Abstract: A system for transfer path optimization is disclosed. The system comprises a computing device configured to receive a plurality of inputs from a user device at a current geographical location. The computing device is configured to generate a plurality of originators as function of the plurality of inputs, by identifying originators within a threshold distance relative to current geographical location of the user device. The computing device is configured to generate a fast transfer path. Computing device is configured to pair the fast transfer path with the first component and to assign a transfer agent to the fast transfer path. Computing device is configured to generate a second component path to transfer the second component. A method for transfer path optimization is also disclosed.

Abstract: Systems and methods for forward market price prediction and sale of energy storage capacity are disclosed. An example transaction-enabling system may include a fleet of machines having an aggregate energy storage capacity; and a controller, comprising: an external data circuit structured to monitor an external data source and collect data from the external data source; an expert system circuit structured to predict a forward market price for energy storage capacity based on the collected data and the aggregate energy storage capacity; and a smart contract circuit structured to automatically sell at least a subset of the aggregate energy storage capacity on a forward market for energy storage capacity in response to the predicted forward market price.

Abstract: The present disclosure describes transaction-enabling systems and methods for enabling machine resource transactions. A system can include a machine having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement; and a controller. The controller can include a resource requirement circuit to determine an amount of a resource for the machine to service task requirement, a resource market circuit to access a resource market, and a resource distribution circuit to execute a transaction of the resource on the resource market in response to the determined amount of the resource.

Abstract: A method includes generating a plurality of training vectors relating to different respective historical service requests generated by respective autonomous vehicles, each of the training vectors including respective features associated with the historical request to which the training vector relates. The method further includes, using the training vectors, training a model configured to generate a prediction relating to one or more future service requests, generating the prediction using the model, and outputting the generated prediction. Other embodiments are also described.

Abstract: Apparatus and methods for collecting information may include receiving one or more inputs of information related to a business experience. In addition, the apparatus and methods may include storing the received business information. The methods may also include analyzing the received information to generate one or more targeted recommendations; and forwarding the one or more targeted recommendations to management of the business.

Abstract: Systems and methods for forward market renewable energy credit prediction from business entity behavior data are disclosed. An example transaction-enabling system may include a forward market circuit to access a forward energy credit market and a market forecasting circuit to automatically generate a forecast for a forward market price of an energy credit in the forward energy credit market. The example system may include wherein the forecast is based at least in part on a business entity behavior collected from at least one business entity behavioral data source, and wherein the energy credit comprises a renewable energy credit associated a renewable energy system. The example system may further include a smart contract circuit to perform at least one of selling the renewable energy credit or purchasing the renewable energy credit on the forward energy credit market in response to the forecasted forward market price.

Abstract: The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit structured to determine an amount of a resource for each of the machines to service at least one of the task requirements, a resource market circuit to access a resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the resource market in response to the determined amount of the resource for each of the machines.

Abstract: Transaction-enabling systems and methods are disclosed. A system may include a controller to interpret a resource utilization requirement for a task system and a plurality of external data sources. The system may further include an expert system to predict a forward market price for a resource in response to the resource utilization requirement and the plurality of external data sources. Then, in response to the predicted forward market price, the controller may execute a transaction on a resource market.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for testing a plurality of variants among a plurality of users. One of the methods includes: determining a spatial granularity to divide an area into a plurality of grid cells; randomly splitting the plurality of grid cells into a plurality of testing groups, wherein a quantity of the plurality of testing groups is determined based on a quantity of the multiple versions of the feature to be tested; determining a temporal granularity to divide a testing period into a plurality of testing intervals; during each of the plurality of testing intervals, respectively assigning the multiple versions of the feature to the plurality of testing groups; and obtaining a treatment effect for each of the multiple versions of the feature and determining an optimal version of the feature.

Abstract: Systems and methods for prediction of forward market renewable energy credit from automated agent behavioral data are disclosed. An example transaction-enabling system may include a forward market circuit to access a forward energy credit market, and a market forecasting circuit to automatically generate a forecast for a forward market price of an energy credit in the forward energy credit market, based in part on an automated agent behavior collected from an automated agent behavioral data source. The example system may further include wherein the energy credit comprises a renewable energy credit from a renewable energy system, and a smart contract circuit to sell the renewable energy credit or purchase the renewable energy credit on the forward energy credit market in response to the forecasted forward market price.

Abstract: Techniques for leveraging data in a data marketplace environment are provided. For example, a method comprises the following steps. A representation of one or more data valuations for a given data set is obtained. The representation of the one or more data valuations for the given data set is converted into a value for presentation to a data marketplace environment. The data marketplace environment comprises one or more data marketplace protocols that each enable one or more data consumers to obtain data. The method brokers a transfer of the given data set through at least one of the data marketplace protocols to at least one data consumer. The method manages transfer of the given data set to the at least one data consumer and receipt of a result of the transfer from the at least one data consumer.

Abstract: Systems and methods for predicting forward market pricing for renewable energy credit based on human behavioral data are disclosed. An example transaction-enabling system may include a forward market circuit to access a forward energy credit market and a market forecasting circuit to automatically generate a forecast for a forward market price of an energy credit in the forward energy credit market where the forecast is based at least in part on a human behavior information collected from at least one human behavioral data source. The example system may further include wherein the energy credit includes a renewable energy credit associated with a renewable energy system, and a smart contract circuit to perform at least one of selling the renewable energy credit or purchasing the renewable energy credit on the forward energy credit market in response to the forecasted forward market price of the energy credit.

Abstract: An automatic service monitor in an information-technology environment performs regular search queries against generated machine data to derive performance measurements. The information technology environment is defined in terms of services provided by entities, and the performance measurements are defined as key performance indicators (KPIs) of the services. Generated machine data used by the search queries pertain to the entities performing the service. Definitional information for the services, entities, and KPIs is administered by a user to control the operation of the service monitor. Various aspects of such definitional information as well as related performance measurement information may be presented in a unified console display tailored to, and organized around, a particular service. The console display may serve as a central launch point by supporting user interaction to navigate to other specialized monitoring interfaces.

Abstract: Techniques for scoring data items using a machine-learned model are provided. In one technique, multiple skills are identifying based on a job posting. Multiple attribute values of the job posting are identified. For each identified skill, multiple probabilities are identified, each probability corresponding to a different attribute value of the identified attribute values. The probabilities are input into a machine-learned model to generate multiple scores. Multiple skills of a candidate user are identified. An affinity score between the job posting and the candidate user is generated based the scores and the skills of the candidate user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for technology assessment and selection. In some implementations, study data indicating parameters of a research study or an objective of a research study is received. Types of data to be collected during the research study are identified. Technology options that each represent one or more technology items that can provide the data to be collected are identified. A suitability score for each of the technology options is determined. A selection is made from among the technology options based on the suitability scores. Output data that indicates the selected technology options for the research study is provided.

Abstract: A method and system for generating Customer Decision Tree (CDT) for an entity in accordance with an attribute value (AV) based demand transfer estimation for a product category using machine learning, is disclosed. The method includes aggregating very high volume of data associated with a plurality of AVs of a product category at a plurality of aggregation levels. Further, generating a data matrix, which represents data is a structured format for machine learning, at a predefined aggregation level for the product category and generating a prediction model with the data matrix to determine predicted AV sales for each AV at the predefined aggregation level. Further, optimizing the trained prediction model. Thereafter, generate the CDT utilizing the optimized prediction model, a Demand Transfer (DT) estimator, a scenario generator and a hierarchy generator. Machine learning based DT is more accurate, effectively generating more accurate CDT tree.

Abstract: Described is a method for work assignment queue elimination. The method includes maintaining at least one data structure including an ordered list of ticket assignment rules and assignment result metrics, receiving a ticket indicating a system problem, assigning the ticket based on the ordered list of ticket assignment rules, the system problem and the assignment result metrics, collecting metrics based on the ticket assignment, and revising the assignment result metrics based on the collected metrics.

Abstract: A service monitoring system (SMS) produces key performance indicator (KPI) scores that indicate the performance of a service. To produce the KPI scores, the SMS may process the data for a large number of machine entities that perform the service. This data can be processed on a per-entity basis to produce a per-entity KPI score representing the contribution of a particular machine to the overall KPI. The per-entity KPI scores can be transformed to statistical representations which can be visualized as a distribution stream graph. The visualization may be presented with interactive aspects.

Abstract: An automatic service monitor in an information technology environment has its operation controlled by information that, in part, defines entities that perform services and defines key performance indicators (KPIs) that indicate measures of performance of the services. Additional information controls the operation of the service monitor with respect to identifying and adapting for KPIs based on the non-normal data caused by maintenance work or other causes. Such adaptation may include changes in how reported information appears to the user.

Abstract: A method of aiding the design of a data center is disclosed. In one aspect, the method refers to generating a list of components from a library that satisfy a defined list of needs.