Abstract: An artificial intelligence that registers users to a common distributed computing platform that provides access to a plurality of voice assistants. A first command issued by a user is received by a first voice assistant of the plurality of voice assistants at a first location. A context database is built by storing the at least the first command on the distributed computing platform. A second command issued by the user is received by a second voice assistant of the plurality of first assistants at a second location. A context assigning engine on the common distributed computing platform analyzes the second command in comparison with the at least the first command on the context database. Similarity between the first command and the second command provides context. The second voice assistant receiving the context from the context assigning engine employs the context to answer the second command.

Abstract: A computer-implemented method for multimedia modification is disclosed. The computer-implemented method includes classifying one or more objects detected within a user's field of view through an augmented reality environment. The computer-implemented method further includes determining a context of the user based, at least in part, on the one or more classified objects detected within the user's field of view. The computer-implemented method further includes generating a priority score for the one or more classified objects based, at least in part, on the context of the user. The computer-implemented method further includes modifying an object detected within the user's field of view based, at least in part, on the priority score of the object.

Abstract: A computer-implemented method according to one embodiment includes causing an environment generator of a Generative Adversarial Network (GAN) to generate realistic training environments, and causing a first discriminator of the GAN to determine whether the realistic training environments are real or fake. In response to a determination that an accuracy of the first discriminator at determining whether the realistic training environments are real or fake is within a predetermined range, the environment generator is caused to generate a first realistic environment. The method further includes causing the first realistic environment to be shared with an agent of a reinforcement learning (RL) algorithm and a second discriminator, and receiving, from the agent of the RL algorithm and the second discriminator, feedback associated with the first realistic environment. The environment generator is caused to generate a second realistic environment based on the feedback associated with the first realistic environment.

Abstract: An approach for state-based dynamic multi-dimensional goal reinforcement learning may be provided. The approach may include measuring a reward for an action. The reward may be a dimensional vector of a number of sub-goal dimensions for achieving a final goal. The approach may also include, determining a temporal difference. The temporal difference can be the difference between the reward from an action taken in response to an immediately prior state and the measured reward. The approach may also include updating a Q-table for the action. Updating the Q-table can be based on the first state and the measured reward. Further, the approach may also include predicting a goal for a first state. The prediction can be based on a Q-value from the updated Q-table. Within the approach, the prediction can be based on a deep neural network configured to output a probability.

Abstract: A system, method, and computer program product for implementing voice activated hardware device enabling is provided. The method includes receiving an instruction set comprising initialization commands associated with initializing a non-specific device of a plurality of devices. The instruction set is analyzed and it is determined that specified instruction keywords are located within the initialization commands. The initialization commands are inputted into a bidirectional encoder representations from transformers (BERT) model classifier component and a specified device associated with the instruction set is classified. As a result, it is determined if a maximum threshold is reached for any class of devices and the specified device is assigned as a desired device. In response, the specified device is enabled with respect to an operationally functional state.

Abstract: A method, computer program product, and computer system for predicting a class of a given input to multiple models. Class parameters of the models are received. A process that predicts the class of a given input to the models is performed using the class parameters of the models. The process is (i) a model ensemble process predicting that the class of the given input is a class that maximizes a function of class accuracy parameters selected from combinations of the class parameters, (ii) a first threshold process based on a requirement that the class of the given input be predicted by running a model whose class accuracy parameter is at least a specified threshold, or (iii) a second threshold process based on a requirement that a specified class be predicted by a running of all models whose class accuracy parameter is at least the specified threshold.

Abstract: Provided is a system and method for moving a virtual object within virtual space in response to an external input supplied by a user. A machine learning model may predict a movement of the virtual object and implement such movement in a next frame of the virtual space. An example operation may include one or more of receiving a measurement of an external input of a user with respect to a virtual object displayed in virtual space, predicting, via execution of a machine learning model, a movement of the virtual object in the virtual space in response to the external input of the user based on the measurement of the external input of the user, and moving the virtual object in the virtual space based on the predicted movement of the virtual object by the machine learning model.

Abstract: A computer-implemented method, according to one embodiment, includes: determining whether a predetermined version of a source script is available. In response to determining that a predetermined version of the source script is available, it is used to condition a first processor, and instructions are sent to the conditioned first processor to generate a translated copy of the source script by translating the words in the source script from a source language to a target language. Instructions are also sent to a second processor to determine a distribution of metrics associated with the speech of each of the actors in the source audio file. The distributions are used to condition a third processor, and instructions are sent to the conditioned third processor to generate an audio file that includes words spoken in the target language. Furthermore, instructions are sent to merge the generated audio file with the video file.

Abstract: One or more user interactions directed to a set of one or more voice-controlled devices in an environment are received by a first connected device. A first input to a first voice-controlled device of the set of voice-controlled devices is detected based on the user interactions. A potential second input to the set of voice-controlled devices is determined in response to the first input and based on an activity model. A deviation from the potential second input is monitored for, in response to the first input and from the user interactions. An activity anomaly in the environment is identified based on the monitoring. A correction action is performed in response to the activity anomaly.

Abstract: A method, computer program product, and computer system for translating, using a beam search, a source sentence in a source language into a target sentence in a target language by an iterative process.

Abstract: A system, method, and computer program product for implementing voice activated hardware device enabling is provided. The method includes receiving an instruction set comprising initialization commands associated with initializing a non-specific device of a plurality of devices. The instruction set is analyzed and it is determined that specified instruction keywords are located within the initialization commands. The initialization commands are inputted into a bidirectional encoder representations from transformers (BERT) model classifier component and a specified device associated with the instruction set is classified. As a result, it is determined if a maximum threshold is reached for any class of devices and the specified device is assigned as a desired device. In response, the specified device is enabled with respect to an operationally functional state.

Abstract: An approach for generating an optimized video of a speaker, translated from a source language into a target language with the speaker's lips synchronized to the translated speech, while balancing optimization of the translation into a target language. A source video may be fed into a neural machine translation model. The model may synthesize a plurality of potential translations. the translations may be received by a generative adversarial network which generates video for each translation and classifies the translations as in-sync or out of sync. A lip-syncing score may be for each of the generated videos that are classified as in-sync.

Abstract: A system, method, and computer program product for implementing automated digital text optimization is provided. The method includes receiving during execution of an Internet search process, digital textual content comprising embedded words, morphemes, and phrases. A specified format for generating a summary for the digital textual content is identified and probability distribution attributes are generated with respect to target vocabulary of the digital textual content. Content of the digital textual content is replaced with replacement content and an automated digital summary of the digital textual content is generated thereby enabling optimized operational functionality of a recurrent neural network (RNN) encoder-decoder hardware device. A decoded version of the automated digital summary is presented via a specialized graphical user interface.

Abstract: Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.

Abstract: A system, method, and computer program product for implementing digital script modification is provided. The method includes generating image sequences associated with textual content of a digital story. Multiple contextual dimensions are identified within the textual content and a group of dimensions are selected. The image sequences in combination with the group of dimensions are expanding or contracted and image sequences are altered based on detected interactions with the group of dimensions. Dimensions are extracted from the group of dimensions during presentation of the digital story and a scriptwriter is enabled to modify the dimensions. The image sequences are modified and a hardware interface device is enabled to interact with various image sequences and alter the multiple contextual dimensions. The textual content of the digital story is dynamically altered.

Abstract: Systems, methods, and computer programming products leveraging cognitive computing and machine learning to dynamically establish circuits within conference calls merging in new callers. The newly established circuits are optimized and established based on location attributes of the new caller and conference call participants, as well as the calling plans and/or costs associated with establishing the circuits to the different conference call participants. New circuits merging in new callers can be prioritized to establish endpoints of the circuit with optimal participants at nearby locations or the same location as the new caller, rather than establishing the endpoints between the new caller and a target participant of the conference call as the default endpoints. Optimized circuits being established between new callers and existing conference call participants can be provisioned entirely within the PSTN of a single service provider or can span across multiple service provider networks.

Abstract: Dynamic checkpointing can include determining, using a processor, a process criticality corresponding to a process configured to execute on computer hardware. The process criticality indicates a priority of the process relative to at least one other process configured to execute on the computer hardware. A checkpoint schedule can be generated, using the processor and based on the process criticality, for checkpointing the process when it executes on the computer hardware.

Abstract: An approach for the capability of managing IoT devices (including eSIMs) and dynamically switch those IoT devices to different network/wireless carriers based on the activity performed is disclosed. The approach can identify poor network connectivity problems with the IoT devices while performing the activities or switching/moving from one activity to another activity and can predict the context of performing the activities with various IoT devices based on identified information. The approach can dynamically adjust the configuration setting of those IoT devices to connect to the appropriate network service provider based on the prediction context of those activities.

Abstract: A computer-implemented includes streaming a first segment of multimedia data to a buffer on a first computing device at a first bitrate, wherein the first segment includes a first set of video frames encoded at a first resolution. The computer-implemented method further includes streaming a second segment of the multimedia data to the buffer on the first computing device at a second bitrate, wherein the second segment includes a second set of video frames encoded at a second resolution. The computer-implemented method further includes determining that a first predetermined threshold is reached. The computer-implemented method further includes streaming, in response to determining that the first predetermined threshold is reached, a third segment of multimedia data to the buffer on the first computing device, wherein the third segment includes a first set of pixels that are logically related to the second set of video frames of the second segment.

Abstract: Deviations in a 3D printing process can be detected during printing via sensors or by user observation. A user can manipulate and evaluate any deviations from a 3D model via a simulation of the work-in-progress object via virtual reality. The user can also make changes to the model, resulting in the printer completing the same work-in-progress object based on the revised model.