Abstract: A hybrid knowledge representation is searched for a machine learning component corresponding to a search query. The hybrid knowledge representation may be structured as nodes representing machine learning workflow components and edges (e.g., links) connecting the nodes based on relationships between the nodes. Responsive to finding the machine learning component in the hybrid knowledge representation, the machine learning component is returned. Responsive to not finding the machine learning component in the hybrid knowledge representation, the hybrid knowledge representation is searched for machine learning model fragments associated with building the machine learning component, generating a new machine learning component by combining the machine learning model fragments and returning the new machine learning component.

Abstract: Document retrieval through assertion analysis on entities and document fragments is disclosed. A document is received. Logical structures and entities are extracted from the document by parsing the document. For an entity in the extracted entities, an object representing the entity is created, an assertion made in the document associated with the entity is determined, and the assertion is linked to the object representing the entity. A logical structure from the extracted logical structures and content of the logical structure containing the assertion are identified and linked to the object representing the entity.

Abstract: Systems and methods are described for mapping input devices in real time. The method may include controlling a camera to capture a plurality of images, performing object recognition on the images to identify a plurality of objects, determining properties for each identified object that enable the corresponding object to provide spatial data and interaction data of a preferred input device, ranking the objects according to the determined properties, presenting the identified objects in an order corresponding to the rank that enables a user to select one of the presented objects, tracking the selected object and a human being, generating spatial data and interaction data from a result of the tracking, and providing the generated spatial data and interaction data to a computer to emulate the events of the preferred input device.

Abstract: An ore content prediction system is provided. The system receives structured geological data that is derived based on spatial geological information that is associated with an input region. The received structured geological data includes a plurality of multidimensional tensors that are derived from spatial geological information of a plurality of sub-regions of the input region. The spatial geological information includes one or more types of data. The system trains a prediction model to produce a prediction output based on an average grade of an ore of a target mineral type at a target region by using the received structured geological data.

Abstract: Methods, systems, and computer program products for automatically creating narrative visualizations from audiovisual content according to pattern detection supported by cognitive computing techniques are provided herein.

Abstract: A method and system of dynamically adapting a streaming media content are provided. A user device determines a class of each member of its audience. Streaming media content is received. The streaming media content is monitored to dynamically determine a rating of each segment of the streaming media content. For each segment of the streaming media content, upon determining that a rating of a segment is above a class of a most restricted member of the audience, one or more portions of the segment are adapted to alter the rating of the segment to the class of the most restricted member of the audience. The segment of the media content is then presented on a user interface of the user device.

Abstract: A plurality of datasets may be received. Multiple instances of a machine learning algorithm may be run to create corresponding multiple machine learning models trained for a specific task in a given domain. Each of the multiple instances may use a different subset of the plurality of datasets in training the corresponding machine learning model. The multiple machine learning models may be run with input data. The multiple machine learning models produce corresponding multiple outcomes. A candidate machine learning model may be determined based on comparing each of the multiple outcomes with ground-truth output. A value associated with the different subset of the plurality of datasets may be determined based on comparing of each of the multiple outcomes with ground-truth output. A smart contract may be created which may include the value and the different subset of the plurality of datasets. The smart contract may be recorded in a blockchain.

Abstract: Automatically identifying speakers in real-time through media processing with dialog understanding. A plurality of audio streams may be received, an audio stream representing a speech of a participant speaking during an online meeting. A voice characteristic of a voice corresponding to the speech of the participant in the audio stream may be determined. The plurality of audio streams may be converted into text and a natural language processing may be performed to determine content context of the dialog. The natural language processing infers a name to associate with the voice in the audio stream based on the determined content context. A data structure linking the name with the voice may be created and stored in a knowledge base. A user interface associated with the online meeting application is triggered to present the name or identity of the speaker.

Abstract: A computer-implemented method includes a step of generating a clipped image by applying a display map to a feedback image of a plurality of display devices that display a set of training frames. The method also includes a step of learning a first set of rules that transform the clipped image to match the set of training frames and a step of generating a rendered surface by applying the display map to an input image. Additionally, the method includes a step of generating a set of render frames by applying the first set of rules to the rendered surface and a step of sending the set of render frames to be displayed by the plurality of display devices.

Abstract: A computer-implemented method includes a step of generating a clipped image by applying a display map to a feedback image of a plurality of display devices that display a set of training frames. The method also includes a step of learning a first set of rules that transform the clipped image to match the set of training frames and a step of generating a rendered surface by applying the display map to an input image. Additionally, the method includes a step of generating a set of render frames by applying the first set of rules to the rendered surface and a step of sending the set of render frames to be displayed by the plurality of display devices.

Abstract: Method and apparatus for monitoring collaboration parameters and maintaining user profiles using cognitive computing techniques are provided. The method includes receiving a domain for a first collaborative session, and retrieving a plurality of trait profiles associated with potential participants. The method further includes determining a subset of trait profiles based in part on comparing each respective trait profile with the rest of the trait profiles, and providing the subset of trait profiles. Additionally, the method includes receiving an indication that the subset of trait profiles is acceptable, and a request to initiate the first collaborative session with participants corresponding to the subset of trait profiles.

Abstract: Methods, systems, and computer program products for automatically creating narrative visualizations from audiovisual content according to pattern detection supported by cognitive computing techniques are provided herein.

Abstract: A system, product, and method including automatically performing extraction of slides from multimodal content, performing object extraction from each of the slides, allowing object substitution through semantics and concepts of the objects extracted, processing audio synchronized with the slides enriched with cognitive computing, search engine, and knowledge base, to provide annotations of the slides, processing the audio synchronized with the object being presented in each slide to enhance semantics and understanding, and curating for each step with human-machine interaction to provide a learning process by the system.

Abstract: A computer-implemented method includes a step of generating a clipped image by applying a display map to a feedback image of a plurality of display devices that display a set of training frames. The method also includes a step of learning a first set of rules that transform the clipped image to match the set of training frames and a step of generating a rendered surface by applying the display map to an input image. Additionally, the method includes a step of generating a set of render frames by applying the first set of rules to the rendered surface and a step of sending the set of render frames to be displayed by the plurality of display devices.

Abstract: A computer-implemented method includes a step of generating a clipped image by applying a display map to a feedback image of a plurality of display devices that display a set of training frames. The method also includes a step of learning a first set of rules that transform the clipped image to match the set of training frames and a step of generating a rendered surface by applying the display map to an input image. Additionally, the method includes a step of generating a set of render frames by applying the first set of rules to the rendered surface and a step of sending the set of render frames to be displayed by the plurality of display devices.

Abstract: A method for classifying content includes receiving the content; identifying a ratings jurisdiction and regime for the content; accessing a knowledge base for a trained model according to the ratings jurisdiction and regime; classifying the content by testing the content against the trained model; and providing to a user the classification of the content. Optionally, the method includes receiving, from the user, a classification feedback of the content; and updating the trained model responsive to the content and the classification feedback.

Abstract: A method for classifying content includes receiving the content; identifying a ratings jurisdiction and regime for the content; accessing a knowledge base for a trained model according to the ratings jurisdiction and regime; classifying the content by testing the content against the trained model; and providing to a user the classification of the content. Optionally, the method includes receiving, from the user, a classification feedback of the content; and updating the trained model responsive to the content and the classification feedback.

Abstract: A modular node includes a semiconductor chip, including modular sensors to detect events or changes in environment, modular actuators for moving or controlling an object, a non-transitory computer readable medium storing a program, a processor executing the program configured to control module networking and setup, and a neuromorphic chip configured to receive information from the modular sensors and modular actuators, autonomously process the information received from the modular sensors and actuators, determine a validity of the information received from the modular sensors and actuators, and autonomously communicate with neighboring modular nodes for network auto-arrangement.