International Business Machines Corporation

Globalfoundries Inc.

Michele M Franceschini

Luis Alfonso Lastras-Montano

Ashish Jagmohan

Livio B Soares

John Peter Karidis

Mark N Wegman

Mayank Sharma

Moinuddin K Qureshi

Hillery C Hunter

Kyu-hyoun Kim

Charles Arthur Kilmer

Luis A Lastras

Blake G Fitch

Thomas Mittelholzer

Ibrahim M Elfadel

Todd Edward Takken

Daniel Christopher Worledge

Ruchir Puri

Rajesh Ramkrishna Bordawekar

Emrah Acar

Haifeng Qian

Stefanie Ruth Chiras

Bulent Abali

Matthew Joseph Breitwisch

John Alan Bivens

John Thomas Richards

John K Debrosse

Warren Edward Maule

Robert K Montoye

Oded Shmueli

Bipin Rajendran

Tin Kam Ho

Roger W Cheek

Lars Schneidenbach

Valentina Salapura

Chung H Lam

John Steven Dodson

Alper Buyuktosunoglu

Pradip Bose

Kevin Charles Gower

Frank David Ferraiolo

Sambit Sahu

Vijayalakshmi Srinivasan

John Kenneth DeBrosse

Peter Anthony Franaszek

Roman Vaculin

Kenneth Lee Wright

Jeffrey Haskell Derby

Chen-Yong Cher

Gary S Ditlow

Karthikeyan Shanmugam

Bernard Metzler

Janani Mukundan

Kanthi K Sarpatwar

Flavio Du Pin Calmon

Ken Inoue

Augusto J Vega

Moinuddin K A Qureshi

Bernaard Metzler

Chung Hon Lam

An example operation may include one or more of generating a hashed summary including hashes of one or more of a validation data set and hashes of data points chosen in previous iterations from producer nodes, and exposing the hashed summary to a plurality of producer nodes, receiving, iteratively, a plurality of requests from the plurality of producer nodes, respectively, where each request identifies a marginal value provided by a hash of a data sample available to a producer node, selecting a request received from a producer node based on a marginal value associated with the request, retrieving hashed data of the producer node associated with the selected request, and aggregating the hashed data of the producer node with the summary of hashes generated at one or more previous iterations to produce an updated summary, and storing the updated summary via a data block of a distributed ledger.

Artificial intelligence software marketplace

There is provided a method for managing a solid state storage system with hybrid storage technologies. The method includes monitoring one or more storage request streams to identify operating mode characteristics therein from among a set of possible operating mode characteristics. The set of possible operating mode characteristics correspond to a set of available operating modes of the hybrid storage technologies. The method further includes identifying a current operating mode from among the set of available operating modes responsive to the identified operating mode characteristics. The method also includes predicting a likely future operating mode responsive to variations in workload requirements to generate at least one future operating mode prediction. The method additionally includes controlling at least one of data placement, wear leveling, and garbage collection, responsive to the at least one future operating mode prediction.

Managing high performance storage systems with hybrid storage technologies

Embodiments relate to personalized low latency communications. A method may include receiving a description of content of a message, receiving recipient data corresponding to at least two possible recipients within a population of possible recipients, and selecting a relevant subpopulation of the population. The selecting may include, for each of the at least two possible recipients, ranking a strength of an indirect relationship between the description and the recipient data. The indirect relationship may be based on the description, the recipient data and at least one additional data source. The selecting may also include, for each of the at least two possible recipients, adding a possible recipient to the relevant subpopulation based on the ranking of the indirect relationship associated with the possible recipient. The method may further include initiating a two-way communication channel between a sender of the message and the relevant subpopulation.

Personalized low latency communication

A method and apparatus are provided for recommending concepts from a first concept set in response to user selection of a first concept Ci by performing a natural language processing (NLP) analysis comparison of vector representations of user concepts contained in written content authored by the user and candidate concepts in a first concept set to determine a similarity measure for each candidate concept, and to select therefrom one or more of the candidate concepts for display as recommended concepts which are related to the user concepts contained in written content authored by the user based on the similarity measure between each candidate concept and each user concept.

Content authoring

An example operation may include one or more of partitioning a data set from a data provider into a training data set and a test data set, exposing the training data set to a learning service provider while preventing the learning service provider from being able to access the test data set, wherein the preventing comprises encrypting the test data set and storing the encrypted test data set in an immutable ledger, receiving a learning model that is generated by the learning service provider based on the exposed training data set, executing the received learning model using the test data set as input to verify whether the learning model satisfies a predefined performance threshold, and in response to verifying the learning model satisfies the predefined performance threshold, outputting information about the verification to a computing node.

Learning service blockchain

Mechanisms, in a system comprising a host system and at least one accelerator device, for performing a concept analysis operation are provided. The host system extracts a set of one or more concepts from an information source and provides the set of one or more concepts to the accelerator device. The host system also provides at least one matrix representation data structure representing a graph of concepts and relationships between concepts in a corpus. The accelerator device executes the concept analysis operation internal to the accelerator device to generate an output vector identifying concepts in the corpus, identified in the at least one matrix representation data structure, related to the set of one or more concepts extracted from the information source. The accelerator device outputs the output vector to the host system which utilizes the output vector to respond to a request submitted to the host system associated with the information source.

Concept analysis operations utilizing accelerators

According to an aspect, searching, recommending, and exploring documents through conceptual associations includes a method for receiving a plurality of documents and extracting concepts from each of the documents. A degree of relation between each of the documents and concepts in a knowledge base is calculated. The method also includes, in response to receiving a query, determining one or more concepts from the query. For each of the concepts, a list of documents having a highest degree of relation to the concept is retrieved. The method also includes outputting a list that is responsive to the one or more retrieved lists.

System for searching, recommending, and exploring documents through conceptual associations

A shared ledger of transactions may be used for various purposes and may be later accessed by interested parties for ledger verification. Authenticity of transactions requires active measures to ensure transaction participants including parties to the transactions, observers to the transaction, etc., are providing accurate information for each transaction. One example method of operation may include one or more of identifying a set of participants to one or more transactions, transmitting a request from an initiating participant to enable each of the set of participants to generate local numbers based on a number source, forwarding the local numbers to one or more of the set of participants before expiration of a specified time interval, receiving the local numbers at the initiating participant, and generating a final number based on the local numbers received, so that after a last participant among the set of participants has forwarded the local number, none of the set of participants can obtain the final number until after a limited amount of time.

Scalable and distributed shared ledger transaction management

According to an aspect, automatically adding new concepts to a concept graph includes receiving a string of text, searching a corpus of data to locate additional text related to the string of text, and extracting concepts from the additional text. The extracted concepts include a subset of concepts in the concept graph. The adding new concepts also includes determining whether the string of text should be linked to an existing concept in the concept graph, performing the linking based on determining that the string of text should be linked to the existing concept in the concept graph and, based on determining that the string of text should not be linked to an existing concept in the concept graph, adding a new concept to the concept graph. The new concept is associated with the string of text.

Automatic new concept definition

A central processing unit system includes: a pipeline configured to receive an instruction; and a register file partitioned into one or more subarrays where (i) the register file includes one or more computation elements and (ii) the one or more computation elements are directly connected to one or more subarrays.

Local computation logic embedded in a register file to accelerate programs

According to an aspect, searching, recommending, and exploring documents through conceptual associations includes receiving a plurality of documents and extracting concepts from each of the documents. A degree of relation between each of the documents and concepts in a knowledge base is calculated. An aspect also includes, in response to receiving a query, determining one or more concepts from the query. For each of the concepts, a list of documents having a highest degree of relation to the concept is retrieved. An aspect also includes outputting a list that is responsive to the one or more retrieved lists.

According to an aspect, automatically linking text to concepts in a knowledge base using differential analysis includes receiving a text string and selecting, based on contents of the text string, a plurality of data sources that correspond to concepts in the knowledge base. In a further aspect, automatically linking the text to the concepts includes calculating, for each of the selected data sources, a probability that the text string is output by a language model built using the selected data source, calculating a probability that the text string is output by a generic language model, calculating link confidence scores for each concept based on a differential analysis of the probabilities, and creating a link from the text string to one of the concepts in the knowledge base. The creating is based on a link confidence score of the concept being more than a threshold value away from a prescribed threshold.

Automatically linking text to concepts in a knowledge base

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White Plains, NY, United States of America

Michele M Franceschini