization. The device sends a request to a network gateway that is communicatively connected to the client device and a plurality of data servers, and receives, from the network gateway, capabilities of each data server. The device determines, according to the received capabilities, that a first data server of the plurality of data servers includes a first set of capabilities that satisfies the requirements for generating the data visualization. The device sends, via the network gateway, one or more queries to the first data server and receives, from the first data server, one or more data sets from the data source. The device generates the data visualization according to the retrieved data sets and displays the data visualization.
Media, methods, and systems are provided for screen sharing. A user may initiate a video recording. A recording preview interface may be displayed for the user to preview the video recording before beginning the recording. The recording preview interface may comprise a live video preview of the user and of a window or application being shared. When the user selects a window or application for previewing that may cause an infinity mirror effect to occur, a screenshot of the window or application may be generated. The screenshot may be rendered over the live video preview of the window or application to obscure the infinity mirror effect. When the user initiates recording, the screenshot may be removed to expose the live video. The screenshot may be cached and retrieved if the user navigates away and then returns to the preview of the window or application causing the infinity mirror effect.
A method, system and computer program product for aggregate query optimization. A dataset with plurality of values divided into dimensions and measurements is received. Pre-calculated values obtained by aggregates of measurements' values respective of plurality of combinations of dimensions' values are calculated and stored for one or more aggregate measurements of interest. Responsive to an input received of a first set of one or more dimensions and a second set of one or more aggregate measurements of interest, an aggregate result value of a respective member of the second set is calculated and outputted by retrieval of the pre-calculated value therefor respective of members of the first set.
Disclosed herein are system, method, and device embodiments for creating an improved mobile interface of a messaging application. The mobile interface displays unread conversations as a stack of tiles. With the top tile displayed, a user may efficiently mark the conversation as read or unread by swiping left or right. The interface then moves to the next tile in the stack. This allows a user to quickly triage unread messages while in the mobile application. The mobile interface ranks unread messages in an intuitive fashion in determining the ordering of the tiles. The interface may generate these rankings using a trained artificial intelligence based on a user's past behaviors and signals in unread messages. Messages received during the user's review of the stack of tiles may be dynamically inserted in a thoughtful manner. A summary may be displayed that indicates the number of messages, an estimated time to complete the review of the unread messages, and a summary of the unread messages that may be generated by sending a generative pre-trained transformer prompt to a trained neural network.
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
A method of data processing is described. The method includes receiving, at a server host, a request to access a web domain associated with a tenant of a multi-tenant cloud platform; retrieving, from a database, a tenant private key and a certificate associated with the tenant, where the tenant private key is encrypted with a secret key derived from a key agreement public key associated with the tenant and a private key provisioned to a key protection component of the server host; providing, to the key protection component, the encrypted tenant private key and the key agreement public key; receiving, from the key protection component, an API response including a signature associated with the tenant private key; and providing, to a client device associated with the request to access the web domain of the tenant, the certificate and the signature, where the certificate is used to verify the signature.
Methods, systems, apparatuses, devices, and computer program products are described. A system may input a first audio stream (e.g., audio recording) and a corresponding text sting into a machine learning model. The first audio stream and the text string may correspond to a first identity (e.g., person). Based on an output of the machine learning model, the system may generate a second audio stream associated with a second identity and mimics the first audio steam. For example, the second audio stream may be a generated recording of the second identity speaking the first text string. In addition, the system may generate a video depicting the second identity speaking the first text string (e.g., the second audio stream) based on combining the second audio stream with some image or previous video of the second identity. For example, the system may generate the video based on generating a head motion sequence.
G10L 21/10 - Transforming into visible information
G10L 13/08 - Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
20.
SYSTEMS AND METHODS FOR A CONVERSATIONAL FRAMEWORK OF PROGRAM SYNTHESIS
Embodiments described herein provide a program synthesis framework that generates code programs through a multi-turn conversation between a user and a system. Specifically, the description to solve a target problem is factorized into multiple steps, each of which includes a description in natural language (prompt) to be input into the generation model as a user utterance. The model in turn synthesizes functionally correct subprograms following the current user utterance and considering descriptions and synthesized subprograms at previous steps. The subprograms generated at the multiple steps are then combined to form an output of program in response to the target problem.
Methods, systems, and devices for data processing are described. A server host may receive a login request that includes a clear text password for an account associated with a tenant of a multi-tenant cloud platform. The server host may retrieve an encrypted payload associated with the account. The encrypted payload may include a hash value of a user-configured password for the account and an indication of a hashing algorithm used to transform the user-configured password into the hash value. The server host may obtain a wrapped symmetric key provisioned by a symmetric key distribution service. The server host may transmit a request that includes the encrypted payload, the clear text password, and the wrapped symmetric key. The server host may receive a response that indicates whether a hash value of the clear text password from the login request corresponds to the hash value of the user-configured password.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
Methods, systems, and devices for data processing are described. A server host may receive a request to access a web domain associated with a tenant of a multi-tenant cloud platform. The server host may retrieve a digital certificate and an encrypted private key associated with the tenant, where the digital certificate includes a public key associated with the tenant. The server host may obtain a symmetric key that is wrapped using an asymmetric public key associated with the server host. The wrapped symmetric key may be provisioned by a symmetric key distribution service. The server host may transmit a request that includes the encrypted private key and the wrapped symmetric key. The server host may receive a response that includes a cryptographic signature associated with the private key of the tenant. The server host may provide the digital certificate and the cryptographic signature to a client device associated with the request.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
23.
HARDWARE-BACKED PASSWORD SECURITY FOR CLOUD SYSTEMS
A method of data processing is described. The method includes receiving, at a server host, a login request that includes a clear text password for an account. The method further includes retrieving, from a database, a payload stored in association with the account. The payload may indicate a hash value of a user configured password for the account, a hashing algorithm used for generation of the hash value, an initialization vector, and a key agreement public key associated with the account. The payload may be encrypted using a secret key derived from the key agreement public key and a private key provisioned to a key protection component of the server host. The method further includes transmitting a request that includes the payload and the clear text password. The method further includes receiving a response that indicates whether the clear text password corresponds to the user configured password.
Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
25.
SYSTEMS AND METHODS FOR TRAINING A NEURAL NETWORK MODEL USING KNOWLEDGE FROM PRE-TRAINED LARGE LANGUAGE MODELS
Embodiments described herein provide a training framework for generative NLP models that operate on previously learnt knowledge from pretrained large language models. Specifically, to train an NLP model to generate a response to a user utterance (e.g., “resolve login issue”), document embeddings of support IT documents encoded by a pretrained LLM are fed to an NLP decoder together with a training dialogue (e.g., a dialogue between the chat agent on how to “resolve login issue”). The NLP decoder can thus be trained by a causal language modeling loss computed based on the predicted next token and the ground-truth token from the training dialogue.
Embodiments described herein provide a training framework for generative NLP models. Specifically, the training input, e.g., in the form of a sequence of tokens representing a user-agent dialogue, may be randomly masked for a few spans, which can be one or more tokens, one or more words, one or more sentences, or one or more paragraphs. These masked spans are replaced with their embeddings generated from pre-trained large language models are then used for training the NLP model.
An application server or other processing entity may receive, via a cloud-based platform, user input that may include at least one request for data. The application server may classify the user input into a first of a plurality of deterministic-stochastic spectrum classifications based on the user input and a probability of mapping the at least one request for data to at least one data location. The application server may retrieve the data from the at least one data location and based on the first deterministic-stochastic spectrum classification. The application server may transmit, based on the first deterministic-stochastic spectrum classification and the user input, an input to a large language model. The application server may present a response to the user input, where the response is based on a combination of an output of the large language model and the data retrieved from the at least one data location.
Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.
G06F 16/9535 - Search customisation based on user profiles and personalisation
G06F 16/958 - Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
G06Q 50/00 - Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
H04L 51/216 - Handling conversation history, e.g. grouping of messages in sessions or threads
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
30.
DATA RETENTION IN GROUP-BASED COMMUNICATION PLATFORM
Techniques for modifying a period of time that data, associated with a characteristic, transmitted via a communication platform is retained are described. A data retention rule can include a first period of time for retaining data transmitted via the communication platform, in association with an organization. The first user can additionally establish a specific data retention rule associated with data associated with a particular characteristic. The specific data retention rule can include an instruction to store communications including the particular characteristic for a second time period that is different from the first time period associated with the data retention rule. The communication platform can receive data from a second user computing device associated with the second user of the organization. Based on a determination that the data is associated with the characteristic, the communication platform can store the data according to the data retention rule specified for such data.
Disclosed herein are system, method, and device embodiments for programmatically generating and deploying an integration application based on a natural language request without requiring any coding by a user. The application generator infers the sources, targets, connectors, operations, entities, and data mappings needed to build the requested integration application. An exposed web service or API may receive natural language input, determine the meaning of the request, and generates and deploys the resulting integration application without requiring any coding by a user.
Embodiments described herein provide A method for training a neural network based model. The methods include receiving a training dataset with a plurality of training samples, and those samples are encoded into representations in feature space. A positive sample is determined from the raining dataset based on a relationship between the given query and the positive sample in feature space. For a given query, a positive sample from the training dataset is selected based on a relationship between the given query and the positive sample in a feature space. One or more negative samples from the training dataset that are within a reconfigurable distance to the positive sample in the feature space are selected, and a loss is computed based on the positive sample and the one or more negative samples. The neural network is trained based on the loss.
In some embodiments, a method selects a set of fields for a record in a database system. A set of prompt templates is retrieved that is associated with the set of fields. A prompt template comprises text and a variable. The method searches information that is associated with the record to determine context information and inserts the context information into the prompt templates to generate a set of prompts. The set of prompts is input into a generative model to output a generated result. The generative model is trained to output text based on prompts. The method outputs enrichment data for the record on an interface, wherein the enrichment data is based on the text of the generated result.
A method and apparatus for collecting and supporting querying of multi-dimensional data pertaining to usage of software and/or hardware to service tenant requests in a multi-tenant cloud computing system where the multi-dimensional data is initially captured on a per request basis and recorded in objects of a first type that store data pertaining to a specific request, specific tenant, specific host and specific time. The objects of the first type are combined by time windows to form objects of a second type. The objects of a second type are stored in another system as separate text files. Responsive to a query for multi-dimensional data for a specific tenant that spans an interval of multiple time windows, the objects of the second type for the specific tenant and time interval are combined across all hosts to generate a query result, and the query result is returned.
Database systems and methods are provided for initiating an action at a database system by an instance of a native application at a client device coupled to the database system over a network. One method involves a service associated with a field service application at a client device monitoring a location of the client device to determine the location satisfies update criteria including a field of a data record associated with a service appointment when the location is within a threshold distance of a value for the field of the data record corresponding to an address for the service appointment. The service automatically provides an indication to automatically update a status field of the data record associated with the service appointment at the database system in accordance with a configuration associated with the instance of the field service application when the location of the client device satisfies the update criteria.
A computing device receives a first user interaction with a graphical user interface (GUI) of the computing device. In response to the user interaction, the device sends, to a server system, a request for data corresponding to a first component of the GUI. The device initializes the first component concurrently with the sending. The device receives, from the server system, the data corresponding to the first component and corresponding metadata for the first component. The device generates the first component based on the corresponding metadata and at least a first subset of the received data and displays the first component in a first portion of the GUI. Concurrently with the generating and displaying, the device generates a second component of the GUI based on at least a second subset of the received data, and displays the second component simultaneously with the first component.
Database systems and methods are provided for augmenting a received conversational user input to provide an augmented conversational user input to a chatbot or other artificial intelligence (AI) system configurable to generate a personalized conversational response to the received conversational user input using the augmented conversational user input. One or more personal models or other user data associated with the user providing the received conversational user input are utilized to identify a relevant subset of data associated with the user for generating the augmented conversational user input, where the personalized conversational response is influenced by the relevant subset of data associated with the user.
Database systems and methods are provided for personalized automation agents. One method involves determining an action to be performed on behalf of a user, identifying a relevant subset of data in a database of the database system associated with the user based on the action, generating a personalized input prompt for an execution plan for the action using the using that subset of data, providing the personalized input prompt to a service configurable to generate a personalized conversational response, receiving the personalized conversational response comprising textual content indicative of a sequence of steps of the execution plan from the service, automatically executing the execution plan in accordance with the sequence using the service to perform the action with respect to a data record in the database, and automatically providing a response to the client device indicative of the action with respect to the data record.
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
Embodiments described herein provide systems and methods for training neural network based language models using human feedback. An existing (or generated) summary of a document is provided, and that summary may be used to generate a number of other summaries. A human annotator may reject the summary if there is any factuality issue with the summary. Summaries which are agreed to have no factuality problems are used as baseline summaries. Small atomic edits are made to the baseline summaries (e.g., replacing a single word or phrase) to create a group of summaries. Human annotators label each of these summaries as factual or not. The annotated summaries are used to train a summarization model and/or a factual detector model.
Apparatus and method for dynamic and persistent data sharing between cloud services. To address limitations in existing systems, resource provisioning and application deployment pipelines are configured with calls to share data using a configuration service. In some implementations, the configuration service includes an API, which is called by one or more stages of the resource provisioning pipeline to write configuration data in key-value pairs (e.g., data related to resource provisioning). One or more stages of the application deployment pipeline are configured with calls to access the configuration data. The stages then use the configuration data for application deployment. The configuration service manages the key-value store using versioning, repeatability, and immutability, to ensures that a configuration generated by any pipeline execution can be automatically re-used by another pipeline, at execution time. Thus, the configuration service is a dynamic, single source of truth for sharing pipeline configuration data.
Embodiments described herein provide a method of image generation. The method includes a fixed diffusion model, and a trainable diffusion model. The fixed diffusion model may be pretrained on a large training corpus. The trainable diffusion model may be used to control the image generation of the fixed diffusion model by modifying internal representations of the fixed diffusion model. A task instruction may be provided in addition to a text prompt, and the task instruction may guide the trainable diffusion model together with the visual conditions. The visual conditions may be adapted according to the task instruction. During training, a fixed number of task instructions may be used. At inference, unseen task instructions may be used by combining convolutional kernels of the visual condition adapter.
Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.
H04N 13/279 - Image signal generators from 3D object models, e.g. computer-generated stereoscopic image signals the virtual viewpoint locations being selected by the viewers or determined by tracking
43.
SYSTEMS AND METHODS FOR RECONSTRUCTING A THREE-DIMENSIONAL OBJECT FROM AN IMAGE
Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.
A computing device displays, in a user interface, data field icons corresponding to a plurality of data fields. Each of the data fields is associated with a respective object in an object model. In response to receiving (i) user selection of a first data field icon corresponding to a first data field, and (ii) placement of the first data field icon in a shelf region of the user interface, where the first data field is associated with a first object of the object model, the computing device generates a first data visualization and updates a visual characteristic of a subset of the data field icons from a first visual characteristic to a second visual characteristic. Each data field icon in the subset is associated with a second object of the object model. The data field icons in the subset are user-selectable independently of the first or second visual characteristic.
A computing device receives user input specifying a first dimension data field and a second dimension data field. The device constructs a dimension subquery according to characteristics of the first dimension data field, the second dimension data field, a first object to which the first dimension data field belongs, and/or a second object to which the second dimension data field belongs, including determining a join type for combining (i) first data rows that include data values of the first dimension data field and (ii) second data rows that include data values of the second dimension data field. The device constructs the dimension subquery according to the determined join type, and executes the dimension subquery to retrieve first tuples. The device constructs measure subqueries and executes the measure subqueries to retrieve second tuples. The device forms extended tuples, and generates and displays the data visualization according to the extended tuples.
Database systems and methods are provided for assigning structural metadata to records and creating automations using the structural metadata. One method of assigning structural metadata involves determining a candidate group of semantically similar conversations based on unassigned conversations, determining a clustering performance metric associated with the candidate group based on a relationship between the candidate group and a plurality of existing groups of semantically similar conversations, and when the clustering performance metric is greater than a threshold, automatically assigning one or more unassigned conversations to the candidate group based on the representative utterances associated therewith and automatically updating one or more associated records at a database system to include metadata identifying the candidate group.
A system receives an access token generated by a user performing authentication via an authentication device, for example, a smart card. The system obtains a personalized virtual machine assigned to the user. The system exchanges the access token for a temporary certificate having an expiry time. The system provides the temporary certificate that includes verifiable user identity to a personalized virtual machine. The system provides the user with access to the personalized virtual machine. The system allows the user to present verifiable user identity and connect to any of a plurality of systems without requiring the user to authenticate again using the authentication device. After the expiry time of the temporary certificate is exceeded, the system denies subsequent requests from the user to connect to any of the plurality of systems.
A computing device displays a first object icon representing a first object of a first data source and a second object icon, representing a second object of the first data source. The first object icon is connected to the second object icon via a first connector representing a relationship between the first object and the second object. In response to receiving a first user input to add a third object, the computing device displays a third object icon representing the third object. In response to receiving a second user input on the third object icon, in accordance with a determination that the second object and the third object include at least one common data field, the computing device displays a second connector, connecting the third object icon to the second object icon.
G06F 16/901 - Indexing; Data structures therefor; Storage structures
G06F 3/04812 - Interaction techniques based on cursor appearance or behaviour, e.g. being affected by the presence of displayed objects
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
49.
Automatic structure selection and content fill within a group-based communication system
Media, methods, and systems for automatically selecting and prefilling template structures within a group-based communication system. A template structure is automatically selected based on a received user input. A prompt including one or more keywords from the user input is submitted to a content fill model. The content fill model returns a response with content output used to automatically populate one or more content fields within the template structure.
Techniques are disclosed that relate to truncating a subrange of records from a database table. A computer system receives a request to truncate the subrange of records. The request specifies a conditional expression that is usable to identify the subrange from other subranges of records of the database table. Before truncating the subrange of records, the computer system determines whether the subrange of records can be truncated from the database table with a single-record subrange truncate operation, regardless of a size of the subrange of records, based on whether the conditional expression satisfies a set of preconditions. Based on determining that the conditional expression satisfies those preconditions, the computer system performs the single-record subrange truncate operation that includes generating a truncate record that causes the subrange of records to be truncated from the database table.
Embodiments described herein provide a method of generating a multi-modal task output to a text instruction relating to inputs of multiple different modalities (e.g., text, audio, video, 3D). The method comprises receiving, via a data interface, a first input of a first modality, a second input of a second modality and the text instruction relating to the first and the second inputs; encoding, by a first multimodal encoder adapted for the first modality, the first input of the first modality into a first encoded representation conditioned on the text instruction; encoding, by a second multimodal encoder adapted for the second modality, the second input of the second modality into a second encoded representation conditioned on the text instruction; and generating, by a neural network based language model, the multi-modal task output based on an input combining the first encoded representation, the second encoded representation, and the text instruction.
Embodiments described herein provide a query-focused summarization model that employs a single or dual encoder model. A two-step approach may be adopted that first extracts parts of the source document and then synthesizes the extracted segments into a final summary. In another embodiment, an end-to-end approach may be adopted that splits the source document into overlapping segments, and then concatenates encodings into a single embedding sequence for the decoder to output a summary.
Systems, devices, and techniques are disclosed for a horizontally scalable system for managing container clusters. A monolithic management system may perform a first task on a first level of a cloud computing server system. The monolithic management system may perform a second task on a second level of a cloud computing server system. The monolithic management system may invoke instances of a container manager on a level of the cloud computing server system below the second level. The instances of the container manager may update container clusters of the cloud computing server system. The instances of the container manager may be associated with container clusters and the instances of the container manager update their associated container clusters.
A computer-implemented method for monitoring and control of a network traffic in a cloud server environment is disclosed. The method includes receiving network traffic at a cloud service account that includes a corresponding local security enforcement module configured to enforce security policies for data processed by the cloud service account and forwarding a part of the network traffic from the cloud service account to a centralized security monitoring hub that includes a hardware-based security component. The method also includes detecting, by the hardware-based security component, offending traffic that includes traffic from an unwanted source or with malicious content. The method further includes sending a notification of the offending traffic to the localized security enforcement module, by the centralized security monitoring hub, and responsive to the notification, implementing a security enforcement strategy in the cloud service account based on the security policy, by the corresponding localized security enforcement module.
A computing platform configurable to allow users to graphically represent relationships between database records may be provided to a plurality of organizations. A request to generate a customizable visualization for graphically representing relationships between a root database record and child database records in a customizable format may be processed. Graphical representations of the root database record and the child database records may be caused to be displayed in accordance with the customizable format.
G06F 16/26 - Visual data mining; Browsing structured data
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
56.
CONTENT-OBLIVIOUS FRAUDULENT EMAIL DETECTION SYSTEM
A system supporting one or more machine learning models may receive, via a cloud-based platform that supports a multi-tenant system, metadata associated with a set of electronic communication messages for a tenant of the multi-tenant system. The system may normalize the metadata by extracting fields of the metadata into a format readable by the machine learning model to identify a set of fraudulent users associated with the set of electronic messages. The system may utilize the machine learning model to identify the set of fraudulent users based on executing a set of detection models and performing pattern matching between a set of previously authenticated user activity logs and a set of newly generated user activity logs in the metadata. Upon detection of the set of fraudulent users, the system may generate and transmit a report indicating the set of fraudulent users and the respective electronic message corresponding to the respective fraudulent user.
A computing device receives a natural language input specifying a first search term and a second search term, directed to a dataset. The device (i) executes, for the first search term, first queries against a search index to retrieve a first set of labeled trend events; and (ii) executes for the second search term, second queries against the search index to retrieve a second set of labeled trend events. Each labeled trend event has a respective chart identifier. The device constructs sequences of labeled trend events based on the retrieved sets of labeled trend events, assigns each sequence into groups according to the respective chart identifier, and ranks the groups. The device retrieves data corresponding to a subset of line charts having the respective chart identifiers of the ranked groups, generates the subset of line charts, and displays one or more line charts of the subset.
A computing device receives user interaction with a portion of a data visualization that is displayed on the computing device. In response to receiving the user interaction, the computing device generates a first prompt that includes (i) a first parameter specifying a visualization type of the data visualization, (ii) a second parameter specifying a data array corresponding to data marks of the data visualization, and (iii) a third parameter specifying a title of the data visualization. The computing device inputs the first prompt into a large language model (LLM) and obtains, from the LLM, a text narrative for the portion of the data visualization. The device generates a second prompt in accordance with the text narrative, inputs the second prompt into the LLM, and obtains from the LLM a title for the text narrative. The device generates a self-contained story based on the text narrative and the title.
A computing device receives a natural language input specifying search terms directed to a dataset. The device parses the input into tokens and executes queries against a search index to retrieve a plurality of labeled trend events. Each labeled trend event has a respective chart identifier. The device determines a respective composite score for each labeled trend event and individually assigns each labeled trend event to a respective group. For each group, the device sorts the respective labeled trend events within the respective group according to respective composite scores, determines a respective final score for each group, and ranks the groups according to one or more determined final scores. The device retrieves data corresponding to a first subset of line charts having the respective chart identifiers of the ranked groups, generates the first subset of line charts, and displays one or more line charts of the first subset with annotation.
System, method and interface for interpreting natural language comparisons during visual analysis are provided. The system includes obtaining a natural language utterance that includes a comparison query and a dataset of attributes and values relevant to interpreting the comparison query. The system also includes interpreting the natural language utterance based on the dataset using multi-step chain-of-thought reasoning prompting to generate a response to the comparison query. The system also includes generating a visualization based on the response and a text summary describing the multi-step chain-of-thought reasoning for the comparison query.
Methods, apparatuses, and computer-program products are disclosed. A method may include activating, in a processing entity, a connection agent and a manifest, the manifest including a data signature and an endpoint type that are associated with the processing entity. The method may include generating, based on the data signature, the endpoint type, or both, one or more load balanced dynamic endpoints configured for access, by the connection agent and via one or more application programming interfaces, to a repository including access configurations for the processing entity. The method may include retrieving, via the one or more load balanced dynamic endpoints and from the repository, one or more first access configurations of the plurality of access configurations and the one or more first access configurations may be associated with the processing entity.
Online meeting software typically generates a flow of data. A server system is configured to receive the flow of data, which may include metadata. The data may include metadata of online meetings. Different types of metadata are generated by online meetings. Such different types of metadata are provided in different patterns. Different types of metadata are provided throughout the online meeting session or at various points of the session and are provided to various different elements of the server system. The various different metadata received are then parsed and certain specific metadata elements are identified to match the different metadata streams.
Techniques are disclosed relating to storing location information about storage nodes in cookies. A cloud-based service may send location requests to an orchestration service that instantiated storage nodes included in a storage cluster of the cloud-based service. The cloud-based service may receive location information that identifies in which computer zone that a given storage node is located. The cloud-based service may store the location information in cookies at a metadata store that is shared among the storage nodes. The cloud-based service may receive, from a client node, a search request to identify ones of the storage nodes that store particular data. The cloud-based service may return a set of cookies corresponding to identified storage nodes. The set of cookies may enable the client node to determine whether there is a storage node that stores the particular data and is within the same computer zone as the client node.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
System and methods are presented for configuring and managing metadata switches and platform licenses in a distributed system. Using metadata switches, a platform license can be developed for a software product without the need for an engineer to develop the platform license by hand. A software application depot can be used to configure metadata switches that provide configuration information for a particular aspect of the software product and, when associated to a platform license that utilizes metadata switches, generate an accessible platform license for use by tenant organizations.
Systems and methods are provided for parsing, at a server, a design file including code for a user interface, where the code is readable by the server into a tree representation having nodes, the nodes represent design elements of the user interface and includes one or more design properties, a unique identifier, and references to child elements. The server traverses the tree representation and comparing the design elements of the tree representation to a set of factors to determine when the design elements and meet a criteria to be a subcomponent for one or more components of the code of the design file. The server adds the design elements to a list of subcomponent candidates that meet at least one of the set of factors to be a subcomponent. The server generates a tree structure for the one or more components using the list of subcomponent candidates.
Techniques for locating information previously shared via a virtual space of a communication platform are disclosed herein. For example, the communication platform may receive, at the virtual space associated with a first user and a second user, a message containing one or more keywords. Based at least in part on receiving an indication from one of the first user or the second user, the communication platform may determine that the message is a searchable message. In some examples, the communication platform may then receive, from a third user of the communication platform unassociated with the virtual space, a request to access one or more messages associated with a keyword of one or more keywords. Based at least in part on receiving the request, the communication platform may cause presentation, to the third user, of at least a portion of the searchable message.
Disclosed are examples of systems, apparatus, methods and computer program products for sharing and publishing files. In one aspect, the database system can maintain a user database, a file database and a library. The database system can receive a first request initiated by a first user to share a first file with one or more second users and, responsive to the first request, enable a second set of one or more permissions for each of the second users. The database system also can receive a second request initiated by the first user to publish the first file to the library and, responsive to the second request, publish the first file to the library. The database system additionally can restrict access to the published file based on permissions associated with the library.
Techniques are disclosed that relate to manipulating a chain of database objects without locking the chain. A computer system may maintain a chain that orders a set of database objects stored in a cache of the computer system. The computer system may receive a set of requests to perform database transactions. Based on those received set of requests, the computer system may determine to perform a plurality of chain operations that involve modifying the chain. The computer system may perform two or more of the plurality of chain operations at least partially in parallel using a set of atomic operations without acquiring a lock on the chain.
A multi-tenant system receives a request to build a software artifact for deploying on one or more target datacenter entities of the datacenter configured on the could platform. A software artifact comprises executable instructions associated with a service configured for execution on one or more cloud platforms. The system generates a release configuration that includes reusable release components and is used as a template by the release orchestration system to orchestrate release of the software artifact. The release configuration may specify one or more stagger groups, or a group of target datacenter entities that can be rolled-out in parallel.
A plurality of permissions associated with the on-demand computing services environment may be identified. Each of the permissions may identify a respective one or more actions permitted to be performed within the on-demand computing services environment. Each of the permissions may be granted to a respective one or more user accounts within the on-demand computing services environment. A degree of overlap between a first group of the user accounts granted a first one of the permissions and a second group of the user accounts granted a second one of the permissions may be determined. When the degree of overlap exceeds a designated threshold, a designated permission set that includes the first permission and the second permission may be created.
Implementations(s) for simulated software features are described. Responsive to a request for accessing a first web page, first code for the first web page is caused to be retrieved from a first web application. Responsive to the first code, the first web page is caused to be displayed with an access to a simulation of a feature that may be used in the first web application. Responsive to a user's selection of the access, the first web page is caused to be updated to include a first user interface (UI) component that identifies a second web page; responsive to the updated first web page, second code for the second web page is caused to be retrieved from a second web application; and responsive to the second code, the second web page is caused to be displayed inside the first UI component to allow for the simulation.
A method provides visual analysis of datasets. A system receives a natural language search query that is directed to data repositories including data sources and data visualizations. The system parses search tokens to determine if the natural language search query contains analytic intents. The system also determines if the search tokens match fields in one or more data sources, using a semantic search. When (i) the search tokens match fields in the one or more data sources and (ii) the natural language search query contains analytic intents, the system generates and displays visualization responses. When (i) the search tokens do not match fields in the data sources or (ii) the natural language search query does not contain the analytic intents, the system displays pre-authored content from the data visualizations.
Disclosed are methods, apparatus, systems, and computer readable storage media for interacting with one or more data objects in an online social network. A user interface includes a publisher with a custom action. The custom action is defined in accordance with custom action instructions provided by a first entity via an application programming interface (API). Such custom action instructions may declaratively or programmatically define the data object, the interaction to be performed with the data object, and other attributes associated with the custom action. A user may request to interact with the data object via selection of the custom action by a second entity. Information may be submitted through the publisher to interact with the data object to update a database system associated with the data object. A feed item may be presented for inclusion in the information feed based on the update.
G06F 40/143 - Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 40/106 - Display of layout of documents; Previewing
An application server may receive an input document including a set of input text fields and an input key phrase querying a value for a key-value pair that corresponds to one or more of the set of input text fields. The application server may extract, using an optical character recognition model, a set of character strings and a set of two-dimensional locations of the set of character strings on a layout of the input document. After extraction, the application server may input the extracted set of character strings and the set of two-dimensional locations into a machine learned model that is trained to compute a probability that a character string corresponds to the value for the key-value pair. The application server may then identify the value for the key-value pair corresponding to the input key phrase and may out the identified value.
A text interaction record including interaction text from one or more messages between a client machine and a service provider is received at a database system. A search vector including a text embedding representing the interaction text in a multi-dimensional vector space may be determined based on the interaction text via a processor at the database system. A reference interaction record including reference interaction text may be retrieved from the database system based on the search vector. The reference interaction record may include a reference vector representing the reference interaction text in the multi-dimensional vector space. Recommended reply text is determined based on the interaction text and the reference interaction text by a large language model configured to generate the recommended reply text in response to a prompt that includes one or more natural language instructions.
Embodiments are directed to pre-training a transformer model using more parameters for sophisticated patterns (PSP++). The transformer model is divided into a held-out model and a main model. A forward pass and a backward pass are performed on the held-out model, where the forward pass determines self-attention hidden states of the held-out model and the backward pass determines loss of the held-out model. A forward pass on the main model is performed to determine a self-attention hidden states of the main model. The self-attention hidden states of the main model are concatenated with the self-attention hidden states of the held-out model. A backward pass is performed on the main model to determine a loss of the main model. The parameters of the held-out model are updated to reflect the loss of the held-out model and parameters of the main model are updated to reflect the loss of the main model.
Method, apparatus and computer program product for generating a channel calendar in a group-based communication system are described herein. The apparatus is configured to at least generate a channel calendar identifier associated with a group-based communication channel in the group-based communication system, receive a calendar sharing request associated with the channel calendar identifier from a client device, retrieve the calendar object and calendar object metadata set based on the channel calendar identifier, and cause rendering of the calendar object for display via a user interface of the client device.
Methods, systems, and storage media are described for providing access to private resources such as in a Virtual Private Cloud (VPC) or in a database which is behind a Virtual Private Network (VPN). The solution involves configuring access to the privately owned resource, then using an integration platform to solve design operations or execute the full integration against the private resources. Ephemeral (short-term) or long-term connectivity can be provided.
Embodiments described herein provide a method of training a language model by tuning a prompt. The method comprises masking tokens of first and second conversational texts which have the same semantic meaning but in different languages (e.g., a translation). The masked texts are input to a language model with a prepended soft prompt. The language model generates respective predicted outputs. A loss objective is computed including a masked language model loss. The prompt is updated based on the computed loss objective via backpropagation while keeping the language model frozen.
Techniques are disclosed relating to restarting a database node. A database node may allocate memory segments that include a restart segment for storing data records. The database node may spawn processes to read a log and replay log records of the log to update the restart segment to store data records. The database node may determine to perform a restart operation to transition from a first mode to a second mode. Performing the restart operation may include ceasing reading the log at a stop position and storing, based on the stop position, database state information that enables the processes to resume reading the log from the stop position. The database node may further deallocate the memory segments except for the restart segment and terminate the processes. After performing the restart operation, the database node may spawn the processes, which may resume reading the log based on the database state information.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/22 - Indexing; Data structures therefor; Storage structures
A method and system for defining feature variable configurations in a system defined by a codebase has been developed. The codebase is executed over a set of test cases to test the software feature behaviors of a software feature. Feature variable configurations including feature variables generated by the test cases are logged. Associations between the feature variables and individual software feature behaviors are identified based on the logged feature variable configurations. Impact scores for the feature variables associated with individual software feature behaviors are calculated based on an occurrence of the associations between the feature variables and individual software feature behaviors. Deterministic feature variables are identified for individual software feature behaviors based on the calculated impact scores. At least one common feature variable is operable to enable access to the software feature in the system is identified from the deterministic features variables associated with the individual of software feature behaviors.
Techniques are disclosed relating to index metadata that is usable for accessing multi-level data structures. A computer system may operate a database, including maintaining a set of records having a set of corresponding keys. The computer system may create multi-level data structures that facilitate key range lookups against those records. A given multi-level data structure may store key information indicative of a subset of the corresponding keys. The computer system may create separate index metadata that is usable for accessing the multi-level data structures. The index metadata may specify indications of key information that is stored in the multi-level data structures and locations of the multi-level data structures. The computer system may perform a key range lookup that includes using the index metadata to determine a particular set of the multi-level data structures whose key information corresponds to a key range of the key range lookup.
Techniques for displaying tasks and/or virtual spaces to a user within a group-based communication platform are discussed herein. In some examples, a user may use a first device to start a first session on a communication platform. As the user may transition from the first user device to a second device, the communication platform may determine that the user has changed devices based on determining that the first session has ended and/or the user having requested to start a second session using a second device. Upon receiving the request and/or based on the first session ending, the communication platform may identify or otherwise predict a task and/or virtual space that the user may want to access upon starting the second session on the second device. The communication platform may cause the task and/or virtual space to be displayed via a user interface of the second device.
A method of training a neural network based three-dimensional (3D) encoder is provided. A first plurality of samples of a training dataset are generated using a first 3D model. An image generator with multi-view rendering is used to generate a plurality of two-dimensional (2D) images having different viewpoints of the first 3D model. A first language model is used to generate a plurality of texts corresponding to the plurality of 2D images respectively. A first text for a first image is generated by using one or more text descriptions generated by the first language model. A point cloud is generated by randomly sampling points in the 3D model. The first plurality of samples are generated using the plurality of 2D images, the corresponding plurality of texts, and the point cloud. The neural network based 3D encoder is trained using the training dataset including the first plurality of samples.
In some embodiments, a method determines a first functional domain that includes a group of security policies that have been copied from a second functional domain. Network flow data is queried to determine network traffic that is associated with a security policy in the group of security policies in the first functional domain. The method analyzes utilization of the security policy based on the network traffic. Based on the analyzing, a recommendation is generated to change the security policy in the first functional domain.
An extensible platform-as-a-service (PaaS) system is used during the software development lifecycle (SDLC) processes of an application. The system facilitates the process of getting security approval for the application. The system allows developers to use software bundles including software modules that are pre-approved. The system allows a developer to customize one or more software modules of the software bundle if necessary. The system monitors the development of the application to check if the developer customizes any software module to use a configuration that is not pre-approved. The system automatically generates a report noting the customization to the software module and requests the security team to review the modified configuration for security approval.
G06F 11/36 - Preventing errors by testing or debugging of software
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
87.
PARALLELISM WITH TASK DEPENDENCIES IN A CURATED EXPERIENCE
A method in a computing environment for application start up includes: generating a directed acyclic graph (DAG) for tasks that are performed during application start-up; performing topological sorting of the tasks based on the DAG to define an order for the tasks; allocating a tenant-specific priority queue; loading the tasks in the tenant-specific priority queue in the order determined by the topological sorting; allocating a plurality of computing threads to executing the tasks; executing the tasks using the plurality of computing threads that were allocated, wherein a plurality of the tasks are executed in parallel, and the tasks are assigned to the computing threads in an order based on the order in which the task are loaded in the tenant-specific priority queue; preparing a start page for use in accessing the application; and causing the start page to be displayed on a user access device for accessing the application.
Techniques are disclosed relating to upgrade groups. A node of a computer system may access metadata assigned to the node during deployment of the node. The node may be one of a plurality of nodes associated with a service that is implemented by the computer system. The node may perform an operation on the metadata to derive a group identifier for the node and the group identifier may indicate the node's membership in one of a set of groups of nodes managed by the service. The node may then store the group identifier in a location accessible to the service.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
89.
CONTROLLED UPDATES OF CONTAINERS IN A DISTRIBUTED APPLICATION DEPLOYMENT ENVIRONMENT
System and methods are described for implementing controlled updates of containers in a distributed application deployment environment. In one implementation, a method comprises: receiving a request to update a target container of a plurality of containers within a deployed computing unit; identifying an updated configuration object to be applied to the target container based on the request; receiving or computing a health indicator representative of performance of the deployed computing unit or other containers to which the updated configuration object has been applied; and assigning the updated configuration object to the target container based on the health indicator.
A method for data processing is described. The method includes receiving an indication of a reference string from a cloud client of a content generation service. The method further includes generating multiple candidate strings associated with the reference string based on using a machine learning model to calculate similarity metrics between the reference string and the multiple candidate strings, where the machine learning model is trained using a dataset of annotated strings. The method further includes selecting a quantity of the candidate strings based on filtering the multiple candidate strings according to the similarity metrics. The method further includes causing the quantity of candidate strings to be displayed at the cloud client. The method further includes receiving feedback associated with the quantity of candidate strings and a selection of at least one candidate string displayed at the cloud client.
Embodiments described herein provide a method of generating an image. the method comprises receiving, via a data interface, a natural language prompt, obtaining a noised image vector, and generating a denoised image vector by a first forward pass of a plurality of iterations of a denoising diffusion model with the noised image vector as an input and conditioned on the natural language prompt. The method further includes calculating a gradient of a loss function based on the denoised image vector with respect to the noised image vector, and updating the noised image vector based on the gradient. A final image is generated using a final forward pass of the denoising diffusion model with the updated noised image vector as an input and conditioned on the natural language prompt.
Embodiments described herein provide a feedback based instructional image editing framework that employs a diffusion process to follow user instruction for image editing. A diffusion model is fine-tuned using a reward model, which may be trained via human annotation. The training of the reward model may be done by having the image editing model output a number of images, which a human annotator ranks based on their alignment with the original image and a given instruction.
Embodiments provide a generative AI creation framework to a customized generative AI stack using a foundational model (such as GPT) based on user-defined prompts, a natural language description of the task to be accomplished, and domain adaptation. In one embodiment, organization-specific knowledge may be injected into either the prompt and/or the foundational model. In this way, the customized generative AI stack thus supports a full spectrum of domain-adaptive prompts to enable a full spectrum of personalized and adaptive AI chat applications.
Systems, devices, and techniques are disclosed for provisioning and secure access control for storage on public servers. Data may be received from a tenant service identifying both the tenant service and a security certificate. A data storage container may be generated on a public server. A security role that is associated with the tenant service and includes permissions for accessing data in the data storage container may be generated on the public server. A request to access the data storage container may be received from the tenant service, including an identification of the tenant service and the security certificate. Credentials and a request to assume the security role may be sent to an identity provider. A temporary security token for accessing the data storage container with the permissions of the security role may be received from the public server. The temporary security token may be sent to the tenant service.
Embodiments provide a generative AI creation framework to a customized generative AI stack using a foundational model (such as GPT) based on user-defined prompts, a natural language description of the task to be accomplished, and domain adaptation. In one embodiment, organization-specific knowledge may be injected into either the prompt and/or the foundational model. In this way, the customized generative AI stack thus supports a full spectrum of domain-adaptive prompts to enable a full spectrum of personalized and adaptive AI chat applications.
A method and system for rendering a stack trace visualization display has been developed. A first stack trace associated with execution of an application during a time period is received from a central processing unit profiler. A first stack trace visualization display is rendered including a plurality of stack frames stacked in accordance with an order of ancestry based on the first stack trace. Rendering at least one stack frame involves rendering at a first location of the first stack trace visualization display, a stack frame rectangle for the at least one stack frame in accordance with the order of ancestry and rendering at a second location of the first stack trace visualization display, stack frame specific text for the at least one stack frame. The second location overlays the first location. Rendering of the stack frame rectangle is independent of the rendering of the stack frame specific text.
A request to perform an action related to a smart contract recorded on a public trust ledger external to the database system may be received via a communication interface at a database system. The request may authenticate a designated database system account. A determination may be made as to whether the designated database system account is authorized to perform the action by accessing definition information for a public trust ledger synthetic party identifying a plurality of database system accounts authorized to perform one or more actions related to the smart contract. The database system may communicate with a token exchange to perform the action by executing the smart contract when it is determined that the designated database system account is authorized to perform the action.
G06Q 20/06 - Private payment circuits, e.g. involving electronic currency used only among participants of a common payment scheme
H04L 9/00 - Arrangements for secret or secure communications; Network security protocols
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
98.
BEHAVIOR-BASED DETECTION OF AUTOMATED SCANNER EVENTS
Methods, systems, apparatuses, devices, and computer program products are described. An application server or another device may receive a set of input data associated with an activity between an actor and an electronic communication message (e.g., a marketing email). From the input data, the application server may identify a set of features associated with the activity (an open rate, a click rate, etc.) and a set of source network addresses of respective, known automated scanners. The application server may input the features and source network addresses into a positive-and-unlabeled (PU) learning model, which may output a classification result that indicates a probability that the activity is associated with an automated scanner.
Techniques are disclosed pertaining to migrating a database between different storage clusters. A computer system identifies a current state of the database that is managed by a database application that enables a client application to access data of the database stored at a first storage cluster. The computer system copies first particular data of the database that is associated with the current state from the first storage cluster to a second storage cluster. After the copying, the computer system transitions the database application into a read-only mode in which it processes read but not write traffic. The computer system copies, from the first storage cluster to the second storage cluster, second particular data of the database that was generated by the database application during the copying of the first particular data. The computer system may also instantiate another instance of the database application in association with the second storage cluster.
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
100.
AUTOMATICALLY IDENTIFYING AND RIGHT SIZING INSTANCES
A system is disclosed. The system includes a resource monitor to monitor a resource utilization of a set of resources of one or more instances, the resource utilization corresponding to a first level of performance and cost and an instance type determiner to, based on the resource utilization, determine if there is an instance type for at least one of the one or more instances, with a resource profile, that will provide a second level of performance and cost that is closer to a default level of performance and cost than the first level of performance and cost. In addition, the system also includes an instance type recommender to, based on the determining, perform one of making and not making a recommendation to replace the instance type of the at least one of the one or more instances.
