Pwc Product Sales LLC

Pricewaterhousecoopers Llp

Thomas Joseph Foth

Joseph David Voyles

Kris Douglas Kersey

Ilana Alexandra Golbin

Jun Li

Yizhuo Zhang

Ryan Paul Beechey

Francis Njoroge Kahura

Shabbir Hussamuddin Alibhai

Joseph Michael Engel

Ernesto Valdes Forte

Christopher Ryan Tucci

Antoinette L Young

Walter Quesada

The present disclosure relates generally to storing computer models, and more specifically to a platform for achieving replicability of a computer model (e.g., a trained machine-learning algorithm) by storing and providing access to data associated with the computer model using an immutable and decentralized ledger system (e.g., a blockchain ledger) and a distributed database. An exemplary computer-enabled method for storing a computer model, the method comprises: receiving data associated with the computer model; generating one or more asset files based on the data associated with the computer model; generating one or more hash values corresponding to the one or more asset files; generating one or more of location trackers corresponding to the one or more asset files; generating a ledger entry comprising the one or more hash values and the one or more location trackers; and adding the ledger entry to a blockchain ledger.

Immutable and decentralized storage of computer models

Systems and methods for implementing an automation platform that is configured to analyze computing activities from a plurality of users so as to identify potential automation processes is provided. In one or more examples, a plurality of data collection agents are deployed across a plurality of computing devices and can be configured to collect and record activities performed on the computing device by one or more users of the computing devices. In one or more examples, each agent deployed on a computing device can be configured to transmit the collected data to a central server that can store the collected data in memory. The central server can be configured to collect the data from each agent and can be configured to apply one or more data science algorithms that can be configured to cluster various activities collected by the agents into groups for potential automation.

System and methods for implementing a computer process automation tool

Described are systems, methods, apparatuses, and computer program product embodiments for automatically processing intent-based spoken language for SLU. The disclosed solution uses a scale-free network structured conversational knowledge graph that stores nodes representative of actions, objects, and intent names and edges representative of relationships between the nodes. For all phrases (including a sentence) from the same intent, the system calculates a mean feature vector using a Universal Sentence Embedding (USE) model as a feature element. The system also employs a multi-step intent detection strategy. A graph query technique may be used to match all potential intent nodes from the trained knowledge graph. The system may compute a covariance matrix between the feature element of an input phrase and feature elements of all potential intents. The major component of the covariance matrix along with the maximum covariance may be used to determine the final intent.

Intent-based conversational knowledge graph for spoken language understanding system

Systems and methods for secure and accountable execution of computer scripts are disclosed. A system for validating an execution of a set of computer instructions may be configured to receive a first cryptographic hash, the first cryptographic hash corresponding to the set of computer instructions, to receive a second cryptographic hash, the second cryptographic hash corresponding to a runtime utility, wherein the runtime utility is configured to execute the set of computer instructions, to generate a ledger entry comprising the first cryptographic hash, the second cryptographic hash, and an indicator of success, and to add the ledger entry to a blockchain ledger, wherein the blockchain ledger is configured to receive the ledger entry from an authenticated node.

Secure and accountable execution of robotic process automation

Growing community of inventors

Melrose, MA, United States of America

Thomas Joseph Foth