Abstract: In an integrated circuit (IC) assessment method, an artificial intelligence (AI) component comprising at least one artificial neural network (ANN) is trained to transform layout rendering tiles of a rendering of a reference IC into corresponding reference layout image tiles extracted from at least one layout image of the reference IC. Using the trained AI component, standard cell layout renderings of a library of GDSII or OASIS standard cell layout renderings are transformed into as-fabricated standard cell layout renderings forming a library of as fabricated standard cell layout renderings. Instantiated standard cells and their placements in the layout image of an IC-under-test are identified by matching the instantiated standard cells with corresponding as-fabricated standard cell layout renderings retrieved from the library of as fabricated standard cell layout renderings.

Abstract: A computer design verification system comprising a parsing module configured to receive output messages from a computer design testing tool and to compose from the output messages formatted objects comprising a set of fields having field descriptors and test values; a signoff module holding a plurality of signoff objects, each comprising a plurality of fields having a field descriptor, at least some fields populated with a signoff expression, each signoff object associated with a severity level indicative of the severity of a condition represented by the signoff object. The signoff module is configured compare at least one test value in the formatted objects received from the parsing module with at least one signoff expression in the signoff objects to determine if a signoff object matches the formatted object, and in the case of a match, associating the severity level of the signoff object with the formatted object.

Abstract: A computing system configured to verify design of an integrated circuit (IC) includes a memory and a processor. The memory is configured to store computer executable instructions. The processor is configured to generate a first coverage model for at least two high-level parameters from the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard or hardware description language (HDL) code by executing the computer executable instructions, generate a second coverage model for low-level internal signals from the HDL code by executing the computer executable instructions, and generate a plurality of test packets for a regression test by using at least one of the first coverage model or the second coverage model by executing the computer executable instructions.

Abstract: A method is provided for performing power validation on an integrated circuit (IC) design based on a power assertion specification. The method includes receiving the power assertion specification for the IC design, where the power assertion specification includes a predicted power consumption. Power consumption of the IC design is estimated according to power assertions specified in the power assertion specification. The estimated power consumption is compared against the predicted power consumption included in the power assertion specification. The IC design is determined to be associated with a power assertion failure based on results of the comparing. In response to determining that the IC design is associated with the power assertion failure, the IC design is refined to remedy the power assertion failure.

Abstract: Reset Domain Crossing (RDC) detection and simulation is provided via identifying a plurality of RDCs between flip-flops of a sequence of flip-flops leading to an observation point in a circuit design; classifying each RDC of the plurality of RDCs as one of observable at the observation point or not observable at the observation point based on a reset order applied to the sequence of flip-flops; and outputting a list of the plurality of RDCs classified as observable at the observation point.

Abstract: A system includes one or more data processors and a non-transitory computer-readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform operations. The operations include receiving a design schematic, extracting keywords from the design schematic, and sorting the design schematic by the extracted keywords. The operations further include extracting a part number of a component from the sorted design schematic, comparing the component associated with the part number with a reference component associated with the part number, and displaying a result of the comparison indicating whether the component and the reference component match.

Abstract: A layout method includes disposing a first conductive path and a second conductive path across a boundary between a first layout device and a second layout device abutting the first layout device. The layout method also includes disposing a first cut layer on the first conductive path nearby the boundary, and disposing a second cut layer on the second conductive path nearby the boundary. The layout method also includes moving the first cut layer to align with the second cut layer.

Abstract: A specification for a modular circuit design includes a mapping from global clock domains to global voltage domains. A processor assigns, to a first instance of a clocked primitive component, a global voltage domain based on which global clock domain clocks the first instance, automatically adds, to the modular circuit design, first power supply rails to power the first instance, and connects the first power supply rails from the first instance to a first power supply for a first global voltage domain. The processor assigns, to a second instance of the clocked primitive component, a second global voltage domain based on which global clock domain clocks the second instance, automatically adds second power supply rails to power the second instance, and connects the second power supply rails to a second power supply for a second global voltage domain. The processor may perform further processing on the updated modular circuit design.

Abstract: A modeling circuit of a field effect transistor includes a first field effect transistor, a first bipolar transistor, a second bipolar transistor and a substrate resistor. The first bipolar transistor has a collector electrode connected to a first node corresponding to a first electrode of the first field effect transistor, an emitter electrode connected to a second node corresponding to a second electrode of the first field effect transistor, and a base electrode. The second bipolar transistor has a collector electrode connected to the second node, an emitter electrode connected to the first node, and a base electrode connected to the base electrode of the first bipolar transistor. The substrate resistor is connected between the base electrodes of the first and second bipolar transistors and a first surface of a semiconductor substrate on which the first field effect transistor is formed.

Abstract: A method of generating an IC layout diagram includes receiving a first gate resistance value of a gate region in an IC layout diagram, the first gate resistance value corresponding to a location of a gate via positioned within an active region and along a width of the gate region extending across the active region, determining a second gate resistance value based on the location and the width, using the first and second resistance values to determine that the IC layout diagram does not comply with a design specification, and based on the non-compliance with the design specification, modifying the IC layout diagram.

Abstract: The present disclosure provides an image processing method and apparatus, and an electronic device, and relates to the field of artificial intelligence (AI). The method includes: obtaining an input image and extracting region features of image regions in the input image to obtain a first image feature; processing pixels in the first image feature according to a predetermined rule, and determining a second image feature according to the processed pixels; and determining, based on the second image feature and at least one word vector that is determined for the input image, word vectors corresponding to the region features of the image regions in the first image feature at different moments, predicting positions of the word vectors in a text description, and forming the text description corresponding to the input image according to the word vectors and the positions.

Abstract: A client device processing received emoji messages using emoji-first messaging. Text messaging is automatically converted to emojis by an emoji-first application so that only emojis are communicated from one client device to another client device. Each client device has a library of emojis that are mapped to words, which libraries are customizable and unique to the users of the client devices, such that the users can communicate secretly in code. Upon receipt of a string of emojis, a user can select the emoji string to convert to text if desired, for a predetermined period of time.

Abstract: Disclosed herein is a web user experience improvement for digital magazines. A digital magazine viewing platform is integrated with a digital magazine publishing platform including features that leverage the integration including user interface arrangement based on viewing habits and ripped content that is insertable into draft digital magazine documents. In some embodiments, a machine learning model categorizes magazine styles and present publishing features based on those magazines viewed or subscribed to by a given user.

Abstract: A computer implemented method includes receiving embedded font text defining characters associated with an original font family. The embedded font text is processed to generate original glyph metrics data, a combined original font glyph width based on the original glyph metrics data, and one or more candidate font families are identified. For each candidate font family a combined candidate font family glyph width is calculated and a candidate font family difference, the candidate font family difference being a measure of how the candidate font family's combined candidate font family glyph width compares to the combined original font glyph width. A particular candidate font family is selected as a replacement font family based on the candidate font family differences of the one or more candidate font families.

Abstract: A calculation process is efficiently performed to a text file in which one or more records are included, each of the records includes one or more cells having an arbitrary length, and each of the cells includes arbitrary pieces of characters. A parameter setting apparatus sets a maximum value Scsv and a minimum value scsv of a size of character strings for one record by using attribute information as an input, a maximum value Senc of a total size of encode information, a maximum value Sss of a total size of a calculation value obtained by performing specific calculation to the encode information, and a total size Sref of reference information, obtains a function value of C/(Scsv+Senc+Sref) as the number of records which is a process unit of encoding and calculation, and obtains a function value of f0/I·r·Scsv as the number of parallels in the calculation process. Here, C is a cache memory size, M is a main memory size, and f0 is a function value of scsv·M/(scsv+Senc+max(Sref,Sss)).

Abstract: A method of enhancing a link in collaboration applications includes determining, from content entered into a collaboration application, a string of characters indicating a uniform resource locator (URL). Upon determining the string of characters indicating the URL from the content entered into the collaboration application, the method includes automatically calling a first web service to obtain a representation of content referenced by the URL by sending a request, at least including the URL, to the first web service. The representation of the content referenced by the URL can then be received from the first web service in a format customized for the collaboration application, a computing device on which the collaboration application is implemented, or both.

Abstract: Embodiments of the technology described herein are directed to a persona-specific navigation interface for a document. Initially, a user may select a persona associated with a document through a document navigation interface. A machine-learning model may identify an interest within a portion of the document. The interest may be mapped to the persona. A navigation interface that includes a navigable link to the portion of the document is generated and output for display. A user interaction with the navigable link is received. In response to the interaction, the portion of the document corresponding to the navigable link is output for display.

Abstract: A request for a content item that is to be provided for display in a page is received. A content template is embedded in code associated with the page. The content template is embedded at a selected location of a plurality of potential locations of the page that are compatible with the content template. The content item for the page is obtained based on the content template. The content item associated with the embedded content template is provided for display in the page. The content item associated with the embedded content template is provided for display at the selected location.

Abstract: Computer-implemented techniques are disclosed for presenting an in-page console on a website for reviewing interaction data captured during user interaction with one or more web pages of the website. The web browser activates the in-page console via an activation procedure. One or more of the web pages of the website are selected after activation of the in-page console. A feedback badge on the website can be replaced with a reporting badge upon activation of the in-page console and with the reporting badge displaying an indicator of interaction data captured for the selected web page. The in-page console is overlaid one or more of the selected web pages. The in-page console displays the interaction data, or recordings of user interaction, captured during user interaction with the selected web page to enable review of the captured interaction data for the selected web page overlaid on the selected web page.

Abstract: A method includes receiving a user event associated with content of an add-on for a web application displayed on a first user interface. The add-on is a non-native application executed using a hypertext markup language (HTML) element. The method further includes passing the user event to a document object model of the web application using a blank native element. The blank native element links the add-on to the document object model. The method further includes processing the user event using an HTML element renderer. The method further includes displaying updated content associated with the add-on based on the processed user event.

Abstract: Systems and methods are provided for enhancing text-based electronic communications. In one embodiment, a sending agent automatically, or upon request by a user, disambiguates identifiers and terms included in a communication internally or in collaboration with a remote device or server based on the identity and history of the sending or intended receiving device or user, the content or context of the communication and/or the sending or intended receiving device or user and automatically or at the request of the sender, appends, enhances or provides certain additional information related to the identifier or terms to the message in real time. This additional information is then included or referenced, but not necessarily initially displayed or communicated, in the communication. The integrated system also may include a receiving agent on the receiving device that can disambiguate the identifier or terms and provide additional information and services related to the identifier or terms in the communication.

Abstract: The present disclosure provides systems and methods for encoding and decoding a machine-readable document. A system can include a computing device comprising a processor and a memory. To encode each entry on a document, the processor can receive an identification of an entry, identify an entry format, and generate an entry fingerprint. The processor can calculate a hash value from the identification, the entry format, and the entry fingerprint, which can then be stored at an address corresponding to the hash value. The processor can generate an optical code, and print the entry and the optical code on the document. To decode the document, the processor can extract the hash value, a first entry identifier, and a user identifier from the optical code. The processor can retrieve a second entry identifier and determine a match with the first entry identifier. The processor can retrieve entry coordinates and extract the entry.

Abstract: A method and apparatus for managing an interface, a device and a non-transitory computer readable storage medium. The method includes: acquiring a first interface image of a target application, determining a first text contained in the first interface image, the first text being a text in a first language corresponding to the target application, acquiring a second text obtained by translating the first text, the second text being a text in a second language, and replacing the first text in the first interface image with the second text to obtain a second interface image, and displaying, based on the target application, the second interface image.

Abstract: Methods and systems for artificial intelligence (AI)-assisted document annotation and training of machine learning-based models for document data extraction are described. The methods and systems described herein take advantage of a continuous machine learning approach to create document processing pipelines that provide accurate and efficient data extraction from documents that include structured text, semi-structured text, unstructured text, or any combination thereof.

Abstract: The information processing apparatus analyzes the results of modification performed by user for a recommended character string and determines whether there is an excess or a lack in units of predetermined character string areas in a recommended area corresponding to the recommended character string. In a case where it is determined that there is an excess or a lack as a result of the determination, a recommended character string that eliminates the excess or the lack is specified. Then, area information for specifying the recommended area, which is registered in a database, is updated so that the character string corresponding to the specified recommended area becomes the recommended character string.

Abstract: Various embodiments include a method for document creation. The method can include presenting a frame, presenting a first portion of a first collection of data, receiving a denial of the first portion of the first collection for the first group, presenting a first portion of a second collection of data for the first group, receiving a confirmation of the second collection for the first group, presenting a second portion of the first collection of data, receiving a confirmation or a denial of the second portion of the first collection for the second group, presenting a second portion of the second collection of data for the second group, after receiving a denial of the second portion of the first collection, receiving a confirmation of the second portion of the second collection for the second group, compiling confirmed portions of data into a prose output, and presenting the prose output.

Abstract: Systems, methods, and computer-readable media for generating a network map reflective of node connection strength are disclosed.

Abstract: Embodiments of the disclosed technologies include receiving, from a first user device, a first user interface event that includes an upload of a media asset but does not indicate an intended usage for the media asset, determining an intended usage based on a second user interface event, mapping the intended usage to a usage-based specification, converting the media asset to a usage-specific version of the media asset by applying the usage-based specification to the media asset, and initiating a distribution of the usage-specific version of the media asset instead of the media asset to at least one second user device different from the first user device.

Abstract: Systems and methods of converting user input into a standardized input are disclosed. An exemplary method includes receiving via a user input a string including a first set of characters and a second set of characters positioned on either side of a dividing symbol; converting the first set of characters into a first standardized input; converting the second set of characters into a second standardized input that establishes how to delineate the plurality of items of the data set into the number of groups based on the numerically sortable attribute of the data set; and displaying, on a graphic user interface, the number of groups as established by the first standardized input, each group populated by a subset of the set of the plurality of items of the data set as delineated by the second standardized input.

Abstract: As described herein, a system for expanding contractions in electronically stored text includes expanding contractions having only on expanded form. For remaining contractions, a grammar check is performed for all possible expanded forms to determine if an expanded form can be selected based on context and grammar rules. If an expanded form is not evident from the first two steps, all possible expanded forms of the remaining contractions are converted to a vector representation along with the original text. A Word Movers Distance (WMD) for each possible expansion is calculated using the vectors for each possible expansion and the original text. An expanded form is chosen without human intervention based on the grammar score alone or the WMD and the grammar score.

Abstract: Systems and methods dynamically extracting n-grams for automated vocabulary updates. Text is received. An n-gram extracted from the text is matched to a canonical n-gram from a vocabulary to identify a tag for the text. An n-gram weight is computed for the n-gram extracted from the text. The n-gram weight may be computed by adjusting a term frequency of the n-gram. A relevancy score is computed for the tag using the n-gram weight and using an n-gram frequency of the canonical n-gram. The relevancy score is computed by dividing the n-gram weight by a value proportional to the n-gram frequency of the canonical n-gram. The relevancy score of the n-gram is presented.

Abstract: Systems and methods for user-agent anomaly detection are disclosed. In one embodiment, a user-agent string may be embedded into a numerical data vector representation using a sentence embedding algorithm (e.g., FastText). A predictive score may be calculated based on the numerical data vector representation and using a probability distribution function model that models a likelihood of occurrence of the observed user-agent based on patterns learned from historic payload data (e.g., a Gaussian Mixture Model). The predictive score may be compared to a threshold and, based on the comparison, it may be determined whether the user-agent is fraudulent.

Abstract: An item recall method includes: behavior data is acquired, where the behavior data includes items and item information of each item; target behavior data containing a retrieval category word is extracted from the behavior data; retrieval words of each item and a retrieval frequency of each retrieval word are acquired in a reverse correlation manner; word segmentation is performed on the item information to obtain multiple item segmented words; a similarity between all retrieval words and the multiple item segmented words is calculated; whether the similarity is greater than a first preset threshold or not is determined, and if yes, then a retrieval word is extracted as an expansion word of the retrieval category word; and item recall is performed according to the retrieval category word and the expansion word.

Abstract: Identifying documents that contain potential code words using a machine learning model. In some embodiments, a method may include receiving documents, identifying a first corpus and a second corpus in the documents, extracting a first set of word embeddings from the first corpus and a second set of word embeddings from the second corpus, generating a first vector space for the first set of word embeddings and a second vector space for the second set of word embeddings using a machine learning model, performing a vector rotation to improve alignment of the first set of word embeddings with the second set of word embeddings, identifying a word embedding in the first vector space that is not aligned with a corresponding word embedding in the second vector space as a potential code word, and identifying one or more documents that contain the potential code word in the first corpus.

Abstract: A method and an apparatus for sequence labeling on an entity text, and a non-transitory computer-readable recording medium are provided. In the method, a start position of an entity text within a target text is determined. Then, a first matrix is generated based on the start position of the entity text. Elements in the first matrix indicates focusable weights of each word with respect to other words in the target text. Then, a named entity recognition model is generated using the first matrix. The named entity recognition model is obtained by training using first training data, the first training data includes word embeddings corresponding to respective texts in a training text set, and the texts are texts whose entity label has been labeled. Then, the target text is input to the named entity recognition model, and probability distribution of the entity label is output.

Abstract: An automatic terminology linking system includes a candidate generator configured to identify candidate nodes for each terminology that is to be linked to a node of the knowledge base. A pseudo-candidate generator is configured to identify pseudo-candidate nodes for candidate-less terminologies. A candidate scorer is configured to respectively score the candidate nodes and the pseudo-candidate nodes by collective inference using occurrence statistics and co-occurrence statistics for these nodes. The pseudo-candidate generator is configured to identify knowledge base nodes that are semantically-related to candidate-less terminology as the pseudo-candidate nodes for the candidate-less terminology.

Abstract: A system includes: a natural language processing (NLP) model trained in a training domain and configured to perform natural language processing on an input dataset; an accuracy module configured to: calculate a domain shift metric based on the input dataset; and calculate a predicted decrease in accuracy of the NLP model attributable to domain shift relative to the training domain based on the domain shift metric; and a retraining module configured to selectively trigger a retraining of the NLP model based on the predicted decrease in accuracy of the NLP model.

Abstract: Systems and methods associated with generation and/or provision of predictive content are disclosed. One exemplary method includes receiving communications associated with a plurality of customers; determining a message type for each message of the communications; splitting first messages of the first message type into a first set of subcomponent text sections; splitting second messages of the second message type into a second set of subcomponent text sections; analyzing the first set and the second set to generate a plurality of semantic numerical scores for each respective subcomponent text section; determining at least one impactful semantic category for a target audience by selecting at least one semantic category corresponding to at least one semantic numerical score of at least one subcomponent text section of the first set or the second set that is equal to or higher than a first pre-determined threshold value; generating personalized textual content targeting the audience.

Abstract: The disclosure relates to system and method for processing user input using Natural Language Processing (NLP). The method includes generating, by an NLP model, a set of input intent maps associated with a user input. The method includes matching each of the set of input intent maps with each of a plurality of pre-stored sets of intent maps. Each of the plurality of pre-stored sets of intent maps is generated from a single predefined training input and is mapped to a predefined intent and a predetermined response. The method includes determining a distance of each of the set of input intent maps relative to each of the plurality of pre-stored sets of intent maps. Further, the method includes identifying a pre-stored intent map closest to the set of input intent maps and rendering the predetermined response mapped to the pre-stored sets of intent maps to the user.

Abstract: Various embodiments of a system and associated method for anonymization of text without losing semantic utility of text by extracting a latent embedding representation of content with respect to a given task and by learning an optimal strategy for text embedding manipulation to satisfy both privacy and utility requirements are disclosed herein. In particular, the system balances private attribute obfuscation with retained semantic utility.

Abstract: A system for assisting sharing of information includes circuitry to: input a plurality of sentences each representing a statement made by one of a plurality of users, the sentence being generated by speaking or writing during a meeting or by extracting from at least one of meeting data, email data, electronic file data, and chat data at any time; determine a statement type of the statement represented by each one of the plurality of sentences, the statement type being one of a plurality of statement types previously determined; select, from among the plurality of sentences being input, one or more sentences each representing a statement of a specific statement type of the plurality of types; and output a list of the selected one or more sentences as key statements of the plurality of sentences.

Abstract: The present disclosure provides a method for selecting an annotated sample. The method includes: determining a first attribute and a second attribute of a sample characteristic; in which the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set; and determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute; in which the target annotated sample is configured to train a classification model, the classification model includes a model for determining an emotion polarity by analyzing an input sample to be classified.

Abstract: Systems, methods and products for accessing a set of electronic document templates, identifying instances of common document content such as content items which are semantically similar, and generating component templates containing the common content. Semantically similar content may be identified by analyzing content for factors such as expressed sentiment, included keyphrases, recognizable entities, expressed topics, assigning values to content based on these factors, and determining similarity based on comparisons of the assigned values. Component templates may also be generated based on types of content that include identical text or images, content that has a predefined level of similarity rather than being identical, content that has common rules, scripting logic or variables, metadata, etc. The component templates may be generated automatically, or in response to user instructions.

Abstract: A computer executed process for mimicking human dialog, referred to herein as a “humanoid” or “humanoid process software,” can be configured to participate in multi-party conversations. The humanoid can monitor electronic communications in a conversation involving the humanoid and at least one other party. The humanoid can model the electronic communications by uniquely identifying each of the electronic communications as a stream of data. For example, the data can be labeled and sorted in a database and/or arranged in a nodal graph representation. The humanoid can participate in the conversation based on the modeling.

Abstract: The disclosure provides a role labeling method. The method includes: obtaining a dialogue sentence to be labeled and context information corresponding to the dialogue sentence, and splicing the context information and the dialogue sentence to obtain a spliced text; extracting location information of a role name of the dialogue sentence in the spliced text from the spliced text; determining a first candidate role name of the dialogue sentence based on the location information; determining a second candidate role name of the dialogue sentence from role names in the spliced text; and determining a target role name of the dialogue sentence based on the first candidate role name and the second candidate role name, and performing role labeling on the dialogue sentence based on the target role name.

Abstract: Computer-readable media, systems and methods may improve classification of content based on a machine-learning natural language processing (ML-NLP) classifier. The system may train a general language model based on a general corpus, further train the general language model based on a domain-specific corpus to generate a domain-specific language model, and conduct supervised machine-learning based on the domain-specific language using topic-specific corpus labeled as relating to topics of interest to generate the ML-NLP classifier. Accordingly, the ML-NLP classifier may be trained on a general corpus, further trained on a domain-specific corpus, and fine-tuned on a topic-specific corpus. In this manner, domain-specific content may be classified into topics of interest. The ML-NLP classifier may classify content into the topics of interest.

Abstract: Methods and apparatuses are described for enhancing chatbot recognition of user intent through graph analysis. A computing device classifies user messages associated with a chat session as either comprehensible user messages that are mapped to a user intent or incomprehensible utterances that are not mapped to a user intent. The computing device arranges the comprehensible messages into first clusters and arranges the incomprehensible messages into second clusters. The computing device generates a first sub-graph for each first cluster and generates a second sub-graph for each second cluster. The computing device calculates a graph kernel matrix using the sub-graphs and trains a classification model using the graph kernel matrix. The computing device executes the trained classification model using the graph kernel matrix as input to generate a predicted intent identifier for the incomprehensible messages.

Abstract: Implementations relate to generating multi-modal response(s) through utilization of large language model(s) (LLM(s)). Processor(s) of a system can: receive natural language (NL) based input, generate a multi-modal response that is responsive to the NL based output, and cause the multi-modal response to be rendered. In some implementations, and in generating the multi-modal response, the processor(s) can process, using a LLM, LLM input (e.g., that includes at least the NL based input) to generate LLM output, and determine, based on the LLM output, textual content for inclusion in the multi-modal response and multimedia content for inclusion in the multi-modal response. In some implementations, the multimedia content can be obtained based on a multimedia content tag that is included in the LLM output and that is indicative of the multimedia content. In various implementations, the multimedia content can be interleaved between segments of the textual content.

Abstract: A generative cooperative network (GCN) comprises a dataset generator model and a learner model. The dataset generator model generates training datasets used to train the learner model. The trained learner model is evaluated according to a reference training dataset. The dataset generator model is modified according to the evaluation. The training datasets, the dataset generator model, and the leaner model are stored by the GCN. The trained learner model is configured to receive input and to generate output based on the input.

Abstract: Techniques for implementing a streaming remote procedure call (RPC) mechanism using distributed processing components of a system are described. A first processing component sends a connect message to a second processing component. Thereafter, the first processing component sends different instances of data to the second processing component as the different instances of data are determined by the first processing component. The second processing component performs at least some processes as the second processing component receives the different instances of data. After the first processing component sends all relevant data to the second processing component, the first processing component sends a commit message to the second processing component. Based at least in part on receiving the commit message, the second processing component determines finishes its processing, and sends result data to the first processing component.