International Business Machines Corporation

Gennaro A Cuomo

Victor S Moore

Erik John Burckart

Dinakaran B Joseph

Gari Singh

Brian Keith Martin

Gregory Louis Truty

Sandeep Kishan Singhal

Richard J Redpath

Binh Q Nguyen

Meeta Yadav

Erik Alan Daughtrey

Todd Eric Kaplinger

Andrew J Ivory

Aaron Kyle Shook

Roman Vaculin

Donna N Dillenberger

Rong Liu

Michael L Fraenkel

Jason Karl Yellick

Rishi Vaish

Meeta Vouk

John S Cox

Savio Rodrigues

Nataraj Nagaratnam

Donald Francis Ferguson

Hani Talal Jamjoom

Jim Alain Laredo

Asser Nasreldin Tantawi

Malgorzata Steinder

Matt Richard Hogstrom

Christopher Creighton Mitchell

Giovanni Pacifici

Michael Joseph Spreitzer

John Erik Wittern

Shriram Rajagopalan

Arjun Natarajan

Fenno F Heath, Iii

Daniel J Williams

Daniel Christopher Shupp

Christopher J Blythe

Richard M Poundstone

Lorenzo J De La Vega

Shikhar Singh

Goran D Zlokapa

Marco Barcella

Dinesh C Verma

David Bruce Lection

Blaine H Dolph

Anthony Joseph Nadalin

William Thomas Newport

Nikolaos Anerousis

Steven Dale Ims

Karen Ruth Kluttz

Peter George Capek

Timothy P Ellison

Gabriel Garcia Montero

Jay H Unger

Sarah D Redpath

Barry Mosakowski

Robert David Callaway

Wilfred Cadelina Jamison

Elizabeth Ann Black-Ziegelbein

Abbott Purdy Brush, Ii

Donald Robert Wood

Simon Phipps

Hung D Nguyen

Carmine Fred Greco

Shelley Lambert

Mark Anthony Parzygnat

Haechul Shin

Christopher Hay

Savio Rodriguez

Andrew Ivory

Computer-implemented methods for a large language model privacy preservation system. Aspects include receiving prompt data from a user device. Aspects further include generating pre-processed prompt data using the prompt data from the user device. Aspects also include identifying a category for the pre-processed prompt data using topic modeling. Aspects include generating normalized prompt data using the pre-processed prompt data. Aspects further include storing the category and the normalized prompt data.

Large language model privacy preservation system

An example operation may include one or more of receiving a request for blockchain information from a user device, acquiring blockchain data from a plurality of blockchains which are actively operating and available for joining, determining an amount of trust for each blockchain among the plurality of blockchains based on acquired blockchain data of the respective blockchain, and outputting a list identifying the plurality of blockchains where each blockchain on the list comprises a trust indicator indicating a determined amount of trust for the respective blockchain.

On-chain governance of blockchain

An approach is provided in which the approach collects distributed test results from multiple users, wherein at least one of the multiple users is an untrusted user. The approach aggregates the distributed test results in response to determining that each one of the distributed test results corresponds to the same system under test. The approach then presents the aggregated test results as a trusted test result.

Crowd-sourced QA with trusted compute model

A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include identifying a number of data parameters to extract from a blockchain based on a request for analytic data, creating one or more queries based on the data parameters, executing the one or more queries and retrieving the data parameters from the blockchain, identifying one or more permissions of a user account associated with the request for analytic data, and populating an interface with analytic figures based on the data parameters retrieved from the blockchain.

Automatic generating analytics from blockchain data

An example operation may include one or more of generating a data block for a hash-linked chain of blocks stored on a distributed ledger and accessible to a plurality of computing nodes of a blockchain network, storing governance policies within the data block, the governance polices governing interaction with the hash-linked chain of blocks, and transmitting the generated data block with the encoded governance policies therein to a plurality of peer nodes of the distributed ledger.

An example operation may include one or more of receiving a request to commit a blockchain request to a hash-linked chain of blocks stored on a distributed ledger, extracting governance policies which are encoded within a data block of the hash-linked chain of blocks on the distributed ledger, determining if the blockchain request satisfies the extracted governance policies of the hash-linked chain of blocks on the distributed ledger, and in response to the blockchain request satisfying the extracted governance policies, executing the blockchain request and storing the executed blockchain request within another data block of the hash-linked chain of data blocks on the distributed ledger.

An example operation may include one or more of receiving a request to modify a governance policy of a blockchain, identifying a principal identity that controls the governance policy, determining an allowable combination of signatures of the principal identity required for modifying the governance policy based on a graph data structure storing signature policies for endorsing modifications to governance policies, and modifying the governance policy of the blockchain based on the request in response to an allowable combination of signatures being received.

A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include identifying one or more analytic processes to process blockchain data, determining a primary type of data analytic to be performed by the one or more analytic processes, selecting a type of data store to use for performing the one or more data analytic processes based on the primary type of data analytic, accessing the blockchain data, applying the one or more analytic processes, and storing results of the applied analytic processes in a database, file or dashboard. The analytic data may be realized in any manner or preference requested.

Cognitive blockchain automation and management

A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include extracting obligation data from one or more of documents and rules, identifying transaction data from one or more blockchain transactions, creating one or more transaction contexts based on the transaction data, comparing the obligation data to the transaction data to identify whether the one or more transaction contexts are subject to the obligation data, and creating a notification including a current compliance status between the transaction contexts and the obligation data.

Cognitive regulatory compliance automation of blockchain transactions

Mobile enablement of a web site, in one aspect, may comprise separating the web application into a static content and a dynamic content, the dynamic content comprising one or more data sources from which to retrieve data at runtime of the web application; rendering the static content as one or more hypertext markup language pages with one or more links between the hypertext markup language pages converted to local links; changing one or more references to the dynamic content to representational state transfer requests; enabling the representational state transfer requests from said one or more hypertext markup language pages; and packaging said one or more hypertext markup language pages as the mobile application.

Mobile enablement of existing web sites

An example operation may include one or more of receiving a request to implement a modification to previously established governance policies of a blockchain, identifying one or more requirements for the modification based on the blockchain, determining whether the one or more identified requirements are satisfied based on signature data included within the request, and in response to the signature data satisfying the one or more requirements, transmitting the modification to an ordering node for inclusion within a data block of a hash-linked chain of blocks of the blockchain.

Embodiments relate to method products for publishing messages within a geographic area. Aspects include receiving a location from each of a plurality of user devices and creating a geo-hash tree based on the location of each of a plurality of user devices. Aspects also include receiving a message with the geographic area, computing a geo-hash grid for a region that includes the geographic area and identifying one or more nodes of the geo-hash tree that corresponds to the geo-hash grid. Aspects further include transmitting the message to one or more of the plurality of user devices associated with the one or more identified nodes.

Publishing messages based on geographic area

Embodiments relate to methods, systems and computer program products for publishing messages within a geographic area. Aspects include receiving a location from each of a plurality of user devices and creating a geo-hash tree based on the location of each of a plurality of user devices. Aspects also include receiving a message with the geographic area, computing a geo-hash grid for a region that includes the geographic area and identifying one or more nodes of the geo-hash tree that corresponds to the geo-hash grid. Aspects further include transmitting the message to one or more of the plurality of user devices associated with the one or more identified nodes.

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Durham, NC, United States of America

Gennaro A Cuomo