Abstract: A system for addressing failure in an autonomous agent includes a driving subsystem, a control subsystem, a central computing subsystem, and an autonomous vehicle (AV) sensor subsystem. The system can optionally additionally include a power subsystem, a vehicle chassis subsystem, a communication subsystem, a distributed computing and/or processing subsystem, a supplementary sensor subsystem, and/or any other components. A method for addressing failure can include any or all of: detecting and responding to a failure; and operating the vehicle. Additionally or alternatively, the method 200 can include any other processes.

Abstract: A system for addressing failure in an autonomous agent includes a driving subsystem, a control subsystem, a central computing subsystem, and an autonomous vehicle (AV) sensor subsystem. The system can optionally additionally include a power subsystem, a vehicle chassis subsystem, a communication subsystem, a distributed computing and/or processing subsystem, a supplementary sensor subsystem, and/or any other components. A method for addressing failure can include any or all of: detecting and responding to a failure; and operating the vehicle. Additionally or alternatively, the method 200 can include any other processes.

Abstract: Systems and methods for providing various Human Resources (HR) services to a company are provided. A method, according to one implementation, includes the step of monitoring employment policies and updates thereto, the employment policies representing employment laws, rules, and/or regulations applicable to each of a plurality of jurisdictions (e.g., countries, states, provinces, etc.). The method also includes the step of displaying multiple options and fields on one or more screens of a User Interface (UI) of a remote user device allowing a user to enter information defining a job to be executed by a job candidate or new employee. Also, the method includes the step of detecting whether the information entered by the user complies with the employment policies.

Abstract: A system for addressing failure in an autonomous agent includes a driving subsystem, a control subsystem, a central computing subsystem, and an autonomous vehicle (AV) sensor subsystem. The system can optionally additionally include a power subsystem, a vehicle chassis subsystem, a communication subsystem, a distributed computing and/or processing subsystem, a supplementary sensor subsystem, and/or any other components. A method for addressing failure can include any or all of: detecting and responding to a failure; and operating the vehicle. Additionally or alternatively, the method 200 can include any other processes.

Abstract: A system for addressing failure in an autonomous agent includes a driving subsystem, a control subsystem, a central computing subsystem, and an autonomous vehicle (AV) sensor subsystem. The system can optionally additionally include a power subsystem, a vehicle chassis subsystem, a communication subsystem, a distributed computing and/or processing subsystem, a supplementary sensor subsystem, and/or any other components. A method for addressing failure can include any or all of: detecting and responding to a failure; and operating the vehicle. Additionally or alternatively, the method 200 can include any other processes.

Abstract: A system for addressing failure in an autonomous agent includes a driving subsystem, a control subsystem, a central computing subsystem, and an autonomous vehicle (AV) sensor subsystem. The system can optionally additionally include a power subsystem, a vehicle chassis subsystem, a communication subsystem, a distributed computing and/or processing subsystem, a supplementary sensor subsystem, and/or any other components. A method for addressing failure can include any or all of: detecting and responding to a failure; and operating the vehicle. Additionally or alternatively, the method 200 can include any other processes.

Abstract: A method including training a machine learning algorithm by iteratively adjusting, by a computer processor, adjusted matching parameters to increase a correlation between approval statistics of lending decisions and risk profiles. The risk profiles represent probabilities of businesses defaulting on a loan. The probabilities are derived from usage statistics of a business management application (BMA) used by the businesses. Iteratively adjusting continues until reaching a threshold correlation between the approval statistics and the lending decisions and the risk profiles. Training generates an updated machine learning algorithm. An updated risk score for a business entity is generated using a number of logins to the BMA made by the business entity.

Abstract: The method and system involves instant loan decisions by generating a risk profile of a small business (SMB). The risk profile is generated based on accounting data and other third party business management application (BMA) data of the SMB. In particular, the accounting data and other third party BMA data are retrieved from a BMA (e.g., accounting application, payroll application, tax preparation application, personnel application, etc.) as a software-as-an-service (SaaS) used by the SMB. Specifically, the risk profile represents the likelihood of the SMB to be delinquent and/or to default on a loan. The risk profile is then provided to a lender for making an expedient lending decision with respect to the SMB. In addition, statistics of lenders' lending decisions based on provided risk profiles are analyzed to generate a correlation. Accordingly, the algorithm(s) used to generate the risk profile from the accounting data and other third party BMA data are adjusted to maximize the correlation.

Abstract: A method for modeling risk of a derogatory financial event. The method includes generating a risk profile of a small business (SMB) using a risk model based on accounting data and other third party business management application (BMA) data of the SMB. In particular, the risk model is generated using a training data set that includes accounting data and other third party BMA data of multiple SMBs over particular time periods related to historic derogatory events (e.g., to be delinquent and/or to default on a loan) of these SMBs. Generated using the risk model, the risk profile of the SMB represents the likelihood of a derogatory financial event occurring to the SMB.

Abstract: A method for generating a business health score of a business entity that includes identifying tools used to manage the business entity, obtaining business information from the tools, filtering the business information into at least one data category to obtain categorized business information, populating the categorized business information into a data silo, and analyzing, by a computer processor, the categorized business information in the data silo to create a composite business factor. The method also includes applying an algorithm to the composite business factor to generate a result, generating, based on the result, the business health score of the business entity, and providing the business health score to an interested entity.

Abstract: A method and system provide reduced and personalized versions of webpages to users lacking sufficient computing resources to load the full versions of the webpages in a satisfactorily short amount of time. The method and system receives a request from a user to access a webpage, analyze the computing resources of the user, and determine whether the user is able to load the full version of the webpage quickly. If the user is able to load the full version of the webpage quickly, then the method and system outputs the full version of the webpage to the user. If the user is unlikely able to load the full version of the webpage quickly, then the method and system outputs a reduced version of the webpage retaining the portions most likely to be relevant to the user based on an analysis of user data related to the user.

Abstract: A method for cash forecasting creates a plurality of event streams associated with a user of an online accounting service, identifies a first pattern in a first event stream that is a commitment and a second pattern in a second event stream that is a repeated pattern, generates a characterization for each of the plurality of event streams based on each identified pattern for the event stream, predicts one or more expected cash payments and one or more corresponding expected dates for each of the event streams using the characterization for the event stream and a forecasting model, receives a query related to cash flow through an application program interface (API), and responds to the query based on the one or more of the expected cash payments, the corresponding expected dates, and the one or more measures of uncertainty, to the query.

Abstract: A technique for providing information about financial transactions is described. This information technique allows a user, who has conducted financial transactions with one or more other parties, to access information about these financial transactions that is maintained by a provider of financial software, which is used by the one or more other parties to manage the information about the financial transactions. In particular, in this technique, in response to an access request from the user, a portal (such as a web page), which includes the information about the financial transactions between the user and the one or more other parties, is provided by the provider of the financial software to the user.