Wells Fargo Bank, N.a.

Bank of America Corporation

Naveen Gururaja Yeri

Ashutosh Verma

Rameshchandra Bhaskar Ketharaju

Vinothkumar Venkataraman

Paul Davis

Dipanjan Deb

Yang Yang

David Joa

Timothy J Bendel

Amit Agarwal

Abhishek Kumar

Thayer S Allison

Yanghong Shao

Manesh Saini

Hasan Adem Yilmaz

Matt Hord

Sitara Kumbale

Vinayak Sodar

Manak Suri

Mayuri Chaubey

Rahul Ignatius

Srimoyee Duttagupta

Michelle Sunna Nowe

Alan On Yau

Pranshu Sharma

Dipan Banerjee

Hemalatha Ac

Agus Sudjianto

Manpreet Singh

David Neil Joffe

William Anthony Nobili

Arun Pinto

Ananth Kendapadi

Timothy John Breault

Aijun Zhang

Zhe Zhang

Benhong Zhang

Tyler Case

Nihar Swain

Divakar Vijayan

Shitiz Gupta

Deepak Verma

Jie Chen

Harsh Singhal

Sandi Setiawan

Jade Michelle Le Vo-Dinh

Vinoth Venkataraman

Srihari Rao Gatpa

Kaloyan Mihaylov

Bibhudatta Jena

Michael Chorba

Hungien Wang

Daniel Hudson

Vikas Mishra

Jocelyn Sikora

Ramesh Babu

Kiran Vuppu

Debashis Ghosh

Vivek Shyamlal Sharma

Ramesh Kempanna Babu

Shuvam Sengupta

Meghan Alita Steach

Arya Kumar Vedabrata

Ramesh Babu Sarvesetty

Elaine C Marino

Anusha Yenduri

Renuka Mannem

Saurav Kumar

Mayank Kumari

Mehdi Allahyari

Christopher M Mahler

Ayat Abuagla

Jason R Beene

Sandeep Pradhan

Brandon P Castaing

Thejas M Bhat

Shuchun Wang

Chandrashekar Katuri

Parul Bajaj

Kunal Makin

Ulrich A Bruns

John Delmonico

Shelly X Ennis

Ruilong He

Glenn B Jones

WeiCheng Liu

Julia A Kosheleva-Coates

Hungjen Wang

Lalitha Lakshmipathy

Tapan Totla

Fordjour Y Kyei

Janaki R Akella

Narender Dhiman

Ramamohan S

Kevin J Hale

Systems, apparatuses, methods, and computer program products are disclosed for simultaneous multifactor authentication. An example method includes simultaneously receiving, by communications hardware and in response to a first authentication request, a plurality of authentication factors associated with an individual via a plurality of channels. The example method further includes performing, by an authentication engine, a verification operation that evaluates the plurality of authentication factors in parallel. The example method further includes authorizing, by the authentication engine, the one or more actions based on a successful outcome of the verification operation.

Systems and methods for simultaneous multifactor authentication

Systems, apparatuses, methods, and computer program products are disclosed for generation of a user biosignature. An example method includes extracting user data from a data environment, wherein the user data is associated with a user. The example method further includes analyzing the user data, wherein the user data comprises one or more data types, wherein the one or more data types comprise at least metadata and biometric data. The example method further includes determining a character classification associated with each of the one or more data types based on the analyzed user data, wherein the character classification comprises a primary character classification and a secondary character classification. The example method further includes generating a user biosignature based on the determined character classification, and outputting the generated user biosignature.

Systems and methods for generating a blended user biosignature using multimodal AI

An example method includes receiving and preprocessing a query request prior to execution of a query. Through preprocessing, a probability that execution of the query would yield a result set similar to at least a portion of results stored in a repeated query result repository is obtained. In response to the probability satisfying a probability threshold, a portion of results is retrieved from the repository. The example method further includes causing transmission of a response to the query request, the response comprising the portion of results.

Systems and methods for reducing computational resource usage in a query-based data access system via a repeated query results repository

Quality associated with an interpretation of data captured as unstructured data can be determined. Attributes can be identified within the unstructured data automatically. Subsequently, sentiment associated with each of the attributes can be determined based on the unstructured data. Correctness of the unstructured data, and thus the interpretation, can be assessed based on a comparison of the attribute and associated sentiment with structured data. A quality score can be generated that captures the quality of the data interpretation in terms of correctness and as well as results of another analysis including completeness, among others. Comparison of the quality score to a threshold can dictate whether or not the interpretation is subject to further review.

Data interpretation analysis

Systems, apparatuses, methods, and computer program products are disclosed for managing operation of a distributed system that provides computer-implemented services. An example method includes collecting, via an out-of-band stream, sensor data from a plurality of temperature sensors positioned to infer temperatures of components of a distributed system. The example method further includes inferring, using the inferred temperatures, power consumption rates for performing respective actions with each of the components. The method further includes obtaining an action request and selecting, based on the inferred power consumption rates, a particular component of the components to perform an action to service the action request, the selection being made with a preference to reduce power consumption for performance of the action. The method further includes performing, with the particular component, the action to service the action request, the action resulting in updated computer-implemented services being provided by the distributed system.

Systems and methods for managing power consumption of a distributed system

Embodiments are generally directed to techniques for query-based binarized point decisions, such as with a system that can provide end-to-end decision making support. Some embodiments are particularly directed to a system that makes point decisions, with traceable reasoning, for queries while factoring in a variety of influences. In many embodiments, the traceable reasoning may refer to the generation and collection of metadata associated with various aspects of the decision making process. For example, the metadata may include, or be used to create, a decision lineage and/or reasoning summary that is generated for each point decision. Some embodiments may ensure various influences do not derail the query from the overall objective. In several such embodiments, the point decisioner may confirm or deny that a decision was made with aspect to a certain objective.

Query-based binarized point decisions

Techniques are described for generating a set of emotion factor values using one or more machine learning models for customer communications. For example, a computing system includes one or more processors in communication with a memory. The one or more processors are configured to receive communication data of a current communication associated with a customer, apply the communication data to an emotion-based indexer as input wherein the emotion-based indexer includes a set of machine-learning models for a set of emotion factors, generate as output from the emotion-based indexer a set of emotion factor values for the current communication wherein each emotion factor value indicates the measure of a particular emotion factor in the current communication, apply the set of emotion factor values to an emotion classification model, and classify the current communication into an emotion state based on the set of emotion factor values.

Emotion analysis using deep learning model

Systems, apparatuses, methods, and computer program products are disclosed for generating a predicted effect for a target cluster in response to a synthetic stimulus. An example method includes receiving a synthetic behavior prediction request and generating a plurality of clusters, wherein each cluster is associated with a corresponding centroid position. The method further includes selecting the target cluster from the plurality of clusters and generating the predicted effect for the target cluster in response to the synthetic stimulus based on the centroid position corresponding to the target cluster. The method further includes providing a predicted effect notification.

Generative artificial intelligence for generating predicted effects in response to a synthetic stimulus

Systems, apparatuses, methods, and computer program products are disclosed for predicting an emotion in real-time based on a multimodal input including at least (i) an amount of keystrokes over a period of time and (ii) text. An example method may include receiving, by a communications circuitry, a multimodal input from a user including at least (i) an amount of keystrokes over a period of time and (ii) text. The example method may further include generating, by a trained machine learning model of an emotion prediction circuitry and using the multimodal input, an EmotionPrint for the user. The example method may finally include determining, by the emotion prediction circuitry and using the EmotionPrint, a next action.

Systems and methods for predicting an emotion based on a multimodal input

Systems, apparatuses, methods, and computer program products are disclosed for predicting an entity and intent based on captured speech. An example method includes capturing speech and converting the speech to text. The example method further includes causing generation of one or more entities and one or more intents based on the speech and the text. The example method further includes determining a next action based on each of the one or more entities and each of the one or more intents.

Systems and methods for determining a next action based on entities and intents

An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes scheduling, by context analysis circuitry and based on the occurrence of the triggering condition, retraining of a model. The example method also includes generating, by data grafting circuitry and in response to scheduling the retraining of the model, a context-relevant training data set based on a target context vector. The example method also includes retraining, by model training circuitry, the model using the context-relevant training data set to mitigate deterioration of performance of the model.

Systems and method for data grafting to enhance model robustness

Systems and methods for data grafting to enhance model robustness

Computer-automated systems and methods that retain requests for information until documents containing the information are released at a later date. Release of the documents can trigger natural language understanding of the documents to be automatically performed and responses to the requests to be generated. In some examples, the responses include recommendations for taking or not taking financial actions relating to the request and the information.

Responses to requests for information

Systems, apparatuses, methods, and computer program products are disclosed for mitigating deterioration of modeling system performance. An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes determining, by context analysis circuitry and in response to detecting the occurrence of the triggering condition, a destination modeling solution based on a regime strategy for the modeling system. The example method also includes switching, by regime deployment circuitry and based on the regime strategy, from a source modeling solution to a destination modeling solution.

Systems and methods for using regime switching to mitigate deterioration in performance of a modeling system

Systems, apparatuses, methods, and computer program products are disclosed for measuring employee engagement. An example method includes receiving, by communications circuitry, an exogenous event report and identifying, by a frequency modulator and based on the exogenous event report, a frequency at which to deliver an employee survey to an employee. The example method further includes causing, by an engagement engine, delivery of the employee survey to the employee based on the identified frequency and receiving, by communications circuitry, a response to the employee survey. The example method further includes storing the received response in a memory as a measure of employee engagement.

Systems and methods for measuring employee experience

Growing community of inventors

Bengaluru, India

Naveen Gururaja Yeri