Amazon Technologies, Inc.

Umar Farooq

Bhavesh Anil Doshi

Rishabh Animesh

Patrick Ian Wilson

Andrea Olgiati

James Caleb Kirschner

Rahul Bhotika

Amit Adam

Shai Mazor

Vivek Bhadauria

Adam Frederick Brock

Anand Dhandhania

Wendy Tse

Gururaj Kosuru

Kurniawan Kurniawan

An indication of training artifacts for a machine learning model to be trained with an input data set having an access restriction is obtained. A representation of a software execution environment containing the artifacts is deployed to a computing platform within an isolated resource group which satisfies the access restriction. A trained version of the machine learning model is generated at the computing platform, and transferred outside the isolated resource group.

Secure machine learning workflow automation using isolated resources

A data storage system implements techniques to efficiently store and retrieve structured data. For example, structured data is transformed into correlated segments, which are then redundancy coded and archived in a correlated fashion. The characteristics of the redundancy code used enable flexible handling of the archived data without excessive latency.

Archival data storage for structured data

A data storage system implements techniques for efficient retrieval of data stored thereon, using time of upload or another monotonically increasing variable as a key or identifier for the data to be stored and/or retrieved. Data is sorted according to, e.g., upload time, and the data is addressed with respect to time of upload and byte offset within the archive.

Monotonic time-based data storage

Techniques for layout-agnostic complex document processing are described. A document processing service can analyze documents that do not adhere to defined layout rules in an automated manner to determine the content and meaning of a variety of types of segments within the documents. The service may chunk a document into multiple chunks, and operate upon the chunks in parallel by identifying segments within each chunk, classifying the segments into segment types, and processing the segments using special-purpose analysis engines adapted for the analysis of particular segment types to generate results that can be aggregated into an overall output for the entire document that captures the meaning and context of the document text.

Layout-agnostic complex document processing system

Growing community of inventors

Mercer Island, WA, United States of America

Umar Farooq