International Business Machines Corporation

Convey Corporation

John Coleman Newell

Aaron K Baughman

Stephen Carl Hammer

Craig M Trim

Micah Forster

Stefan Van Der Stockt

David Alexander Provan

Sebastian Kuruvilla Karivelithara

John Joseph Kent

Joseph Stephen Mabry

Anna Leigh Bourland

Jeff Powell

Noah Syken

Samuel Thomas Weston Butler

A computer-implemented method includes monitoring, by a computing device, sensor data during gameplay of a sporting event; determining, by the computing device, predictive factors associated with a target based on the monitoring the sensor data; determining, by the computing device, a real-time region of effectiveness for the target based on the predictive factors and training data identifying historical effectiveness of the target; and outputting, by the computing device, the real-time region of effectiveness for displaying the real-time region of effectiveness around the target.

Dynamically determining a region of effectiveness of athletes during game play based on predictive factors

Embodiments provide systems, methods and computer program products for artificial intelligence-based detection of delays in a shipping network that include training a machine learning model using a training set of in-flight snapshots to infer, based on a set of predictive features, whether a shipment having an estimated delivery dates will meet the estimated delivery date. The machine learning model represents a set of shipment statuses, a set of timings relative estimated delivery dates, and a set of shipment outcomes of the plurality of historical shipments.

Systems and methods for AI-based detection of delays in a shipping network

Using a simple cue to reduce a number of sequential frames included in a video that needs to be analyzed by an artificial neural network to predict information corresponding to a projectile depicted within the video is provided. A timing of the simple cue associated with the video is detected. The number of sequential frames within the video is reduced down to only those frames that are within a specified range of the simple cue. The artificial neural network is used to analyze the reduced number of sequential frames. The information corresponding to the projectile is predicted based on analyzing the reduced number of sequential frames using the artificial neural network.

Projectile extrapolation and sequence synthesis from video using convolution

Computer-implemented method includes developing, via a processor, a words model from a plurality of natural language text based articles relating to a subject and generating, via the processor, a static vector based upon the words model. The computer-implemented method further includes developing, via the processor, an actual articles model from actual articles, generating, via the processor, a bootstrapped vector using the actual articles model, generating, via the processor, a n-dimensional depth item using the static vector and the bootstrapped vector, and determining, via the processor, evidence based on the n-dimensional depth item. The computer-implemented method still further includes presenting, via the processor and a display, the evidence base upon an input query from a user.

Triangulated natural language decoding from forecasted deep semantic representations

Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: running a comment examining process for processing comments of one or more user to provide a comment processing output; applying data of a dataset as training data for training a neural network to define a trained neural network, wherein the training data includes input node training data and output node training data; and generating a decision rule for the dataset based on a transfer function of the trained neural network, wherein the decision rule is based on the comment processing output.

Unstructured key definitions for optimal performance

A set of vectors may be obtained. The vectors may be multi-dimensional vectors that are associated with and describe tokens from a first set of tokens from a corpus of sources. The description may be based in part on the relationship of the token to at least a portion of the remainder of the corpus. A set of sentiment scores may be obtained. The sentiment scores in the set of sentiment scores may describe a sentiment associated with a corresponding token that is described by a vector from the set of vectors. The set of vectors and the set of sentiment scores may be input into a pattern-recognizer pathway in a first neural network. A probability value of a potential future event may then be generated by the first neural network. The probability value may be based on the set of vectors and the set of sentiment scores.

Predictive neural network with sentiment data

Devices and methods for modeling streaming data are disclosed. A method includes: receiving, by a computing device, a local graph model; determining, by the computing device, a subgraph in the local graph model; acquiring, by the computing device, an external graph model; determining, by the computing device, a plurality of alternative subgraphs in the external graph model; determining, by the computing device, a score for each of the plurality of alternative subgraphs; selecting, by the computing device, an alternative subgraph having a highest score among the plurality of alternative subgraphs; and ensembling, by the computing device, the local graph model and the alternative subgraph having the highest score.

Growing community of inventors

Austin, TX, United States of America

John Coleman Newell