Abstract: An apparatus for providing cognitive insights comprising: a cognitive inference and learning system, the cognitive inference and learning system comprising a plurality of agents, the plurality of agents processing streams of data from a plurality of data sources, the processing the streams of data from the plurality of data sources via the plurality of agents performing a respective plurality of cognitive operations on the streams of data, at least one of the plurality of agents generating cognitive insights based upon the performing the respective plurality of cognitive operations on the streams of data from the plurality of data sources.

Abstract: In one aspect, the inventions include a system for control of an entertainment state system. First, an application plane layer is adapted to receive instructions regarding operation of the entertainment state system. Preferably, the application plane layer is coupled to an application plane layer interface. Second, a control plane layer includes an adaptive control unit, such as a cognitive computing unit, an artificial intelligence unit or a machine-learning unit. Third, a data plane layer includes an input interface to receive data input from one or more data sources.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing a layer output for a convolutional neural network layer, the method comprising: receiving the layer input, the layer input comprising a plurality of activation inputs, the plurality of activation inputs represented as a multi-dimensional matrix comprising a plurality of depth levels, each depth level being a respective matrix of distinct activation inputs from the plurality of activation inputs; sending each respective kernel matrix structure to a distinct cell along a first dimension of the systolic array; for each depth level, sending the respective matrix of distinct activation inputs to a distinct cell along a second dimension of the systolic array; causing the systolic array to generate an accumulated output from the respective matrices sent to the cells; and generating the layer output from the accumulated output.

Abstract: Embodiments are directed to data verification of business or consumer data. Certain embodiments include a data verification system that receives or selects data to be verified, selects one or more verification methods to verify, update, and/or append/enhance the data. The data verification system may verify the data with one or more data verification methods, either alone or in combination. The methods may include a web-crawling verification method, an agent web verification method, a call verification method, a direct mail method, an email method, an in-person verification method, or other methods. The system has the ability to, automatically or manually, (1) blend automatic and manual segmentation of records or elements by criteria such as industry type, best times of day/month/year to verify, update, or append, cost, and level of importance (2) select the best verification processing method(s), and (3) manage the results and properly verify, update, append/enhance records.

Abstract: Roughly described, the technology disclosed provides a so-called machine learned conversion optimization (MLCO) system that uses evolutionary computations to efficiently identify most successful webpage designs in a search space without testing all possible webpage designs in the search space. The search space is defined based on webpage designs provided by marketers. Website funnels with a single webpage or multiple webpages are represented as genomes. Genomes identify different dimensions and dimension values of the funnels. The genomes are subjected to evolutionary operations like initialization, testing, competition, and procreation to identify parent genomes that perform well and offspring genomes that are likely to perform well. Each webpage is tested only to the extent that it is possible to decide whether it is promising, i.e., whether it should serve as a parent for the next generation, or should be discarded.

Abstract: A method for configuring a neural network is provided. The method includes: selecting a neural network including a plurality of layers, each of the layers including a plurality of neurons for processing an input and providing an output; and, incorporating at least one switch configured to randomly select and disable at least a portion of the neurons in each layer. Another method in the computer program product is disclosed.

Abstract: An apparatus comprises a plurality of storage tiers, at least one data mover module, and skew predictor. A model generator processes information characterizing input-output activity involving one or more of the storage tiers in order to obtain skew measurements indicating portions of the input-output activity directed to portions of the one or more storage tiers for respective periods of time less than at least one corresponding time granularity, and generates a predictive model from the skew measurements. The skew predictor is configured in accordance with the predictive model to convert additional skew measurements obtained for a given period of time less than a desired time granularity to corresponding skew measurements in the desired time granularity. One or more of the converted skew measurements are utilized by the data mover module in controlling transfer of data between the storage tiers. The model generator is part of a machine learning system.

Abstract: A method, system and program product comprise monitoring inputs, into a system, for detected actions from a user. At least one detected action is identified. At least a first database storage location associated with the user is accessed. The first database storage location is at least configured for storage of emotional profiles of the user. At least a second storage location associated with the system is accessed. The second storage location is at least configured for storage of emotional profiles of the system. The at least one detected action is processed in a computational machine using data from the first storage location to determine a status of the user. A response to the status of the user is calculated. The response is at least in part determined by the status of the user and data contained in the second storage location.

Abstract: Methods and systems are provided for evaluating standing queries against updated contact entries configured as a stream of facts. The method includes resolving the standing queries into an array of rules, each rule having a first and a second condition; sorting one of the facts into a first property and a second property; comparing the first property of the fact to the first condition of each rule in the array of rules to produce a first subset of matching rules; comparing the second property of the fact to the second condition of each rule in the first subset of rules to produce a second subset of matching rules; and reporting at least one of the second subset of rules to an author of the matching rule. The method further includes populating a first hash with indicia of the first subset, and populating a second hash with the second subset.

Abstract: There is provided an information processing apparatus including: evaluation information extracting means extracting evaluation information from evaluation of every user for an item; preference information creating means for creating preference information indicating a preference of every user on the basis of the evaluation information extracted by the evaluation information extracting means and an item characteristic amount indicating a characteristic of the item; space creating means for creating a space in which the user is located, according to the preference information; and display control means for controlling display of the user located in the space, according to the space created by the space creating means and the preference information. The apparatus may be applied to, for example, an image display apparatus which displays server images for providing a variety of items and information.

Abstract: A computer system, comprising: one or more processors; and a memory coupled to the one or more processors, wherein the computer system is programmed with a set of computer-readable instructions configured to implement a method for determining a drill site in a shale, tight gas sands, coal bed methane or other unconventional well field for an oil or gas well and one or more parameter settings therefore, the computer-readable instructions comprising: one or more data mining instructions for data mining of a first part of a set of measurement or objective data parameters from existing oil or gas wells in the well field that, when executed, produce a ranking of each parameter and its respective effect on oil or gas well production from the well field; one or more training instructions that, when executed, produce a model comprising an artificial neural network (ANN) trained with the first part of the set of measurement or objective data parameters and/or the ranking that is useful for producing a group of optimiz

Abstract: Some embodiments include an experiment management interface for a machine learning system. The experiment management interface can manage one or more workflow runs related to building or testing machine learning models. The experiment management interface can receive an experiment initialization command to create a new experiment associated with a new workflow. A workflow can be represented by an interdependency graph of one or more data processing operators. The experiment management interface enables definition of the new workflow from scratch or by cloning and modifying an existing workflow. The workflow can define a summary format for its inputs and outputs. In some embodiments, the experiment management interface can automatically generate a comparative visualization at the conclusion of running the new workflow based on an input schema or an output schema of the new workflow.

Abstract: A method, system, and/or computer program product establish a data organization format for displaying data to a specific user. A first set of data, which is organized according to a user-selected data organization format, is received from a user. A cognition bias, which defines a preferred manner in which the user cognitively interprets data, is identified by being associated with the user-selected data organization format. The cognition bias is also associated with one or more other data organization formats that support the cognition bias. A second set of data is received and formatted using the one or more other data organization formats that also support the cognition bias. The second set of data is then displayed using the one or more data organization formats that also support the cognition bias.

Abstract: The invention discloses an intelligent inhaler holster with a system and method to sense, track properties of inhaled air and medication, alert in hostile environments, map medication with personal dynamics, inhaled air and environment for better health, along with predictive and prognostic analytics. The system includes a sensor module to sense various environmental parameters of the personal environment envelope surrounding the individual. The system also includes an inhaler module configured to track the medication taken by the user. The system also has a processing module to collect data from multiple numbers of environmental sensors and further dynamically processes the information from the inhaler module including the time and location from where the user has taken medication. The processing module alerts for deviations, learns the preferred settings, advises based on trends, predictive and prognostic analytics.

Abstract: The present invention generally relates to failure prediction of an infrastructure (110). A failure likelihood for one or more components of an infrastructure (110) is determined. History data (210) representing prior failures of the components of the infrastructure (110) is applied (230-250) to a Bayesian nonparametric statistical model using a beta process. Then the failure likelihood of one or more components of the infrastructure from the Bayesian nonparametric statistical model is estimated (270). Aspects of the invention include computer-implemented methods (200, 300), software and computer systems (100).

Abstract: Workload data associated with past execution of an application by a computing system is obtained. Two or more prediction models are trained using the obtained past workload data. A weight is assigned to each of the two or more trained prediction models. The two or more weighted prediction models are combined to form an ensemble prediction model configured to predict, in real-time, workload associated with future execution of the application by the computing system.

Abstract: A reservoir computing neuromorphic network includes an input layer comprising one or more input nodes, a reservoir layer comprising a plurality of reservoir nodes, and an output layer comprising one or more output nodes. A portion of at least one of the input layer, the reservoir layer, and the output layer includes an optically tunable material.

Abstract: Some embodiments include a method of machine learner workflow processing. For example, a workflow execution engine can receive an interdependency graph of operator instances for a workflow run. The operator instances can be associated with one or more operator types. The workflow execution engine can assign one or more computing environments from a candidate pool to execute the operator instances based on the interdependency graph. The workflow execution engine can generate a schedule plan of one or more execution requests associated with the operator instances. The workflow execution engine can distribute code packages associated the operator instances to the assigned computing environments. The workflow execution engine can maintain a memoization repository to cache one or more outputs of the operator instances upon completion of the execution requests.

Abstract: A method for inferring venues from social messages includes: accessing a collection of venues and training a classifier that predicts whether a social message is linked to a venue in the collection of venues; receiving a new social message; for each venue in the collection of venues: identifying for the new social message corresponding meta-paths to the particular venue; encoding the corresponding meta-paths as a feature vector for the trained classifier; computing by the trained classifier a score for each venue in the collection of venues indicating whether the new social message is linked to the venue; and based on the scores, identifying at least one candidate venue as a predicted venue for the new social message and associating the predicted venue with the new social message. In some implementations, the new social message is not geotagged.

Abstract: A method and system for adding advertising content to multimedia content elements. The method comprises receiving a request from a user device to identify a multimedia content element, the request including the multimedia content element; generating at least one signature respective of the multimedia content element; identifying at least one concept matching the at least one signature; determining at least one identifier associated with the multimedia content element respective of the at least one matching concept; searching a database to identify at least one advertising content item associated with the at least one identifier; and sending the at least one advertising content item together with the at least one identifier upon determination that the at least one advertising content item is associated with the at least one identifier.