Sap Se

Viktor Lapitski

Alexander Ocher

Andrey Belyy

A database includes a blockchain infrastructure that allows data tables comprising the database to be associated with respective blockchains. Data inserted into a data table is replicated in its associated blockchain. Certain operations on a data table are disabled when it is associated with a blockchain.

Dual-stack architecture that integrates relational database with blockchain

Technologies described herein can be used to generate and distribute neural network models and executable code using feedback data received from one or more client computing devices. A neural network model can be generated by a server computer. Executable code can also be generated by the server that, when executed by a client computing device, causes the client device to generate a prediction using the neural network model. The server can transmit the model and code to one or more client computing devices. The server can receive feedback data from the client device(s) based on predictions generated by the client device(s) using the neural network model and the executable code. The server can generate an updated version of the neural network model and/or an updated version of the executable code base on the feedback data, and can transmit the updated model and/or the updated code to the client device(s).

Neural network model generation and distribution with client feedback

Embodiments of the present disclosure pertain to a personal assistant controller. In one embodiment, the present disclosure includes a computer implemented method comprising receiving a voice audio signal in the personal assistant controller, converting the voice audio signal into a target command corresponding to one of a plurality of personal assistants, wherein different personal assistants comprise different target command protocols for executing different operations on different network enabled appliances, and sending the target command for execution by a backend system corresponding to the one of the plurality of personal assistants, and in accordance therewith, performing an operation on the backend system.

Intelligent personal assistant controller where a voice command specifies a target appliance based on a confidence score without requiring uttering of a wake-word

Disclosed herein are system, method, and computer program product embodiments for a an ETL (extract-transform-load) system. An embodiment operates by receiving, at a processor, a message including a request to move data from a source database to a target database. The data is retrieved from the source database. One or more operations to perform on the data that convert the data from a source format associated with the source database to a target format associated with the target database are determined from the message. The one or more operations are executed on the data. The data is stored on the target database in the target format.

Dynamic execution of ETL jobs without metadata repository

Disclosed herein are system, method, and computer program product embodiments for a secured cloud storage system. An embodiment operates by receiving a compressed file comprising data that has been compressed using a compression algorithm. The compressed data is divided into a plurality of separate files. A password for each of the separate files is determined. Each of the separate files is encrypted with its corresponding password. The encrypted files are stored across a plurality of servers.

Secure cloud storage system

Disclosed herein are system, method, and computer program product embodiments for interfacing with and managing IoT devices. An embodiment operates by requesting a list of device-specific capabilities from one or more IoT devices, providing a user interface by which users can view all available capabilities across the one or more IoT devices, and receiving a selected capability which subsequently executes on the appropriate IoT device.

Growing community of inventors

Mountain View, CA, United States of America

Viktor Lapitski