Abstract: A smart speaker power controller may be configured to receive power conforming to one of a plurality of power modes from an input power source. The power controller may be further configured to communicate the power mode to at least one component of a processing system or at least one component of an audio system for operating the smart speaker according to the received power mode, including determining a current limit of a power converter; determining a shutdown voltage threshold and safely shutting down the smart speaker if the input voltage falls below the threshold, and/or modifying audio operation of the smart speaker in response to the power mode. The smart speaker can further include an audio power supply controller configured to monitor energy required to reproduce an audio signal and to servo a power supply voltage provided to an audio amplifier in response to this energy level.

Abstract: A smart speaker power controller may be configured to receive power conforming to one of a plurality of power modes from an input power source. The power controller may be further configured to communicate the power mode to at least one component of a processing system or at least one component of an audio system for operating the smart speaker according to the received power mode, including determining a current limit of a power converter; determining a shutdown voltage threshold and safely shutting down the smart speaker if the input voltage falls below the threshold, and/or modifying audio operation of the smart speaker in response to the power mode. The smart speaker can further include an audio power supply controller configured to monitor energy required to reproduce an audio signal and to servo a power supply voltage provided to an audio amplifier in response to this energy level.

Abstract: Disclosed methods and system describe a server that uses AI modeling to predict negative cash flow at a user level. The server periodically retrieves data associated with the user, the data comprising monetary attributes associated with one or more accounts of the user; executes a deep neural network model trained based upon historical data associated with at least a subset of the users configured to predict a negative cash flow in one or more accounts of the user, a depth of the negative cash flow, and a duration of the negative cash flow; transmits, to a second server, the predicted values, whereby when the second server determines that a likelihood of account needs satisfies a threshold, the second server establishes an electronic communication session with an electronic device of the user; trains the deep neural network when the second server establishes the electronic communication session.

Abstract: Disclosed methods and system describe a server that uses AI modeling to predict negative cash flow at a user level. The server periodically retrieves data associated with the user, the data comprising monetary attributes associated with one or more accounts of the user; executes a deep neural network model trained based upon historical data associated with at least a subset of the users configured to predict a negative cash flow in one or more accounts of the user, a depth of the negative cash flow, and a duration of the negative cash flow; transmits, to a second server, the predicted values, whereby when the second server determines that a likelihood of account needs satisfies a threshold, the second server establishes an electronic communication session with an electronic device of the user; trains the deep neural network when the second server establishes the electronic communication session.

Abstract: A computerized system for managing a parking lot includes: a beacon in one-way, or location sensor in two-way, communication with a smart device for locating the smart device without it having to determine its own location, a vehicle sensor for sensing the presence of a vehicle, and a computer-implemented server operable to determine from the beacon's identification or receive from the location sensor the location of the smart device. The server authorizes entry or exit of the vehicle when a smart device status indicates acceptance, and the smart device and the vehicle are both at a same appropriate location. The server updates the smart device status after a payment transaction. Entry or exit may be authorized by opening a barrier, displaying an authorization message, communicating a message to the smart device, and/or not issuing a non-authorization alert. The server may receive reservations, and may communicate lot occupancy to third-party systems.

Abstract: A smart speaker power controller may be configured to receive power conforming to one of a plurality of power modes from an input power source. The power controller may be further configured to communicate the power mode to at least one component of a processing system or at least one component of an audio system for operating the smart speaker according to the received power mode, including determining a current limit of a power converter; determining a shutdown voltage threshold and safely shutting down the smart speaker if the input voltage falls below the threshold, and/or modifying audio operation of the smart speaker in response to the power mode. The smart speaker can further include an audio power supply controller configured to monitor energy required to reproduce an audio signal and to servo a power supply voltage provided to an audio amplifier in response to this energy level.

Abstract: Disclosed methods and system describe a server that uses AI modeling to predict negative cash flow at a user level. The server periodically retrieves data associated with the user, the data comprising monetary attributes associated with one or more accounts of the user; executes a deep neural network model trained based upon historical data associated with at least a subset of the users configured to predict a negative cash flow in one or more accounts of the user, a depth of the negative cash flow, and a duration of the negative cash flow; transmits, to a second server, the predicted values, whereby when the second server determines that a likelihood of account needs satisfies a threshold, the second server establishes an electronic communication session with an electronic device of the user; trains the deep neural network when the second server establishes the electronic communication session.

Abstract: Techniques for leveraging existing statistical prediction models are provided. A first statistical prediction model is generated for a content item. An instruction is received to create a clone from the content item. In response to receiving the instruction, the clone is created based on attributes of the content item. A second statistical prediction model that is different than the first statistical prediction model is generated for the clone. In response to receiving a request for content, the clone is identified as relevant to the first request. A similarity between (1) first content of the content item and (2) second content of the clone is determined. If the similarity exceeds a similarity threshold, then the first statistical prediction model is used to generate a prediction of an entity user selection rate associated with the clone. Otherwise, the second statistical prediction model is used to generate the prediction.

Abstract: A computerized system for managing a parking lot includes: a beacon in one-way, or location sensor in two-way, communication with a smart device for locating the smart device without it having to determine its own location, a vehicle sensor for sensing the presence of a vehicle, and a computer-implemented server operable to determine from the beacon's identification or receive from the location sensor the location of the smart device. The server authorizes entry or exit of the vehicle when a smart device status indicates acceptance, and the smart device and the vehicle are both at a same appropriate location. The server updates the smart device status after a payment transaction. Entry or exit may be authorized by opening a barrier, displaying an authorization message, communicating a message to the smart device, and/or not issuing a non-authorization alert. The server may receive reservations, and may communicate lot occupancy to third-party systems.

Abstract: Generally discussed herein are methods, systems, and apparatuses for tracking user interaction with sponsored and/or unsponsored content. A method can include receiving a tracking event packet including data fields comprising a packet identification, a tracking event identifier, a content identifier, a cost, a campaign identifier, and/or an advertiser identifier, determining whether the tracking event packet is a duplicate based on the packet identification, aggregating non-duplicate tracking event packets by advertiser identification such that packets with advertiser identifications that hash to a same value are aggregated together, and transferring aggregated tracking event packets to a first database and a second database, the first database includes data stored for analytics and the second database includes data stored for billing and campaign performance monitoring.

Abstract: Techniques for leveraging existing statistical prediction models are provided. A first statistical prediction model is generated for a content item. An instruction is received to create a clone from the content item. In response to receiving the instruction, the clone is created based on attributes of the content item. A second statistical prediction model that is different than the first statistical prediction model is generated for the clone. In response to receiving a request for content, the clone is identified as relevant to the first request. A similarity between (1) first content of the content item and (2) second content of the clone is determined. If the similarity exceeds a similarity threshold, then the first statistical prediction model is used to generate a prediction of an entity user selection rate associated with the clone. Otherwise, the second statistical prediction model is used to generate the prediction.

Abstract: A computerized system for managing a parking lot includes: a beacon in one-way, or location sensor in two-way, communication with a smart device for locating the smart device without it having to determine its own location, a vehicle sensor for sensing the presence of a vehicle, and a computer-implemented server operable to determine from the beacon's identification or receive from the location sensor the location of the smart device. The server authorizes entry or exit of the vehicle when a smart device status indicates acceptance, and the smart device and the vehicle are both at a same appropriate location. The server updates the smart device status after a payment transaction. Entry or exit may be authorized by opening a barrier, displaying an authorization message, communicating a message to the smart device, and/or not issuing a non-authorization alert. The server may receive reservations, and may communicate lot occupancy to third-party systems.

Abstract: Generally discussed herein are methods, systems, and apparatuses for tracking user interaction with sponsored and/or unsponsored content.

Abstract: Generally discussed herein are methods, systems, and apparatuses for tracking user interaction with sponsored and/or unsponsored content. A method can include receiving a tracking event packet including data fields comprising a packet identification, a tracking event identifier, a content identifier, a cost, a campaign identifier, and/or an advertiser identifier, determining whether the tracking event packet is a duplicate based on the packet identification, aggregating non-duplicate tracking event packets by advertiser identification such that packets with advertiser identifications that hash to a same value are aggregated together, and transferring aggregated tracking event packets to a first database and a second database, the first database includes data stored for analytics and the second database includes data stored for billing and campaign performance monitoring.

Abstract: A machine may be configured to generate metrics or billing reports for online advertising. For example, the machine accesses, in real time, an event cost value associated with an event of consumption of an online ad displayed on behalf of an advertiser associated with an account identifier. The machine accesses, in real time, a remaining budget value associated with the account identifier. The machine determines, in real time, that the event cost value exceeds the remaining budget value. The machine generates, in real time, an adjusted event cost value to correspond to the remaining budget value based on the determining that the event cost value exceeds the remaining budget value. The machine generates, in real time, a real-time billing report including the adjusted event cost value.

Abstract: The present invention is related to a database management system that is capable of autonomous dynamic ontology management through soft classing. The present invention is further related to a method of database management by dividing attribute data, e.g., price=10 dollars, into class elements containing data, e.g., attribute name=price, type=numeric, default units=dollars, and entry elements containing data, e.g., attribute value=10, to permit dynamic ontology management and evolution in the database through soft classing.

Abstract: The present invention is related to a database management system that is capable of autonomous dynamic ontology management through soft classing. The present invention is further related to a method of database management by dividing attribute data, e.g., price=10 dollars, into class elements containing data, e.g., attribute name=price, type=numeric, default units=dollars, and entry elements containing data, e.g., attribute value=10, to permit dynamic ontology management and evolution in the database through soft classing.

Abstract: The present invention is related to a database management system that is capable of autonomous dynamic ontology management through soft classing. The present invention is further related to a method of database management by dividing attribute data, e.g., price=10 dollars, into class elements containing data, e.g., attribute name=price, type=numeric, default units=dollars, and entry elements containing data, e.g., attribute value=10, to permit dynamic ontology management and evolution in the database through soft classing.

Abstract: The present invention is related to a database management system that is capable of autonomous dynamic ontology management through soft classing. The present invention is further related to a method of database management by dividing attribute data, e.g., price=10 dollars, into class elements containing data, e.g., attribute name=price, type=numeric, default units=dollars, and entry elements containing data, e.g., attribute value=10, to permit dynamic ontology management and evolution in the database through soft classing.

Abstract: Digitally encoded presentations are provided at the request and convenience of receivers associated with a data distribution system. The problem of reliably satisfying large numbers of randomly occurring receiver demands for digitally encoded presentations, particularly from a single storage copy of the presentation, and particularly for linear presentations, is addressed. The invention may be embodied in a system which includes a repository of digitally encoded presentations, cache memory for holding presentations which are being supplied to receivers, and a multicasting network for connecting the system to receivers. By grouping receivers into receiving groups for receiving multicasts of presentation segments, the system can satisfy the requests of any number of individual receivers, irrespective of other receivers receiving the presentation.