Abstract: Various embodiments are generally directed to techniques for multi-voice speech recognition commands, such as based on monitoring a telecommunications channel between first and second devices, for instance. Some embodiments are particularly directed to prompting initiation of a transaction between a first entity associated with a first device and a second entity associated with a second device based on detection of an audible request corresponding to the second entity and an audible response corresponding to the first entity.

Abstract: Systems, methods, articles of manufacture, and computer program products to: train a prediction model using a machine learning process, the prediction model configured to estimate whether further application of a hyperparameter tuning technique will cause an improvement in at least one of the hyperparameters; select the hyperparameters using the tuning technique; apply the prediction model to determine if further adjustment of the hyperparameters is likely to improve the success metric; and terminate the tuning technique when: accuracy of the prediction model in predicting improvement in a hyperparameter is above a predetermined accuracy threshold, and the prediction model predicts that further application of the tuning technique will not result in an improvement to the hyperparameter; or the accuracy of the prediction model in predicting improvement in the parameter is below the predetermined accuracy threshold, and an accuracy of hyperparameter adjustment is determined to be below a predetermined adjustment

Abstract: Various embodiments are generally directed to techniques utilizing computers to process service billing data, generate one or more groups of customers based on one or more attributes of the data, and train a recurrent neural network (RNN) to predict future bill amounts for customers. Embodiments further include techniques to predict the future bill amounts of the customers and providing an indication of the bill amounts to the customers.

Abstract: Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent plurality of colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors. A matrix barcode may be generated based on the related plurality of colors and an ultraviolet layer.

Abstract: Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent plurality of colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors. A matrix barcode may be generated based on the related plurality of colors and an infrared layer.

Abstract: Exemplary embodiments relate to the secure storage of security questions through an immutable log, such as a blockchain. The security questions may be stored in a centralized location, accessible from an application or browser tab running on the user's device. When a security question is required, such as to perform a password reset on a website, the website may interact with the application or browser tab, which retrieves the question(s) from the blockchain. The user may enter their answers to the question(s), which may be hashed by the application or tab. The hashed answers may be entered into the original requesting website, which may verify with the blockchain that the correct answers have been provided. Thus, the requesting website sees neither the questions nor the answers. Additional security features may include logging requests for questions, so that a user can determine if a security question may have been compromised.

Abstract: Exemplary embodiments pertain to new techniques for classifying or labeling organized data. A major impediment to implementing high-quality machine learning is the lack of readily accessible labeled data. In some cases, data can be classified using a classifier, but these solutions can be inaccurate and slow. Exemplary embodiments address the problem of obtaining accurate labeled data in a timely manner by applying a classifier configured to operate on character-level embeddings. Among other advantages, this can help the classifier to recognize information contained within a data unit, such as a cell of a table. The classifier may operate within the organizational structure of the data, such as by operating across a particular row or column of a table. Because data within a particular row or column is often temporally organized (e.g., transactions that are logged in chronological order), row- or column-based approaches can yield more accurate results.

Abstract: Described herein are embodiments for managing comments in a program code file. A system may select program code and compile it to an intermediary code. The system may compare the intermediary code to a library of intermediary code snippets associated with comments. Based on the comparison, a system may recognize the code to be obsolete. In some embodiments, a system may generate one or more recommendations to update a code. Based on received feedback regarding a recommendation, a system may accordingly update a code.

Abstract: Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second sub set.

Abstract: Techniques to improve operation of an augmented reality device and/or system utilizing fiducial markers and/or color space conversions are provided. In various embodiments, a color space of an object is altered based on a movement of the object in relation to an environment. The environment may include two or more segments with a distinct environment color space in relation to one another. The object may transition from one of the two or more environment segments into the other one of the two or more segments. The alteration is based on the transition from the color space of the one of the two or more environment segments into the other one of the two or more environment segments.

Abstract: Exemplary embodiments may provide an approach to converting multidimensional color data for an image encoded in a first color space into an intermediate form that is a single dimensional value. The exemplary embodiments may then decode the intermediate form value to produce an encoding of the color data that is encoded in a second color space that differs from the first color space. In this manner, the data for the image may be efficiently converted from an encoding in the first color space into an encoding in the second color space.

Abstract: Techniques to apply machine learning to schedule events of interest for a device user. As described herein, a typical device user is inundated with information suggesting activities and other things to do. Using these techniques, the information is categorized according to the activity and those activities that are most likely to be engaged in by the device user are recommended to the device user (via their device) as events of interest. If the device user selects an event of interest, the device is updated to reflect that selection. For instance, a calendar application may be updated to include an event description at the event's date and time. Other embodiments are described and claimed.

Abstract: Techniques for providing a real-time service that protects personal data of clients from customer service agents are provided. Customer data that includes personal data indicative of sensitive information of a customer can be received from the customer. The personal data within the received customer data can be detected and a token that does not include the sensitive information of the customer can be generated. The personal data and the generated token can be stored along with data indicating a relationship between the token and the personal data. The personal data in the received customer data can be replaced by the token to form modified customer data. The modified customer data can be provided to a customer service representative. The token within the modified customer data can later be detected and associated with the personal data without revealing the personal data to the customer service representative.

Abstract: Techniques and apparatus for providing peer-based management of user accounts are described. In one embodiment, for example, an apparatus may include at least one memory and logic coupled to the at least one memory. The logic may be configured to receive a request from at least one first user account to unlock a second user account locked responsive to a fraud event, determine a safe authentication value for the fraud event, and unlock the second user account responsive to the at least one first user account being a safe authentication account and the safe authentication value being over a safe authentication threshold value. Other embodiments are described.

Abstract: Various embodiments are generally directed to techniques utilizing computers to process service billing data, generate one or more groups of customers based on one or more attributes of the data, and train a recurrent neural network (RNN) to predict future bill amounts for customers. Embodiments further include techniques to predict the future bill amounts of the customers and providing an indication of the bill amounts to the customers.

Abstract: Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent plurality of colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors. A matrix barcode may be generated based on the most prevalent colors, the related plurality of colors, an infrared layer, and an ultraviolet layer.

Abstract: Described herein are embodiments for managing comments in a program code file. A system may select program code and compile it to an intermediary code. The system may compare the intermediary code to a library of intermediary code snippets associated with comments. Based on the comparison, a system may recognize the code to be obsolete. In some embodiments, a system may generate one or more recommendations to update a code. Based on received feedback regarding a recommendation, a system may accordingly update a code.

Abstract: Exemplary embodiments pertain to new techniques for classifying or labeling organized data. A major impediment to implementing high-quality machine learning is the lack of readily accessible labeled data. In some cases, data can be classified using a classifier, but these solutions can be inaccurate and slow. Exemplary embodiments address the problem of obtaining accurate labeled data in a timely manner by applying a classifier configured to operate on character-level embeddings. Among other advantages, this can help the classifier to recognize information contained within a data unit, such as a cell of a table. The classifier may operate within the organizational structure of the data, such as by operating across a particular row or column of a table. Because data within a particular row or column is often temporally organized (e.g., transactions that are logged in chronological order), row- or column-based approaches can yield more accurate results.

Abstract: An article of manufacture may include a matrix barcode on a physical medium and associated with an environment. The matrix barcode may include a plurality of colors, where at least one of the plurality of colors is a least prevalent color, of a plurality of prevalent colors in the environment.

Abstract: Various embodiments are directed to a password security warning system. An artificial neural network or other types of models may be used to determine whether a password that is created, input, or proposed by a user via an interface includes one or more predictable or typical transformations or combinations of characters derived from user-specific information. Based on the determination, a warning may be provided to the user.