Abstract: This document presents a system and method for presenting vetted and verified Supplier information to Buyers. The Know Your Suppler (TYS) Application collects previously vetted and verified Supplier information and commits the collected information, verification authorities, verification details, and transaction information to a shared distributed ledger implemented as a privately permissioned blockchain. Buyers who want to onboard a newly identified Supplier, or update Supplier information with more recently verified information records, may subscribe to the TYS Application and purchase available vetted and verified Supplier information to optimize the onhoarding or updating process for Suppliers from whom the Buyer wants to purchase goods or services.

Abstract: This document presents a system and method for presenting vetted and verified Supplier information to Buyers. The Know Your Suppler (TYS) Application collects previously vetted and verified Supplier information and commits the collected information, verification authorities, verification details, and transaction information to a shared distributed ledger implemented as a privately permissioned blockchain. Buyers who want to onboard a newly identified Supplier, or update Supplier information with more recently verified information records, may subscribe to the TYS Application and purchase available vetted and verified Supplier information to optimize the onboarding or updating process for Suppliers from whom the Buyer wants to purchase goods or services.

Abstract: A method and an information processing apparatus for classifying subject matter of content in a webpage are described. The method comprises receiving a webpage, extracting content from the webpage and identifying keywords from the extracted content. The keywords are identified based on keywords contained in a taxonomy stored by the information processing apparatus that associates the keywords with categories of subject matter. The information processing apparatus assigns an importance score to the keywords identified from the extracted content. Context scores associated with categories or subcategories of subject matter within the taxonomy are calculated based on the importance scores of the identified keywords. The content is classified as being associated with the category of subject matter based on the context scores.

Abstract: A modular neural network system comprising: a plurality of neural network modules; and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A modular neural network system comprising: a plurality of neural network modules; and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A modular neural network system comprising: a plurality of neural network modules; and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A modular neural network system comprising: a plurality of neural network modules: and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A modular neural network system comprising: a plurality of neural network modules; and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A modular neural network system comprising: a plurality of neural network modules; and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A method for AI training at an end device placed in an end-user premises, the method comprising: receiving by a processor of the end device sensor data captured by a sensor bundle of the end device; deciding if the sensor data included a data unit that requires external feedback, and in case external feedback is required obtaining external feedback about classification of the data unit; updating a decision module controlled by the processor of the end device based on the obtained feedback; and making a decision about the received sensor data, by the decision module. The external feedback is obtained from an end user or from another device. The method includes obtaining instructions about the type of decision to make, from a user or by pre-configuration. External feedback about the decision is obtained and the decision module is updated based on the feedback.

Abstract: A robotic system (“new robot”) operative for performing at least one task in an environment, the system comprising: learn-from-predecessor functionality governed by a data exchange protocol, which controls short-range wireless knowledge transfer from a short-range wireless transmitter in a predecessor robot system (“old robot”) to a short-range wireless receiver in said robotic system, said knowledge comprising at least one environment-specific datum previously stored by the predecessor robot.

Abstract: A robotic system (“new robot”) operative for performing at least one task in an environment, the system comprising: learn-from-predecessor functionality governed by a data exchange protocol, which controls short-range wireless knowledge transfer from a short-range wireless transmitter in a predecessor robot system (“old robot”) to a short-range wireless receiver in said robotic system, said knowledge comprising at least one environment-specific datum previously stored by the predecessor robot.

Abstract: This document presents a system and method for presenting vetted and verified Supplier information to Buyers. The Know Your Suppler (TYS) Application collects previously vetted and verified Supplier information and commits the collected information, verification authorities, verification details, and transaction information to a shared distributed ledger implemented as a privately permissioned blockchain. Buyers who want to onboard a newly identified Supplier, or update Supplier information with more recently verified information records, may subscribe to the TYS Application and purchase available vetted and verified Supplier information to optimize the onboarding or updating process for Suppliers from whom the Buyer wants to purchase goods or services.

Abstract: A modular neural network system comprising: a plurality of neural network modules; and a controller configured to select a combination of at least one of the neural network modules to construct a neural network, dedicated for a specific task.

Abstract: A system and method for implementation of attention mechanism in artificial neural networks, the method comprising: receiving sensor data from at least one sensor sensing properties of an environment, classifying the received data by a multi-regional neural network, wherein each region of the network is trained to classify sensor data with a different property of the environment, and wherein each region has an individually adjustable contribution to the classification, calculating based on the classification a current environment state including at least one property of the environment, and based on the at least one property, selecting corresponding regions of the network and adjusting contribution of the selected regions to the classification.

Abstract: A robotic system (“new robot”) operative for performing at least one task in an environment, the system comprising: learn-from-predecessor functionality governed by a data exchange protocol, which controls short-range wireless knowledge transfer from a short-range wireless transmitter in a predecessor robot system (“old robot”) to a short-range wireless receiver in said robotic system, said knowledge comprising at least one environment-specific datum previously stored by the predecessor robot.

Abstract: The present invention includes computer vision based driver assistance devices, systems, methods and associated computer executable code (hereinafter collectively referred to as: “ADAS”). According to some embodiments, an ADAS may include one or more fixed image/video sensors and one or more adjustable or otherwise movable image/video sensors, characterized by different dimensions of fields of view. According to some embodiments of the present invention, an ADAS may include improved image processing. According to some embodiments, an ADAS may also include one or more sensors adapted to monitor/sense an interior of the vehicle and/or the persons within. An ADAS may include one or more sensors adapted to detect parameters relating to the driver of the vehicle and processing circuitry adapted to assess mental conditions/alertness of the driver and directions of driver gaze. These may be used to modify ADAS operation/thresholds.

Abstract: The present invention includes computer vision based driver assistance devices, systems, methods and associated computer executable code (hereinafter collectively referred to as: “ADAS”). According to some embodiments, an ADAS may include one or more fixed image/video sensors and one or more adjustable or otherwise movable image/video sensors, characterized by different dimensions of fields of view. According to some embodiments of the present invention, an ADAS may include improved image processing. According to some embodiments, an ADAS may also include one or more sensors adapted to monitor/sense an interior of the vehicle and/or the persons within. An ADAS may include one or more sensors adapted to detect parameters relating to the driver of the vehicle and processing circuitry adapted to assess mental conditions/alertness of the driver and directions of driver gaze. These may be used to modify ADAS operation/thresholds.

Abstract: A method for controlling a device comprises: a) providing a mobile device comprising a camera; b) positioning said mobile device such that said camera acquires the image of an operator's hands; c) analyzing the movements of said operator's hands to derive a control command therefrom; and d) transmitting said control command to a controlled device.

Abstract: A method for controlling a device comprises: a) providing a mobile device comprising a camera; b) positioning said mobile device such that said camera acquires the image of an operator's hands; c) analyzing the movements of said operator's hands to derive a control command therefrom; and d) transmitting said control command to a controlled device.