International Business Machines Corporation

Utpal Mangla

Mathews Thomas

Dinesh C Verma

Mudhakar Srivatsa

Satishkumar Sadagopan

Janki Y Vora

Amandeep Singh

Sharath Prasad Krishna Prasad

Gerald Coon

Steven Layne Canepa

Satish Sadagopan

Aaron K Baughman

Praveen Jayachandran

Pawan Raghunath Chowdhary

Raghu Kiran Ganti

Subil M Abraham

Franck Vinh Le

Jonathan Ian Settle

Tassanee Kraipon Supakkul

Dushyant K Behl

Mudit Verma

Saurabh Agrawal

Sagar Tayal

Joshua M Rosenkranz

Linsong Chu

Iranna Dharmaraya Ankad

Tuan Minh Hoang Trong

Sai Srinivas Gorti

Venkatesh Ashok Rao Rao

Davis Wertheimer

Using a probability distribution and a search result history, a probability of selecting a specified number of relevant samples and a specified number of irrelevant samples from a set of contents is computed, each content in the set of contents comprising a content copied to a first system clipboard of a first device. Using the probability distribution, each content in the set of contents is weighted. Using the weighted set of contents, a set of predicted searches is generated. The set of predicted searches is presented for selection responsive to an indication of intent to perform a search. A selected search within the set of predicted searches is caused to be performed.

Clipboard based search term prediction

Provided is a method for generating a personalized response to a user query. An omnichannel assistant receives a query from a user. The query is parsed to identify a user request. A user profile of the user is analyzed to determine one or more sources for responding to the query. The user profile includes a set of trusted sources for the user. Data for responding to the query is retrieved from the one or more sources. A channel for a response is selected based at least in part on the user profile. The response to the query is generated. The response is generated using the retrieved data, the selected channel, and the user profile. The response is then transmitted to the user.

Omnichannel virtual assistant using artificial intelligence

The present inventive concept provides for a method of unmanned machine synchronization using robotic sensing. The method includes generating at least one physical signal in the vicinity of at least one unmanned machine. The at least one generated physical signal is received by the at least one unmanned machine. At least one task is performed by the at least one unmanned machine based on the at least one received generated physical signal.

Unmanned machine synchronization using robotic sensing

A method, computer system, and a computer program product is provided for establishing a dynamically adaptive network firewall. A firewall model is established that identifies resources that can be used and a plurality of nodes that connect to one another to form a network. A set of external rules and policies are provided to each resource. The firewall implemented using the firewall model upon receiving of incoming data and upon traffic flow. The firewall expands or contracts the network by adding or removing resources according to work that needs to be performed. The work includes both tasks to be completed and efforts that has to be taken by the firewall to ensure security by preventing unauthorized access into the network.

Polymorphic dynamic firewall

A computer-implemented method, according to one approach, includes: receiving, from a remote location, a request to generate a unique equipment code identifying a device. Identifying characteristics of the device are determined, and a unique equipment code is generated. The unique equipment code is generated by applying policy based rules summarized in one or more predetermined information dependency graphs while combining at least some of the determined identifying characteristics in a specific order. Moreover, the combined identifying characteristics are converted into a corresponding alphanumeric string. The unique equipment code is assigned to the device and the unique equipment code is also transmitted to the remote location.

Managing distributed devices using unique codes

Embodiments related to using a foundational model for network packet traces. A technique includes receiving network traffic of a network and extracting features from the network traffic, the features having a function related to communications in the network. The technique includes generating tokens from the features, each of the features corresponding to a respective one of the tokens, training a machine learning model by inputting the tokens, the machine learning model being trained to output contextual embeddings for the tokens, and using the contextual embeddings to determine an anomaly in the network traffic.

Foundational model for network packet traces

A computer-implemented method for grouping devices in a massive multiple-input and multiple-output (MIMO)-based cellular network, in accordance with one embodiment, includes determining movement states of end devices in a cell of the massive MIMO-based cellular network, estimating payload requirements of the end devices, and grouping the end devices in a group based on the determined movement states and the estimated payload requirements.

Dynamic massive MIMO end device pairing based on predicted and real time connection state

A computer implemented method determines a placement of an application being added to a network. The method includes determining a logical-physical mapping for the application. Sub-graphs in the logical-physical mapping are identified. A stored application in a catalog of applications previously used in the network is located. The stored application includes one of the sub-graphs in the logical-physical mapping. An experiment is generated, performed by a computing device running a neural network model, using the sub-graphs. The experiment includes inducing a physical node mapping for the sub-graph. A cost function associated with a placement of the application being added to the network to one or more physical nodes in the induced physical node mapping is determined.

Generative experiments for application deployment in 5G networks

A method for determining a correlation of one or more events occurring in a plurality of nodes of a network includes accessing, by a computing device, address information associated with each of the plurality of nodes on the network. The computing device can further access one or more event IDs associated with one or more events occurring on the plurality of nodes. The computing device can further create an association the one or more events occurring on the plurality of nodes with related events occurring on others of the plurality of nodes, the association including the address information.

Topology-homogeneity for enriching event patterns in artificial intelligence operations

A computer implemented method performs data skipping in a hierarchically organized computing system. A group of processor units determines leaf node data sketches for data in leaf nodes in the hierarchically organized computing system. The leaf node data sketches summarize attributes of data in the leaf nodes. The group of processor units aggregates the leaf node data sketches at intermediate nodes in the hierarchically organized computing system to form aggregated data sketches at the intermediate nodes and retains data sketches received at the intermediate nodes from a group of child nodes to form retained data sketches. The retained data sketches are one of leaf node data sketches and the aggregated data sketches. The group of processor units searches the data using the retained data sketches and the data skipping within the hierarchically organized computing system in response to queries made to the intermediate nodes in the hierarchically organized computing system.

Hierarchical data skipping using data sketches

A computer-implemented method and a computer system establish network slices within a physical network having a plurality of network elements. The method includes receiving a request to instantiate a network slice at a network element. The method also includes determining a performance metric of the network element. The method further includes delaying instantiation of the requested network slice within the network element in response to determining that the performance metric of the network element is below a threshold. The method also includes instantiating the requested network slice within the network element in response to determining that the performance metric of the network element is at or above the threshold. Finally, the method includes deactivating the requested network slice in response to determining that the performance metric of the network element is below the threshold at a time subsequent to instantiating the requested network slice.

Delayed instantiation of network slices

Provided is a method for selecting a service provider for an application. The method includes detecting a plurality of available service providers for an application running on a computing device. The method further includes comparing service information for each of the plurality of service providers to a set of service provider selection factors for the application. The method further includes selecting a first service provider of the plurality of service providers to provide service for the application.

Mobile network switching

An approach for creating dynamic content. The approach receives advertiser data associated with activities of one or more advertisers and receives publisher data associated with activities of one or more publishers. The approach manages the one or more DSPs activities associated with the received advertiser data and publisher data. Furthermore, the approach manages the one or more SSPs activities associated with the received advertiser data, publisher data and the one or more DSPs activities and selects one or more advertisement for one or more website. Finally, the approach manages the one or more consumer behaviors associated with the selected one or more advertisement.

Dynamic content fulfilment associated with real time bidding

In an approach to dynamic network management based on user, device, application, and predicted network characteristics, one or more computer processors identify one or more network interfaces. The one or more computer processors determine one or more network performance parameters and capabilities of the identified network interfaces. The one or more computer processors determine a highest ranked network connection based on the determined network performance parameters and capabilities of the identified network interfaces. The one or more computer processors generate one or more network templates based on the determined highest ranked network connection and associated network performance parameters. The one or more computer processors apply the one or more generated network templates to a plurality of entities and devices.

Growing community of inventors

Toronto, Canada

Utpal Mangla