Abstract: Techniques for determining recommended allocations of resources among different platforms that sell a common type of inventory. Determining the allocations can include obtaining parameters of a campaign from a client. Determining the allocations can include combining current campaign parameters and scoring with historical campaign performance data to create recommendations for dividing resources among different media platforms.

Abstract: Systems and methods for a virtual network routing gateway that supports address translation for data plane as well as dynamic routing protocols are disclosed herein. The method can include coupling a gateway with a plurality of ports to a network having a plurality of first IP addresses in a private address space, generating a Network Address Translation (“NAT”) function in the gateway, inputting translation information into the NAT function, advertising routes based on the translation information, populating a unified routing table in the gateway based on the plurality of first IP addresses in the private address space and on translated route advertisements, receive an inbound network packet at the gateway, translating an inbound address of the inbound network packet with the NAT function, and delivering the network packet according to the routing table and based on the translated inbound address.

Abstract: Systems that determine relationships between network components of a cluster using packet filters are disclosed. A system can identify objects that implement services of a cluster and network connections associated with respective pairs of the objects. The system can also filter out network connections from the identified network connections. The filtering can remove connections between source objects and destination objects based on the destination objects lacking any components that implement a service in cluster. The filtering can also retain network connections between source objects and destination objects based on the source objects including components that implement at least one service, and based on the second destination object including components that implement at least one service. Additionally, the system can generate relationship maps and network topologies using the determined relationships.

Abstract: Automated techniques are for generating a large volume of diverse training data that can be used for training machine learning models to extract KV pairs from document images. Given a single input document image and associated annotation data, a large number of diverse synthetic training datapoints are automatically generated by a synthetic data generation system, each datapoint including a synthetic document image and associated annotation data. The generated synthetic training datapoints can be used to train and improve the performance of ML models for extracting KV pairs from document images. In certain implementations, multiple synthetic datapoints are generated by varying the values associated with a key for a content item within the input document image.

Abstract: Routines are used to connect bot queries entered via a bot interface and database queries executed on a database. Each routine is associated with routine configurations, including (a) query attributes associated with bot queries that trigger the routine, (2) a database query executed or to be executed for the routine, and/or (3) display settings for displaying information returned from the database query in a bot response. Each routine is configured to generate an output structured data object (SDO) indicating information returned from the database query and the display settings applicable to the information. The output SDOs from the various routines are transmitted to the bot application via a single API endpoint. The routine configurations are entered by a design user through one or more design user interfaces rendered by an integrative configuration application module.

Abstract: Systems are disclosed for determining contextual segments for targeting contextual advertising in metaverses. The system can deploy an observer avatar in a metaverse to capture information inside a portion of a metaverse from behaviors and interactions of a target user avatar. The observer avatar can capture audio, video, images, and text perceived by the observer avatar in the area of the user avatar, along with metadata describing the captured information. Using the captured observations, the system can determine contextual segments classifying the portion of the metaverse. Using a library of the contextual segments, advertisers can distribute contextually targeted advertisements.

Abstract: Routines are used to connect bot queries entered via a bot interface and database queries executed on a database. Each routine is associated with routine configurations, including (a) query attributes associated with bot queries that trigger the routine, (2) a database query executed or to be executed for the routine, and/or (3) display settings for displaying information returned from the database query in a bot response. Each routine is configured to generate an output structured data object (SDO) indicating information returned from the database query and the display settings applicable to the information. The output SDOs from the various routines are transmitted to the bot application via a single API endpoint. The routine configurations are entered by a design user through one or more design user interfaces rendered by an integrative configuration application module.

Abstract: A data hierarchy including individual data nodes may be used to represent a wide variety of data collections. Requests to change or add nodes in the data hierarchy may be received from many different sources over time. Instead of considering these change requests individually, an interface allows a plurality of change requests to be consolidated together into a single consolidated request. The consolidated request may be displayed in an interface such that changes from each of the original requests may be displayed together in an interface so that a cumulative effect of each of the change requests may be considered before the data changes are committed to the underlying data structure. The consolidated request may maintain links and update underlying data objects representing each of the original requests to provide a record of actions related to the consolidated request.

Abstract: A method includes generating dataset using topics associated with historical records, the dataset including pairs of data that are formed based on the topics, each of the pairs of data including an antecedent topic associated with a historical record corresponding to a preceding event and a consequent topic associated with a historical record corresponding to an event that occurred after the preceding event, the antecedent topic and the consequent topic forming a transitive relation for each of the pairs of data; inputting, into ML model, the pairs of data and input topic associated with a record of a user; generating, by the ML model, a prediction of a next record topic for a next record corresponding to the user, based on the consequent topic included in each of the pairs of data that include the antecedent topic corresponding to the input topic; and outputting the prediction.

Abstract: A computer-implemented method includes: obtaining a record including text narration; inputting the text narration into an NLP model; generating, by the NLP model, encoded narration based on the text narration; determining similarity index between the encoded narration and each of encoded reference topics; comparing the similarity index between the encoded narration and each encoded reference topic to similarity threshold; and determining whether the similarity index between the encoded narration and each encoded reference topic is equal to or greater than the similarity threshold. When the similarity index is equal to or greater than the similarity threshold, a corresponding reference topic is added to a result group, and, when the similarity index is less than the similarity threshold, the corresponding reference topic is left out of the result group.

Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.

Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.

Abstract: Obtaining collections of sentences in different languages that are usable for training models in various applications of artificial intelligence is provided. A method is provided that obtains, from text corpus, webpages in a plurality of languages, each of the webpages corresponding to an URL; obtains annotations for each of the webpages based on its URL, to obtain annotated data entries corresponding to the webpages, each of the annotated data entries including a classification label corresponding to a sub-topic of one of a plurality of topics, where each of the plurality of topics includes a corresponding plurality of sub-topics; filters the annotated data entries to obtain topic-specific content in a target language based on the classification labels, the topic-specific content corresponding to one or more sub-topics; performs post-processing on the topic-specific content to obtain result data; and outputs the result data for the topic.

Abstract: Described herein is a network fabric including a plurality of graphical processing unit (GPU) clusters that are communicatively coupled with one another via a plurality of switches arranged in a hierarchical structure including a first tier of switches, a second tier of switches, and a third tier of switches. One or more switches are selected from the third tier of switches to form a set of target switches, where each target switch receives address information of each GPU included in the plurality of GPU clusters. Each target switch generates, a plurality of sets of address information by filtering received address information based on a condition and transmits the plurality of sets of address information to each switch included in the first tier of switches, wherein the switch stores a subset of the plurality of sets of address information in accordance with the condition.

Abstract: A computer-implemented method to determine form factors of a tree includes building an input tree, wherein the input tree includes nodes. The method further includes implementing a first top-down pass to determine a universal number for each node in the input tree. The method further includes implementing a second top-down pass to determine form factors for each node of the input tree, wherein a form factor includes a depth and a width of the tree with a root in a corresponding node. The method further includes storing the form factors as part of node metadata or in a separate table.

Abstract: The present disclosure relates to systems and methods for automatic rule generation based on natural language input. Natural language input can be received. The natural language input can be tokenized. First tokens can be mapped to a first condition of a rule, and second tokens can be mapped to a second condition of the rule. A graph representation of the natural language input can be generated. A pre-generated, tenant-specific graph can be selected that corresponds to the graph representation of the natural language input. A rule can be generated based on the tenant-specific graph. The rule can be provided to facilitate implementation of the rule.

Abstract: Systems for repairing parse errors in query language statements are disclosed. In response to identifying one or more errors during parsing, a system can perform error recovery operations, including selecting a target sequence of parsable elements from candidate target sequences identified by a grammar. The operations can also include, determining a modification for the first sequence of elements including parsable elements corresponding to the target sequence. The operations can further include repairing first query by applying the modification to the first sequence. Additionally, the operations include generating error report, including information indicating the modifications that allowed parsing to succeed and suggested corrections.

Abstract: Techniques are disclosed for implementing a dynamically reconfigurable network lattice within a distributed computing system. A computing device may determine a combined configuration that includes a union of at least a subset of cloud infrastructure component topologies. The computing device may then provide instructions for implementing a physical layer characterized by the combined configuration. The computing device may then determine a subset configuration corresponding to a cloud infrastructure component topology of the subset of cloud infrastructure component topologies. The computing device may then deploy the subset configuration to the physical layer of the distributed computing system.

Abstract: Techniques for detecting and remediating anomalous intervals in time-series data of a monitored device are disclosed. A system trains a machine learning model on a combination of real data obtained from a monitoring device and false data generated by adding noise to the real data. The model predicts operating values for the device at individual intervals of a time-series data set. The system identifies anomalies in the time-series data based on differences between the predicted values and the real values. If the difference between a predicted value generate by the machine learning model and the real value exceeds a threshold, the system identifies a particular data point, such as a meter reading, as anomalous. The system ranks anomalies to perform remediation operations based on the ranking.

Abstract: Each host machine of a plurality of host machines stores hierarchical locality information for the host machine that identifies at least a rack comprising the host machine, and a block of a plurality of blocks hosting the rack. The host machine is associated with one or more graphical processing units (GPUs), and wherein GPUs included in a first block operate at a first speed and GPUs included in a second block operate at a second speed that is different than the first speed. Responsive to receiving a request requesting execution of a workload, one or more host machines are identified as being available for executing the workload, and the hierarchical locality information and linkage information of the one or more host machines is provided in response to the request.

Abstract: Techniques in this disclosure include polling statuses of one or more assets with one or more messages signed by a device private key. The statuses can be polled by a computing device. The techniques can include receiving one or more replies from the one or more assets. A reply can be signed with an asset private key and the reply can contain an asset status. The computing device can validate the one or more replies using one or more asset public keys. The computing device can add the statuses from the validated replies to a status log.

Abstract: Techniques are disclosed herein for a direct launch for asynchronous actions. An example method can include receiving, by a device, a first workflow request, wherein the device comprises a first launcher in operable communication with a second launcher via a shared queue, and wherein a first duplicate of the first workflow request is stored in the shared queue is to be retrieved by the second launcher upon an elapsing of a threshold time interval. The device can transmit the workflow request to an application for executing the first workflow request, wherein the transmission is prior to the threshold time elapsing. The device can determine whether the application initiated a workflow to process the workflow request. The device can update the first duplicate of the first workflow request stored at the shared queue based at least in part on the determination and prior to the threshold time interval elapsing.

Abstract: Described herein is a network fabric including a plurality of graphical processing unit (GPU) clusters. The plurality of GPU clusters includes at least a first GPU cluster operating at a first speed and a second GPU cluster operating at a second speed that is different than the first speed. The network fabric includes a plurality of blocks, wherein each block includes: (a) one or more racks that host a GPU cluster, and (b) a plurality of switches arranged in a hierarchical structure that communicatively couple the block to other blocks included in the network fabric. Responsive to receiving a request to execute a workload, allocating one or more GPUs from the plurality of GPU clusters to execute the workload.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A current value for an aggregate power threshold of a plurality of hosts may be identified. During a first time period, an aggregate power consumption of the plurality of hosts may be managed using the current value for the aggregate power threshold. A triggering event indicating a modification to the aggregate power threshold is needed may be detected. A new value for the aggregate power threshold may be determined based on the triggering event. During a second time period, the aggregate power consumption of the plurality of hosts may be managed using the new value for the aggregate power threshold.

Abstract: Techniques for configuring a software system include generating a hierarchy of entities representing usage of the software system by a set of users, wherein the hierarchy includes a first set of nodes representing a set of tasks, a second set of nodes representing a set of components that implement the tasks, and a set of edges between the first set of nodes and the second set of nodes. The techniques also include updating the hierarchy based on a first set of configurations for the tasks, wherein the updated hierarchy indicates one or more tasks that have been enabled for the users. The techniques further include determining, based on the updated hierarchy, one or more components that implement the task(s). Finally, the techniques include generating, based on the hierarchy, one or more runbooks that execute the task(s) using the component(s).

Abstract: The present disclosure is directed to devices and techniques for auto-qualifying images on new hardware or infrastructure configurations. The systems and methods include initiating an auto-qualification process for pre-testing one or more images registered within a bare metal system having one or more new infrastructure configurations, discovering all of the one or more images registered for use within the bare metal system, booting each of the one or more registered images into an isolated infrastructure having the one or more new infrastructure configurations, probing instances of each of the one or more registered images booted on the isolated infrastructure to determine stability of each of the one or more registered images on the one or more new infrastructure configurations, and marking each of the one or more registered images as stable or unstable.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. Power consumption of power-drawing devices (e.g., hosts, servers, etc.) may be monitored with respect to a power threshold. When the current power consumption corresponding to those devices breaches the power threshold, or at any suitable time, the system may identify a set of reduction actions configured to reduce aggregate power consumption. The power threshold may be updated dynamically based on the operational status of related systems and environmental factors. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: The present disclosure provides dynamic routing for data flows to a customer network hosted in the cloud. A plurality of compute instances may share a common virtual IP address. Each of the plurality of compute instances may advertise information to a respective network virtualization device (NVD). The information may include the IP address, cost, and/or active/standby status of the compute instance. The NVD may then provide the information to the control plane of a virtual cloud network (VCN), which may aggregate the information from the plurality of compute instances and generate a forwarding table, which may be sent to the NVDs. These techniques may allow a customer to automatically remove a compute instance whose service host has failed. These techniques may also allow a customer to add compute instances and to route data flows according to an active-standby operation, an equal cost active-active operation, or an unequal cost active-active operation.

Abstract: Techniques for generating smart contract transaction data from a program embedded in the smart contract are disclosed. A distributed ledger system stores a smart contract specifying conditions of a transaction. Based on a user input to initiate the transaction, the system executes the smart contract transaction on the distributed ledger. A node executing the smart contract transaction executes the transaction verification program embedded within the smart contract. The transaction verification program includes instructions for transmitting the parameters of the transaction to a third party.

Abstract: A plurality of GPU clusters are communicatively coupled with one another via a plurality of network devices arranged in a hierarchical structure, wherein the GPU clusters includes at least a first GPU cluster operating at a first speed and a second GPU cluster operating at a second speed that is different than the first speed. A routing policy is configured for each network device, wherein the configuring includes establishing a mapping of each incoming port-link of the network device to a unique outgoing port-link of the network device. For a packet transmitted by a GPU of a host machine and received by a first network device, an incoming port-link of the first network device is determined on which the packet was received and based on the configuring, an outgoing port-link is identified that corresponds to the incoming port-link. The packet is forwarded on the outgoing port-link of the network device.

Abstract: Continual learning techniques are described for extending the capabilities of a base model, which is trained to predict a set of existing or base classes, to generate a target model that is capable of making predictions for both the existing or base classes and additionally for making predictions for new or custom classes. The techniques described herein enable the target model to be trained such that the model can make predictions involving both base classes and custom classes with high levels of accuracy.

Abstract: Techniques are described for creating a container environment that implements direct communications between pods. This includes the creation of a management component (such as a control plane) of the container environment, the creation of nodes within an implementation component (such as a data plane) of the container environment, and the attaching of virtualized network interface cards (VNICs) to each node. This also includes creating a custom resource for each node, where the custom resource stores internet protocol (IP) addresses assigned to the node and stored within the VNICs for the node. Pods implemented within these nodes obtain an IP address from the VNICs for their respective node and communicate with each other utilizing the IP addresses via virtual communication devices and the VNICs.

Abstract: A method includes accessing document including sentences, document being associated with configuration flag indicating whether ABSA, SLSA, or both are to be performed; inputting the document into language model that generates chunks of token embeddings for the document; and, based on the configuration flag, performing at least one from among the ABSA and the SLSA by inputting the chunks of token embeddings into a multi-task model. When performing the SLSA, a part of token embeddings in each of the chunks is masked, and the masked token embeddings do not belong to a particular sentence on which the SLSA is performed.

Abstract: A computing system may access a source device configured to store device traffic in a source device queue. The computing system may launch, by one or more worker nodes of a control plane of the computing device, a destination device. The computing system may transmit a source device state to the destination device. The control plane worker nodes may configure the destination device from the source device state. The computing system may instruct the source device to pause storing the device traffic to the source device guest memory. The computing system may store dirty page information in the computing system memory. The computing system may transmit the dirty page information to the destination guest memory. The computing system may instruct the destination device to resume storing the device traffic to the destination guest memory.

Abstract: According to certain implementations, a certificate management service of a cloud service provider requests a certificate for a domain from a certificate authority utilizing an HTTP-based challenge. The certificate authority responds with a challenge string and a subdirectory within the domain. The challenge string and subdirectory within the domain are sent from the certificate management service to a proxy server of the cloud service provider that manages a flow of data to a host that hosts the domain. When the certificate authority sends a request to the sub directory within the domain, the request is intercepted at the proxy server. Instead of forwarding the request to the host that hosts the domain, the proxy server responds to the certificate authority with the challenge string. This verifies ownership of the domain, which is required to obtain the certificate for the domain.

Abstract: The present embodiments relate to identifying and mitigating memory bit flips in a cloud infrastructure service. The cloud infrastructure service can provide a monitoring system to monitor low level memory space to detect bit flips by the DRAM instances in the cloud infrastructure service. The bit flips detected in various DRAM computing instances can be processed to verify that the bit flips are sustained (e.g., and possibly relating to a Rowhammer attack) rather than transitory bit flips occurring in DRAM computing devices. Responsive to validating a set of bit flips at one or more computing instances, workloads associated with the affected computing instances can be migrated to other computing instances in the cloud infrastructure service.

Abstract: Disclosed herein are techniques for using a generative adversarial network (GAN) to train a semantic parser of a dialog system. A method described herein involves accessing seed data that includes seed tuples. Each seed tuple includes a respective seed utterance and a respective seed logical form corresponding to the respective seed utterance. The method further includes training a semantic parser and a discriminator in a GAN. The semantic parser learns to map utterances to logical forms based on output from the discriminator, and the discriminator learns to recognize authentic logical forms based on output from the semantic parser. The semantic parser may then be integrated into a dialog system.

Abstract: In response to a request to replicate resources from a primary region data center to a secondary region data center, an executable configuration file that describes the resources and their configuration is created utilizing information about the resources at the primary region data center. A correspondence table is also updated to include entries for to such resources. Utilizing the correspondence table, the executable configuration file is transformed to create a transformed executable configuration file that references the resources utilizing generic resource identifiers instead of primary region identifiers used within the primary region data center. The transformed executable configuration file is then executed at the secondary region data center to create replicated resources at the secondary region data center.

Abstract: A computer-implemented method includes: accessing a plurality of datasets, where each dataset of the plurality of datasets includes training examples; selecting datasets that include the training examples in a source language and a target language; and sampling, based on a sampling weight that is determined for each of the selected datasets, the training examples from the selected datasets to generate the training batches; training an ML model for performing at least a first task using the training examples of the training batches, by interleavingly inputting the training batches to the ML model; and outputting the trained ML model configured to perform the at least the first task on input utterances provided in at least one among the source language and the target language. The sampling weight is determined for each of the selected datasets based on one or more attributes common to the training examples of the selected dataset.

Abstract: The present disclosure is related to techniques for converting a natural language utterance to a logical form query and deriving a natural language interpretation of the logical form query. The techniques include accessing a Meaning Resource Language (MRL) query and converting the MRL query into a MRL structure including logical form statements. The converting includes extracting operations and associated attributes from the MRL query and generating the logical form statements from the operations and associated attributes. The techniques further include translating each of the logical form statements into a natural language expression based on a grammar data structure that includes a set of rules for translating logical form statements into corresponding natural language expressions, combining the natural language expressions into a single natural language expression, and providing the single natural language expression as an interpretation of the natural language utterance.

Abstract: Techniques for perspective-preserving seamless application switching are disclosed. A system may display a first interface using a first application. The first interface includes interface elements representing a plurality of objects. The system may detect a zoom-in command, received by the first application, requesting a particular zoom level for a first interface element, corresponding to a first object in the first plurality of objects. The system may determine that the requested zoom level exceeds a threshold. Responsive to determining that the requested zoom level exceeds the threshold, the system may display, using a second application, a second interface corresponding to the first object. The second interface may include one or more of: (a) characteristics associated with the first object that were not displayed by the first application, or (b) user input elements for executing operations associated with the first object that were not displayed by the first application.

Abstract: Approaches of reassigning a home region from a first data center to a second data center as requested by a customer are described herein. The home region is able to implement write operations to a domain, whereas other data centers cannot implement write operations to the domain. The customer can request the home region being reassigned to another data center such that the customer can utilize the other data center to implement write operations to the domain.

Abstract: Techniques are described for a hierarchical caching mechanism enabling efficient cross-region replications. In some embodiments, replication-related information (e.g., key-value pairs) is stored in a particular layout in a binary tree (B-tree) of a file system for replication processing. A hierarchy of caches storing a first type of information (e.g., crypto keys associated with iNodes) may be arranged to match the particular layout in the B-tree to enable efficient parallel processing of a second type of information (e.g., files, file data, or symbolic links), where the replication-related information in the B-tree is partitioned into multiple key ranges for parallel processing. In some embodiments, the caches in different hierarchies may be shared by different parallel-processing key ranges and replication jobs in a file system.

Abstract: A computer-implemented method includes obtaining, from text corpus including article-summary pairs in a plurality of languages, a plurality of article-summary pairs in a target language among the plurality of languages, to form an article-summary pairs dataset in which each article corresponds to a summary; inputting articles from the article-summary pairs to a machine learning model; generating, by the machine learning model, embeddings for sentences of the articles; extracting, by the machine learning model, keywords from the articles with a probability that varies based on lengths of the sentences, respectively; outputting, by the machine learning model, the keywords; applying a maximal marginal relevance algorithm to the extracted keywords, to select relevant keywords; and generating a keyword-text pairs dataset that includes the relevant keywords and text from the articles, the text corresponding to the relevant keywords in each of keyword-text pairs of the keyword-text pairs dataset.

Abstract: Techniques are described for implementing a container environment where each pod within the container environment is provided with a unique IP address and a virtual communication device such as an IPvlan device. Communications from source pods are directly routed to destination pods within the container environment by one or more virtualized network interface cards (VNICs) utilizing the unique IP addresses of the destination pods, without the need for bridging and encapsulation. This reduces a size of data being transmitted and also eliminates a compute cost necessary to perform encapsulation of data during transmission.

Abstract: Techniques are described for providing a multi-cloud control plane (MCCP) in a first cloud infrastructure (included in a first cloud environment provided by a first cloud services provider) that enables services and/or resources provided in the first cloud infrastructure to be utilized by users of a second cloud environment, where the second cloud environment is different than the first cloud environment. The multi-cloud infrastructure enables a user associated with an account with a second cloud services provider to use, from the second cloud infrastructure, a first service from the set of one or more cloud services. The multi-cloud infrastructure creates a link between the account with the second cloud service provider and a tenancy created in the first cloud infrastructure for enabling using the first service by the user.

Abstract: A method includes preparing a base model using an input model pretrained on at least three languages different from each other and a base vocabulary including words corresponding to two languages among the at least three languages, where the preparing the base model includes constraining the input model to the words included in the base vocabulary; training the base model using a first enhanced training dataset generated from public data, to generate a text summarization model; training the base model using a second enhanced training dataset generated from the first enhanced training dataset, to generate a text generation model; and training the base model using a third enhanced training dataset that is generated using the second enhanced training dataset and the text summarization model, to generate a next sentence generation model.

Abstract: Techniques for configuring an enriched data metrics pipeline (DMP) include: obtaining node configuration data associated with an unenriched DMP for nodes of a heterogeneous computing platform, including (a) a first kind of node including an application programming interface (API) for obtaining unenriched data associated with the first kind of node and (b) a second kind of node including an API for obtaining unenriched data associated with the second kind of node; the unenriched DMP being configured to provide node-level unenriched data to a service according to a first schedule; the service being configured to generate node-level data metrics based on the unenriched data; based on the node configuration data, configuring an enriched DMP to provide node-level enriched data to the service according to a second schedule that is less frequent than the first schedule; the service being configured to generate fleet-level data metrics based on the node-level enriched data.

Abstract: Techniques are described herein for analyzing and tuning database workloads to optimize application performance. In some embodiments, a workload analyzer identifies a captured workload that includes a set of database queries executed within a particular timeframe. The workload analyzer compares the workload within one or more other workloads executed within a previous timeframe to determine differences between the different workloads. For example, the workload analyzer may identify changes in the distributions of queries, including how many queries are unchanged, missing, and/or new. The workload analyzer may further detect changes in the performance of individual queries. The workload analyzer may determine the overall performance impact of such changes on the total workload. Based on the analysis, the workload analyzer may generate reports, alerts, tuning advice, and/or recommendations to boost performance.