Lenovo (singapore) Pte. Ltd.

International Business Machines Corporation

Lenovo (united States) Inc.

Lenova (singapore) Pte. Ltd.

Rod D Waltermann

Nathan J Peterson

John Carl Mese

Arnold S Weksler

Russell Speight VanBlon

Randall Scott Springfield

Howard J Locker

Suzanne Marion Beaumont

Mark Charles Davis

Daryl Carvis Cromer

Scott Edwards Kelso

David Carroll Challener

James Anthony Hunt

Timothy Winthrop Kingsbury

Joseph Michael Pennisi

Igor Stolbikov

David Rivera

Jonathan Gaither Knox

Scott Edward Kelso

Liang Chen

Richard Wayne Cheston

Joshua Neil Novak

Peter Hamilton Wetsel

Robert James Kapinos

Joseph Wayne Freeman

Axel Ramirez Flores

Grigori Zaitsev

Joaquin F Luna

Scott Wentao Li

Aaron Michael Stewart

Steven Dale Goodman

Antoine Roland Raux

Jun Li

Yi Zhou

Brian Alan Burdette

Bruce Douglas Gress

Hermann Franz Burgmeier

Philip Lee Childs

Bradley Park Strazisar

Karen Ruth Kluttz

Ratan Ray

Richard Paul Cornwell

Seiichi Kawano

Justin Tyler Dubs

Ryan Charles Knudson

Douglas Warren Robinson

Mark Evan Cohen

Nagananda Chumbalkar

Alfredo Zugasti

Jose Rodolfo Ruiz

Christopher Aaron Whitesock

Saba Shah

Veronika Stolbikova

Peter Hortensius

Michael Douglas Anderson

Erin Carolyn Solfiell Acquesta

Jefferson Logan Holt

Gary David Cudak

John Weldon Nicholson

Amy L Rose

James Gordon McLean

John Scott Crowe

Kenneth Scott Seethaler

Xin Feng

Neal Robert Caliendo, Jr

Christopher Miles Osborne

Robert Bowser

Liang Tang

Carlos Munoz-Bustamante

Jason M Grimme

Yasushi Tsukamoto

Ernest Nelson Mandese

Jeffrey Mark Estroff

Michael Gerard Demeter

David Andrew Sawin

Rodrigo Felix De Almeida

Isaac Karpel

Michael William Stuart Ripp

Timothy Jones

Masahiko Nomura

Mei-Wen Sun

Paul Plaskonos

Goran Hans Wibran

Ephraim D Starr

Alfredo Zugasti Hays

Ke Ke

John Hancock Nicholson, Iii

Norman Arthur Dion, Ii

Chunling Han

Kushagra Jindal

Charles Burnham Oxrieder

Xiaohua Xu

Rodrigo Almeida

Joseph Bryan Morris

James Alan LaCroix

Rachael Marie Luna

Stacy John Cannady

Song Chunyu

Fred W F Holt, Jr

Randall Scott Springrield

Methods, apparatus, and computer program products for adding devices to a network via a zero-knowledge protocol are disclosed. One method includes implementing, by a processor, a zero-knowledge protocol configured to establish digital trust relationships between the processor and computing devices attempting to join a network and adding each computing device to the network that successfully establishes a respective digital trust relationship with the processor via the zero-knowledge protocol. Apparatus and computer program products that include hardware and/or software that can perform the methods for adding devices to a network via a zero-knowledge protocol are also disclosed herein.

Adding devices to a network via a zero-knowledge protocol

Methods, apparatus, and computer program products for computing device digital certificates that include a geographic extension are disclosed herein. One method includes a processor managing a digital certificate for a first computing device, in which the digital certificate includes a geographic extension, and populating the geographic extension with a distance value that enables the digital certificate to be validated via the populated geographic extension. Apparatus and computer program products that include hardware and/or software that can perform the methods for computing device digital certificates that include a geographic extension are also disclosed herein.

Computing device digital certificates that include a geographic extension

An apparatus includes a processor and a memory that stores code executable by the processor. The code is executable by the processor to receive a request at a first device to execute a machine learning workload for the first device, dynamically determine at least one characteristic of the first device that is related to execution of the machine learning workload, dynamically determine at least one characteristic of a second device that is related to execution of the machine learning workload, and select one of the first and second devices to execute the machine learning workload in response to the at least one characteristic of the selected one of the first and second devices being more suitable for execution of the machine learning workload than another of the first and second devices.

Dynamic client/server selection for machine learning execution based on current performance characteristics

An electronic device is provided that includes a memory storing program instructions, and one or more processors. The one or more processors, when executing the program instructions, are configured to generate an agent public key, and generate a key font based on the agent public key. The one or more processors are also configured to communicate the key font to an operating system, and obtain a key message based on the key font from an application. The one or more processors are also configured to respond to the key message on a bus based on the key message.

Method and device for securing a communication path

An electronic device is provided that includes a display, a processor, and a data storage device having executable instructions accessible by the processor. Responsive to execution of the instructions, the processor displays a user desktop related to a user, creates a virtual meeting that is configured to be attended by communication through a network by at least one network based electronic device, generates a shared desktop related to the virtual meeting that is configured to be shared with the at least one network based electronic device via the network, and displays the shared desktop during the virtual meeting.

Method and system for content management for a virtual meeting

Systems, apparatus, and methods that can elect a broker on a Message Queuing Telemetry Transport (MQTT) bus are disclosed. One system includes an MQTT bus and a set of client devices on the MQTT bus. Each client device maintains a set of attributes for each other client device and casts one or more votes for a particular client device on the MQTT bus to elect the particular client device as a new broker on the MQTT bus in response to a current broker on the MQTT bus becoming unavailable. The votes cast for the particular client device are based on a first value corresponding to one or more attributes for the particular client device relative to respective second values to the corresponding attribute(s) for each of the other client devices on the MQTT bus as calculated by each respective client device on the MQTT bus.

Systems, apparatus, and methods for electing a new broker for a channel on an MQTT bus

One embodiment provides a method, including: receiving, at a server from a device, a request for device authentication across an unsecure network, the request including a device registration token; generating, at the server, a shared registration key utilizing the device registration token; verifying, at the server, the device registration token by comparing the device registration token to a function of the shared registration key; and producing, at the server and responsive to verifying the device registration token, a one-time activation token and sending the one-time activation token to the device. Other aspects are described and claimed.

Device authentication across unsecure network

Apparatuses, methods, systems, and program products are disclosed for distributed license encryption and distribution. An apparatus includes a processor and a memory that stores code executable by the processor. The code is executable to select a license token from a pool of available license tokens associated with available digital licenses in response to a license request from a first device. The license token includes information identifying second devices where segments of a digital license associated with the license token are stored. The segments are encrypted using encryption keys for one or more participants. The code is executable to re-encrypt the segments of the digital license for the selected license token using an encryption key for the first device and send the license token to the first device where it is used to request the segments from the second devices, decrypt the segments, and reconstruct the digital license.

Distributed license encryption and distribution

A system includes a binary tree having leaf hashes. The leaf hashes include a device privacy protected index and a set of zero-knowledge commitments relating to a computer device. The system calculates the device privacy protected index using a verifiable random function such that a device entity path in the binary tree cannot reveal any information about any other device in the binary tree, and associates the set of zero-knowledge commitments with the device privacy protected index. The system then generates a privacy-protected attestation for the computer device using the device privacy protected index and the set of zero-knowledge commitments.

Privacy protecting transparency tree for device attestation

One embodiment provides a method, including: obtaining a dataset for generation of an outcome using a plurality of artificial intelligence models; classifying, using another artificial intelligence model and before employing the plurality of artificial intelligence models, the dataset into a feature-space; and employing a subset of the plurality of artificial intelligence models on the dataset, wherein the subset is selected based upon the classification of the dataset. Other aspects are described and claimed.

Classifying a dataset for model employment

An embodiment provides a method, including: obtaining, using a processor, contextual information relating to an information handling device; adjusting, using a processor, an automated speech recognition engine using the contextual information; receiving, at an audio receiver of the information handling device, user speech input; and providing, using a processor, recognized speech based on the user speech input received and the contextual information adjustment to the automated speech recognition engine. Other aspects are described and claimed.

Adjusting speech recognition using contextual information

An approach is provided that receives a password that corresponds to a user identifier. A number of hashing algorithms are retrieved with the specific hashing algorithms that are retrieved being based on the received user identifier. The password is hashed using each of retrieved hashing algorithms resulting in a number of hash results. The hash results are combined with the combining of the hash result eventually resulting in a combined hash result. An expected hash result that corresponds to the user identifier is retrieved and compared to the combined hash result. The password is verified based on the results of the comparison.

Password protection based on Merkle tree proofs

An approach is provided that uses multiple hashing algorithms to verify a password. The approach receives a password that corresponds to a user identifier. A set of hashing algorithms are retrieved with the retrieved set based on the received user identifier so that different user identifiers utilize different sets of hashing algorithms. Hashing the password using each of the hashing algorithms included in the set of algorithms with the hashing resulting in a hash result. An expected hash result that corresponds to the user identifier is retrieved and the approach then verifies the received password by comparing the hash result to the first expected hash result.

Password protection using chain of random hashing functions

An aspect provides a method, including: receiving, at an input component of an information handling device, user input comprising one or more words; identifying, using a processor of the information handling device, an emotion associated with the one or more words; creating, using the processor, an emotion tag including the emotion associated with the one or more words; storing the emotion tag in a memory; analyzing one or more emotion tags; and modifying an operation of an application based on the analyzing. Other embodiments are described and claimed.

Preserving emotion of user input

An embodiment provides a method, including: receiving, at an audio receiver of an information handling device, user voice input; identifying, using a processor, words included in the user voice input; determining, using the processor, one of the identified words renders ambiguous a command included in the user voice input; accessing, using the processor, context data; disambiguating, using the processor, the command based on the context data; and committing, using the processor, a predetermined action according to the command. Other aspects are described and claimed.

Using context to interpret natural language speech recognition commands

Growing community of inventors

Rougemont, NC, United States of America

Rod D Waltermann