Morgan Stanley Services Group Inc.

Nvidia Corporation

Rahul Suresh

Mehak Mehta

William R Schnieders

Suryakant Brahmbhatt

Ashutosh Jain

Cheryl Fernandes

Sanjit Vijay Mehta

Ashish Kumar Singh

Karthik Raghavan Ravi

Sandeep Ramesh

Alisha Singh

Labdhi Shah

Naina Bharadwaj

Dipesh Singh

Lokin Makkena

A system and method may create and manage a code repository structure and related files for a ML system such as a NN by executing code to create a version control management platform template commit including a pipeline folder comprising deploy files; a configuration folder comprising key-value pairs describing variables used as input to the neural network; a notebooks folder; a steps folder including ML or NN code; a tests folder comprising test scripts; and a utils folder; and executing code to create a tag associated with a pull request and alter version control management platform data such that the tag is displayed in conjunction with data describing the branch associated with the pull request. Executing code to create a tag may include searching a commit history for a unique commit number associated with a pull request, and based on this search creating a tag.

System and method for machine learning development

Systems and methods for detecting human impersonations on the internet, comprising receiving, by an ingestion layer of a detection system, a plurality of web data; filtering, by a processing engine of the detection system, the plurality of web data to identify relevant websites; extracting, via a scoring engine of the detection system, categories of data of a website of the relevant websites; assigning a score, via the scoring engine, for each category of the categories of data; and determining a risk score for the website, via the scoring engine, based on the score for each category.

Automated identification of internet human impersonators

Apparatuses, systems, and techniques to execute one or more application programming interfaces (APIs) to perform one or more operations for one or more accelerators within a heterogeneous processor. In at least one embodiment, one or more processors are to perform one or more instructions in response to one or more APIs to indicate one or more functions to be performed in response to one or more errors from one or more accelerators within a heterogeneous processor.

Application programming interface to indicate accelerator error handlers

A computer-implemented method for extracting data from separate databases and loading the data into a central data store without introducing additional security vulnerabilities is disclosed. The method begins by receiving a configuration comprising one or more transformation functions to be applied to one or more data fields. Values of the one or more data fields are extracted from the databases for a plurality of records, the values being previously tagged with metadata indicating at least a datatype for the values. Based at least in part on the configuration and the metadata tagging, a function from the one or more transformation functions is selected for each value. A second database with a central data store is populated with transformed data. Requestors are not permitted to access to pre-transformed data in the first one or more databases while being allowed access to at least some post-transformed data in the central data store.

Information compartmentalizing data store

Growing community of inventors

Bengaluru, India

Rahul Suresh