Abstract

A method for operating an ensemble of narrow AI agents, the method may include obtaining one or more sensed information units; determining, by a perception unit and based on the one or more sensed information units, one or more relevant narrow AI agents of the ensemble, that are relevant to a processing of the one or more sensed information units; wherein the ensemble is relevant to a first plurality of scenarios; processing the one or more sensed information units, by the one or more relevant narrow AI agents, to provide one or more narrow AI agent outputs; and processing, by an intermediate result unit, the one or more narrow AI agent outputs to provide an intermediate result; and generating a response, by a response unit, based on the intermediate result; wherein each narrow AI agent is relevant to a respective fraction of the first plurality of scenarios.

IPC Classes  ?

• G06N 20/00 - Machine learning

Abstract

Systems, and method and computer readable media that store instructions for calculating signatures, utilizing signatures and the like, wherein for a low-power calculation of a signature, the method comprises: receiving or generating a media unit of multiple objects: processing the media unit by performing multiple iterations, determining a relevancy of the spanning elements of the iteration; completing the dimension expansion process by relevant spanning elements of the iteration and reducing a power consumption of irrelevant spanning; determining identifiers that are associated with significant portions of an output of the multiple iterations; and providing a signature that comprises the identifiers and represents the multiple objects.

IPC Classes  ?

• G06F 17/30 - Information retrieval; Database structures therefor
• G06F 17/16 - Matrix or vector computation
• G06N 3/04 - Architecture, e.g. interconnection topology
• H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system

Abstract

A method for responding to a query is implemented on at least one computing device and includes: receiving at least one query from a user device; determining a context for the at least one query, selecting at least one deep learning network (DLN) of a plurality of DLNs to process the at least one query, where the selecting is based at least on matching the context to the at least one DLN, sending at least a representation of the at least one query and the context to the at least one DLN, receiving at least one response to the at least one query from the at least one DLN, and sending the at least one response to the user device.

IPC Classes  ?

• G06F 15/18 - in which a program is changed according to experience gained by the computer itself during a complete run; Learning machines (adaptive control systems G05B 13/00;artificial intelligence G06N)

Abstract

A method for determining driving policies for a vehicle includes: receiving, in real-time during a trip of a vehicle, at least a set of input multimedia content elements captured by at least one sensor deployed in proximity to the vehicle, determining a plurality of possible future scenarios based at least on the set of input multimedia content elements, determining a probability score for each of the plurality of possible future scenarios, determining at least one driving policy according to at least the probability score for at least one of the plurality of possible future scenarios, and controlling the vehicle according to the at least one driving policy.

IPC Classes  ?

• G08G 1/005 - Traffic control systems for road vehicles including pedestrian guidance indicator
• G08G 1/01 - Detecting movement of traffic to be counted or controlled
• G08G 1/16 - Anti-collision systems
• G08G 7/02 - Anti-collision systems
• G08G 9/02 - Anti-collision systems
• B60W 40/09 - Driving style or behaviour
• G01C 21/36 - Input/output arrangements for on-board computers

Abstract

A method and system for generating a customized augmented reality environment are provided. The method includes causing generation of at least one signature for at least one multimedia content; determining, based on the generated at least one signature, a selection of at least one augmented reality character, wherein each augmented reality character is associated with a character signature; identifying at least one potential placement location in the at least one multimedia content element, wherein each potential placement location is associated with at least a portion of the generated at least one signature; correlating between the at least one potential placement location signature portion and the at least one character signature to select, for each augmented reality character, a placement location in the at least one multimedia content element; and generating a customized augmented reality environment, wherein the customized augmented reality environment includes each augmented reality character superimposed on the at least one multimedia content element at the respective placement location.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions

Abstract

A system and method for providing augmented reality challenges are provided. The method includes obtaining at least one multimedia content element; causing generation of at least one signature for each obtained multimedia content element; determining, based on the generated signatures, at least one augmented reality challenge; identifying, based on the determined at least one augmented reality challenge, at least one augmented reality object; creating at least one challenge multimedia content element by causing addition of the at least one augmented reality object to the obtained at least one multimedia content element; and causing a display of the created at least one challenge multimedia content element.

IPC Classes  ?

• G06T 17/00 - 3D modelling for computer graphics
• G09G 5/377 - Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the display of individual graphic patterns using a bit-mapped memory - Details of the operation on graphic patterns for mixing or overlaying two or more graphic patterns

Abstract

A system and method for clustering multimedia content. The method includes: detecting at least one clustering trigger event related to at least one multimedia content element to be clustered; generating at least one signature for the at least one multimedia content element, each signature representing at least a portion of the at least one multimedia content element; determining, based on the generated at least one signature, at least one multimedia content element cluster, wherein each multimedia content element cluster includes a plurality of clustered multimedia content elements sharing at least one common concept with the at least one multimedia content element; and adding, to each determined cluster, the at least one multimedia content element.

IPC Classes  ?

• G06F 17/30 - Information retrieval; Database structures therefor

Abstract

A system and method for method for identifying key points in a multimedia data element (MMDE). The method includes: identifying, via a computer vision system, a plurality of candidate key points in the MMDE, wherein a size of each candidate key point is equal to a predetermined size, wherein a scale of each candidate key point is equal to a predetermined scale; analyzing the plurality of candidate key points to determine a set of properties for each candidate key point; comparing the sets of properties of the plurality of candidate key points; and selecting, based on the comparison, a plurality of key points from among the candidate key points.

IPC Classes  ?

• G06K 9/46 - Extraction of features or characteristics of the image
• G06T 7/00 - Image analysis

Abstract

A method and apparatus for symbol-space based compression of patterns are provided. The method comprises receiving an input sequence, the input sequence being of a first length and comprising a plurality of symbols; extracting all common patterns within the input sequence, wherein a common pattern includes at least two symbols; generating an output sequence responsive of the extraction of all common patterns, wherein the output sequence has a second length that is shorter than the first length; and storing in a memory the output sequence as a data layer, wherein the output sequence is provided as a new input sequence for a subsequent generation of a data layer.

IPC Classes  ?

• G06F 12/00 - Accessing, addressing or allocating within memory systems or architectures

Abstract

Content-based clustering, recognition, classification and search of high volumes of multimedia data in real-time. The invention is dedicated to real¬ time fast generation of signatures (4) to high-volume of multimedia content- segments, based on relevant audio and visual signals (2), and to scalable matching (9) of signatures (4) of high-volume database (8) of content- segments' signatures (7). The invention can be implemented in any applications which involve large-scale content-based clustering, recognition and classification of multimedia data, such as, content-tracking, video filtering, multimedia taxonomy generation, video fingerprinting, speech-to-text, audio classification, object recognition, video search and any other application requiring content-based signatures generation and matching for large content volumes such as, web and other large-scale databases.

IPC Classes  ?

• G06F 17/30 - Information retrieval; Database structures therefor

Abstract

A computing arrangement for identification of a current temporal input against one or more learned signals. The arrangement comprising a number of computational cores, each core comprises properties having at least some statistical independency from other of the computational, the properties being set independently of each other core, each core being able to independently produce an output indicating recognition of a previously learned signal, and at least one decision unit for receiving the produced outputs from the number of computational cores and making an identification of the current temporal input based the produced outputs.

IPC Classes  ?

• G06N 3/06 - Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
• G06N 3/063 - Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
• G06N 3/04 - Architecture, e.g. interconnection topology
• G06F 15/80 - Architectures of general purpose stored program computers comprising an array of processing units with common control, e.g. single instruction multiple data processors