Abstract: The disclosed methods may receive a first request for access to a first system memory from a new user and a first justification, the first request includes first role information and first current access information of the new user, determine whether the first request is within a request cluster based on first role history information and current access history information. When the first request is within the request cluster, generate a matrix from the first role information and the first current access information, and determine using a first neural network, whether to grant the first request based on the matrix. When the first request is granted by the first neural network, determine, using a second neural network, whether the first justification is similar to first justification history information. When the first justification is similar to the first justification history information, grant the new user access to the first system memory.

Abstract: Various embodiments are generally directed to techniques for creating and utilizing multidimensional embedding spaces for data objects, such as to condition the data for input to a neural network, for instance. Some embodiments are particularly directed to detecting data types for structured data based on learned metadata. In many embodiments, an embedding space for a set of data objects may be customized with a set of dimensions that correspond to various characteristics of the set of data objects. For example, a set of data objects may correspond to a table with each data object corresponding to a data entry in the table. In such examples, correlations between different columns and/or within a column of data may be identified and utilized as metadata to improve classifications by the neural network.

Abstract: Exemplary embodiments may use word embeddings to enhance scanning of programming code scripts for sensitive subject matter, such as confidential subject matter. The scanning may be performed by a neural network in some exemplary embodiments. The neural network initially may be trained on a corpus of programming code scripts to identify keywords relating to sensitive subject matter, such as passwords, tokens or credentials. The neural network may not only identify instances of the keywords but also may identify related terms as well. The output of the scan may be a ranked list of terms in the programming code script that may relate to sensitive subject matter.

Abstract: Disclosed embodiments include systems and methods for providing a secure physical storage system. The system may receive a request to register a first physical storage box from an entity including location information and security information. The request can be validated by comparing the security information to a predetermined security threshold. The location information associated with the first physical storage box can be recorded to a blockchain. The first registration information can be received from a first user device. The first physical storage box can be assigned to the first user device and a first identity token associated with the first physical storage box. The assignment information associated with the first physical storage box can be recorded to the blockchain. A first identity token can be received from the first user device. Instructions can be transmitted to the first physical storage box to transition from a locked to an unlocked state.

Abstract: The exemplary embodiments provide an improved approach to preventing exfiltration through email messages. The exemplary embodiments process outbound email messages to determine whether an outbound email message contains sensitive subject matter based on contextual information. The determination may be made based at least in part on the context reflected in the contextual information. In the exemplary embodiments, the determination of whether an outbound email message contains sensitive subject matter that should not be exfiltrated may be based at least in part on analysis performed by a trained neural network model.

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: 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 subset.

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 color of a plurality of prevalent colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors and a colorspace conversion. A matrix barcode may be generated based on the related plurality of colors and an ultraviolet layer.

Abstract: Embodiments are directed to methods and systems for inventions disclosure and automated disclosure form generation.

Abstract: In the disclosed transaction processing system, a system and method are described that increase the ease of access and use of different currency networks by consumers using customizable transaction devices. The customizable transaction devices may be re-programmed prior to or during a currency transaction in accordance with the consensus protocol of the currency network associated with the currency transaction. The currency network further includes one or more host devices, each of which include an interface configured to communicate with a transaction device for the purposes of re-programming a Field Programmable Gate Array (FPGA) of the transaction device according to one or more currency network consensus protocols. Optimizing the performance of transaction devices for proof-of-work or other consensus protocol processing decreases the latency associated with validating currency network transactions, thereby increasing the suitability of cryptocurrency for retail transactions.

Abstract: Systems, methods, and computer program products to transmit, by a web browser to a web server, a hypertext transfer protocol request for a web page at a first uniform resource identifier (URI). The web browser may receive, from the web server via, the web page and metadata of a plurality of candidate advertisements, the plurality of candidate advertisements determined based on a master machine learning (ML) model. A client ML model executing in the web browser may process the received metadata, the client ML model trained based on prior interactions between one or more users of the web browser and a plurality of previously displayed advertisements. The client ML model may determine based on the processing, a first candidate advertisement of the plurality of candidate advertisements to display in the web browser with the received web page.

Abstract: Systems to retain a battery within, and to eject a battery from, a battery receptacle of a medical device, such as a portable defibrillator, are described. A battery receptacle of a medical device includes an element that is configured to engage an inserted battery to prevent, or reduce, movement of the battery within the receptacle and to assist with removing the battery from the receptacle. In an example, the element is a monolithic structure that includes a retention portion and an ejection portion. The retention portion is positioned at a side wall of the battery receptacle, and the ejection portion terminates in a free end positioned a distance from the side wall. When the battery is inserted into the battery receptacle, the retention portion exerts a retention force on a side surface of the battery, and the ejection portion exerts an ejection force on an end surface of the battery.

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: 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 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: This disclosure describes a method for retrofitting an existing plant. The method includes adding a fractionation process to separate bran from other components in a feedstock to the existing plant, adding a pretreatment process downstream of the fractionation process, the pretreatment process configured to receive the bran and utilize water and heat to break down cellulose and hemicellulose in the bran; adding a hydrolysis and cellulosic fermentation process downstream of the pretreatment process and upstream of the fermentation process to hydrolyze the bran with a cellulase enzyme complex cocktail and to ferment with an organism to produce cellulosic beer; and combining the cellulosic beer with starch from the grain in the existing plant into the fermentation process to increase overall yield per feedstock unit in the existing plant.