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公开(公告)号：US20190236598A1
公开(公告)日：2019-08-01
申请号：US16177300
申请日：2018-10-31
Applicant: salesforce.com, inc.
Inventor： Prithvi Krishnan Padmanabhan
CPC classification number: G06Q20/3823 , G06N20/00 , G06Q20/383 , G06Q20/4016 , H04L9/0637
Abstract: Systems, methods, and apparatuses for implementing machine learning models for smart contracts using distributed ledger technologies in a cloud based computing environment are described herein. For example, according to one embodiment there is a system having at least a processor and a memory therein executing within a host organization and having therein: means for operating a blockchain interface to a blockchain on behalf of a plurality of tenants of the host organization, in which each one of the plurality of tenants operate as a participating node with access to the blockchain; receiving historical data from each of the participating nodes on the blockchain; generating a new machine learning model at the host organization by inputting the historical data received from the participating nodes into a neural network of a machine learning platform operating at the host organization; receiving a consensus agreement from the plurality of participating nodes; deploying the new machine learning model to the participating nodes as a component of a smart contract to be executed in fulfillment of the smart contract transactions; receiving a transaction at the blockchain and responsively triggering the smart contract to process the transaction onto the blockchain; and executing the smart contract which includes executing the new machine learning model as part of the smart contract. Other related embodiments are disclosed.
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公开(公告)号：US20190236559A1
公开(公告)日：2019-08-01
申请号：US15932092
申请日：2018-01-31
Applicant: Salesforce.com, inc.
Inventor： Prithvi Krishnan Padmanabhan
CPC classification number: G06Q20/06 , G06F8/427 , G06F8/51 , G06F21/44 , G06Q20/40 , H04L9/0637 , H04L9/0643 , H04L67/104 , H04L2209/38 , H04L2209/56
Abstract: Systems, methods, and apparatuses for implementing smart flow contracts using distributed ledger technologies in a cloud based computing environment are described herein. For example, according to one embodiment there is a system having at least a processor and a memory therein executing within a host organization and having therein: means for operating a blockchain interface to a blockchain on behalf of a plurality of tenants of the host organization, wherein each of the plurality of tenants are participating nodes with the blockchain; means for receiving a login request from a user device; means for authenticating the user device with the host organization; means for receiving input from the user device indicating a plurality of smart contract blocks; means for translating each of the smart contract blocks into a native programming language to form a smart contract to execute via the blockchain; and means for transacting the smart contract onto the blockchain. Other related embodiments are disclosed.
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公开(公告)号：US20190236466A1
公开(公告)日：2019-08-01
申请号：US15883095
申请日：2018-01-30
Applicant: salesforce.com, inc.
Inventor： Daniel Thomas HARRISON
CPC classification number: G06N5/043 , G06F16/27 , G06Q30/0202 , G06Q30/0251 , G06Q30/0277 , G06Q50/01
Abstract: A method and a cloud-computing architecture for enabling dynamic access of an artificial intelligence engine are described. A record that includes a set of one or more fields is stored in a database. A first field from the set of fields includes an identification of an artificial intelligence (AI) engine and one or more additional fields from the set of fields respectively include one or more parameters for the AI engine. The record is accesses causing the AI engine to run with the one or more parameters. As a result of the AI engine running with the one or more parameters upon access of the record, a desired predicted output is obtained.
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公开(公告)号：US20190236460A1
公开(公告)日：2019-08-01
申请号：US15882134
申请日：2018-01-29
Applicant: salesforce.com, inc.
Inventor： Arun Kumar Jagota , Dmytro Kudriavtsev , Rakesh Ganapathi Karanth
CPC classification number: G06N5/025 , G06F16/951 , G06N20/00
Abstract: A training dataset having training instances is determined. Each training instance comprises first and second records and a second record and a label indicate whether there is a match between the first and second records. A matching score vector is determined for each such training instance, and comprises components storing match scores for extracted features from field values in the first and second records. Based on matching score vectors and a match objective function, match score thresholds are determined for the extracted features. Match rule(s) each of which comprises predicate(s) are generated. Each predicate makes a predication on whether two records match by comparing a match score derived from the two records against a match score threshold.
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公开(公告)号：US20190236188A1
公开(公告)日：2019-08-01
申请号：US15885559
申请日：2018-01-31
Applicant: salesforce.com, inc.
Inventor： William J. McKenna
IPC: G06F17/30
CPC classification number: G06F16/24544 , G06F16/2453 , G06F16/24565
Abstract: Techniques are disclosed relating to database query optimizers. In some embodiments, a query optimizer of a database system receives a first query including a first constraint that restricts selection of a set of execution plans available to implement the first query. The first constraint identifies, at least, a first option and a second option to implement a clause in the first query. The query optimizer evaluates, based on the first constraint, a first execution plan that includes performance of the first option and a second execution plan that includes performance of the second option. Based on the evaluating, the query optimizer selects one of the first and second execution plans to implement the first query. The query optimizer causes execution of the selected execution plan.
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Patent Agency Ranking
806.发明申请公开(公告)号：US20190236184A1
公开(公告)日：2019-08-01
申请号：US15884322
申请日：2018-01-30
Applicant: salesforce.com, inc.
Inventor： Danil DVINOV , Parth Vijay VAISHNAV , Chenghung KER
IPC: G06F17/30
Abstract: Methods for splitting a plurality of records into subsets for parallel processing by separate threads are disclosed. In one embodiment, a plurality of records are added to a database. The adding includes tracking, for each unique value found in the plurality of records within a selected one of the sequence of fields, a statistic based on the values found in the plurality of records within a next one of the sequence of fields. Then a plurality of queries are generated, each includes a row value constructor (RVC) with a logical operation, a specific one of the unique values found within the selected one of the sequence of fields, and, for that specific value, the tracked statistic. Then a plurality of threads are caused to execute that each submit one of the queries and operate on a subset of the plurality of records responsive to execution of that query.
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公开(公告)号：US20190236138A1
公开(公告)日：2019-08-01
申请号：US15885355
申请日：2018-01-31
Applicant: salesforce.com, inc.
Inventor： Molly MAHAR , Jonathan Rico MORALES , Jacob MUMM , Karson MILLER
CPC classification number: G06F17/2785 , H04L51/02
Abstract: This disclosure relates to configuration tools for interactive agents, sometimes referred to as bots, chatbots, virtual robots, or talkbots. Such interactive agents utilize slots for organizing and storing data received as inputs and displayed as outputs. These slots can be configured such that a slot is temporary and does not persist beyond its source dialog. Slots can also be configured such that a slot is pre-populated with information contain in incoming passed parameters.
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公开(公告)号：US20190235998A1
公开(公告)日：2019-08-01
申请号：US15885240
申请日：2018-01-31
Applicant: salesforce.com, inc.
Inventor： Hui S. Fisher
CPC classification number: G06F11/3688 , G06F16/9566 , G06F16/958
Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for end-to-end user interface component testing in a database system. More specifically, techniques for efficient automation of end-to-end user interface component testing are described.
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公开(公告)号：US20190235989A1
公开(公告)日：2019-08-01
申请号：US15885720
申请日：2018-01-31
Applicant: salesforce.com, inc.
Inventor： Josh Lewis , Andrew Appleton , Guðmundur Bjarni Ólafsson , Ike DeLorenzo , Hector Simpson
IPC: G06F11/36
CPC classification number: G06F11/3612 , G06F11/3664 , G06F11/3684 , G06F11/3688
Abstract: A method for analysis of software programs or applications is disclosed. The method may include an execution broker application executing on a compute resource included in a computer network, receiving application code and analysis information and generating an execution environment on a different compute resource included in the computer network. The execution broker application may initiate performance of an analysis of the application code using the execution environment and storage of a result of the analysis on another compute resource included in the computer network. In response to determining the analysis has completed, the execution broker may deactivate the execution environment.
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公开(公告)号：US20190235712A1
公开(公告)日：2019-08-01
申请号：US15884780
申请日：2018-01-31
Applicant: salesforce.com, inc.
Inventor： Yuseung KIM , Behzad Richey , Naga Siva Chandra Prasad Pamidi , Juyong Kim
IPC: G06F3/0484 , G06F17/30 , G06F3/0482
CPC classification number: G06F3/0484 , G06F3/0482 , G06F16/252 , G06F16/26
Abstract: Disclosed herein are system, method, and computer program product embodiments for quickly switching between multiple dashboards of an application. An embodiment operates by tracking changes made to a first dashboard of an application. The embodiment receives a selection for a second dashboard of the application. The embodiment stores a first data set and a first data state of the first dashboard in a cache. The embodiment removes the first dashboard from memory. The embodiment loads a second dashboard of the application into memory based on the selection. The embodiment then updates the second dashboard in the memory based on a second data set associated with the second dashboard and the shared data associated with a. plurality of dashboards.
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