International Business Machines Corporation

Amazon Technologies, Inc.

Abdigani Mohamed Diriye

Komminist S Weldemariam

Shikhar Kwatra

Michael S Gordon

Sushain Pandit

Clifford A Pickover

Heike E Riel

Paul N Krystek

Jaime Lorenzo Trueba

Patryk Golebiowski

Piotr Jozwiak

Itzhack Goldberg

Jonathan Lenchner

Praveen Jayachandran

Ashley D Gritzman

Andrew Kinai

Felix Bonard Kwizera

Isaac Markus Serfaty

Peninah Mugure Waweru

Lola Aleru

Samuel Maina

An example operation may include one or more of connecting, by a migration server, to a legacy system configured to store legacy data, identifying, by the migration server, artifacts of the legacy system subject to a migration to a blockchain, generating, by the migration server, transactions that correspond to the artifacts of the legacy system, mapping the artifacts of the legacy system to artifacts of the blockchain based on the transactions, and executing, by the migration server, a smart contract to migrate the legacy data corresponding to the mapped artifacts into the blockchain.

Migration of a legacy system

A speech-processing system receives input data corresponding to one or more characteristics of speech. The system determines parameters representing the characteristics and, using the parameters, encoded values corresponding to the characteristics. A speech synthesis component of the speech-processing processes the encoded values to determine audio data including a representation of the speech and corresponding to the characteristics.

Synthetic speech processing

Embodiments of the present invention include a crowdfunding platform comprising one or more computer systems, one or more memories, and one or more central processing units (CPUs). The crowdfunding platform has one or more alternative interfaces to one or more alternative networks. The alternative networks are not capable of operating directly with the Internet. There are also one or more Internet interfaces to the Internet. A crowdfunding platform receives information about a crowdfunding project from one of the alternative interfaces, processes the information into processed information, sends the processed information over one of the Internet interfaces. Further, the crowdfunding platform receives Internet information over one of the Internet interfaces, translates the Internet information into transformed information, and sends the transformed information over one of the alternative interfaces.

Crowdfunding endorsement using non-internet enabled devices

Methods and systems for buyback provisioning. A risk level for each of a plurality of items at risk of losing market value is computed and the plurality of items at risk of losing market value are differentiated based on the corresponding risk levels. An identity of candidate substitute items is learned by communicating with a distribution system and one or more of the candidate substitute items to exchange for one of the plurality of items are identified based on one or more contextual factors. An exchange of the item and at least one of the candidate substitute items is facilitated, the facilitating comprising highlighting the item on a graphical user interface to indicate that the item is losing value or is at risk of losing value.

Buyback provision mechanism

Methods and systems for culturally sensitive operation of an electronic device. One or more cultural characteristics (CC) related to use of a communication device are determined and one or more cultural characteristics rules are learned. An amelioration action is triggered based on use of the communication device, the one or more cultural characteristics rules, and a confidence/risk level.

Communication devices

Systems and methods for reminding a user or a group of users about one or more items related to an upcoming event. The upcoming event is identified based on user data and a context for determining a list of items useful for the upcoming event is obtained. The list of items for the identified upcoming event is determined, using the context, and item reminder enhancement factors are determined in response to the upcoming event and the determined list of items. Content selection models are determined based on the context, the user data, and the item reminder enhancement factors. Conversational content for engaging the user or group of users is generated by applying the content selection models to a plurality of potential content. A conversation trigger signal is determined, and the conversational content is presented to the user via a computing device in response to receiving the conversation trigger signal.

Contextualized item reminder assitance

A method includes obtaining a user profile that includes a user's affinities to each of a plurality of micro-tasks; estimating a duration of down-time for the user; estimating task selection factors responsive to the user profile and to the estimated duration of down-time; generating a list of micro-tasks responsive to the task selection factors; ranking the list of micro-tasks according to the user's affinities; partitioning the down-time according to the ranked list of micro-tasks; and presenting one or more of the micro-tasks to the user, according to the partitioning of the down-time, by altering operation of a user device.

Facilitating micro-task performance during down-time

A social media control method, system, and computer program product, include detecting a contextual meaning of a content of a third-party post on a user's social media account, classifying the content into user-defined categories based on an overlap between the contextual meaning and the user-defined categories, identifying an undesired piece of information from the content, identifying a trusted online friend within a social media circle of the user, and providing a one-time access control to the identified trusted online friend to rectify the undesired content in the third-party post.

Social media control provisioning based on a trusted network

An exemplary method includes obtaining a training set of code data that includes deprecated code; training a multi-layer neural network on the training set of code data to predict usage events for the deprecated code; predicting usage events for the deprecated code, in a first set of code data, using the trained multi-layer neural network; estimating a value of risk associated with the deprecated code in response to the predicted usage events; comparing the estimated value of risk to a threshold; and, in response to the estimated value of risk exceeding the threshold, implementing an ameliorative action regarding the deprecated code.

Predictive code clearance by a cognitive computing system

A smart lens system may include a hardware processor coupled to a smart contact lens, which may include a microprocessor, an image capturing sensor, and a wireless communication interface. The smart lens system may determine reading factors associated with a user with respect to the user reading content item, based on data related to the user's physiological movements captured by the smart contact lens. The reading factors may include a user's cognitive state determined at least from analyzing data representing the user's physiological movements. Responsive to determining that the user's cognitive state is above a threshold value, the smart lens system may generate an assistive action associated with the content item and transmit a signal to at least one assistive device to perform the assistive action. The assistive device performs the assistive action responsive to receiving the signal.

Smart contact lens system with cognitive analysis and aid

A computer-implemented method of controlling a computer system is provided. In particular, the method relates to controlling of a touchscreen of the computer system in order to display contextually relevant user interface objects on a graphical display of the touchscreen. The computer system includes a processor and the touchscreen includes a touch sensor as an input device. The method includes determining, by way of a user context determination module, a user context of at least one user of the computer system, selecting, using an icon selection module, one or more user interface objects which are contextually relevant to the determined context of the user, and displaying, using the graphical display of the touchscreen, the one or more user interface objects selected by the icon selection module. Determining the user's context may include monitoring the user's behavior, mood or cognitive state.

Method and system for context-driven displaying of shortcuts on touchscreen

A volume and speech frequency level adjustment method, system, and computer program product include learning a characteristic of at least one of audio volume and speech frequency from a conversation, detecting a contextual characteristic of an ongoing conversation and an interaction of a user with a device, determining a cognitive state of the user in relation to the ongoing conversation as a function of at least one of the contextual characteristic of the volume or the speech frequency, and a user interaction pattern with a conversation device, and dynamically adjusting audio levels of the ongoing conversation for the user based on the function.

Cognitive volume and speech frequency levels adjustment

A conversation attendant and assistant platform implements a method of receiving by a computer a plurality of messages in a plurality of conversations via one or more messaging applications. The platform tags each message of the plurality of messages with a message cohort and an amelioration action, and assigns a risk to the given message based on the message cohort. The platform also determines a user context of a user of the computer, and, in response to factors including the user context and the risk, assigns a concern level to the given message. The platform accumulates and summarizes the given message along with other messages in a conversation of the given message. In case the concern level exceeds a threshold, the platform selects one or more delivery channels for surfacing a summary of the conversation and surfaces the summary via the one or more delivery channels.

Conversation attendant and assistant platform

A method includes producing a user profile in response to user data; obtaining context for estimating the duration of a down-time; estimating the duration of the down-time; determining experience enhancement factors in response to the user profile and the estimated duration of the down-time; determining an activity selection model in response to the context, the user data, and the experience enhancement factors; generating personalized engaging activities by applying the activity selection model to a plurality of potential activities; partitioning the estimated duration of the down-time into segments; sequencing the personalized engaging activities to fit into the segments; and presenting the personalized engaging activities to the user via a computing device. A computer readable medium embodies instructions for the method and an apparatus including a processor is operative to facilitate the method.

Growing community of inventors

Nairobi, Kenya

Abdigani Mohamed Diriye