Tag: faang

The goal of intelligent document processing (IDP) is to help your organization make faster and more accurate decisions by applying AI to process your paperwork. This two-part series highlights the AWS AI technologies that insurance companies can use to speed up their business processes. These AI technologies can be used across insurance use cases such …

Read more “Intelligent document processing with AWS AI services in the insurance industry: Part 1”

To delight customers and minimize packaging waste, Amazon must select the optimal packaging type for billions of packages shipped every year. If too little protection is used for a fragile item such as a coffee mug, the item will arrive damaged and Amazon risks their customer’s trust. Using too much protection will result in increased …

Read more “Improving stability and flexibility of ML pipelines at Amazon Packaging Innovation with Amazon SageMaker Pipelines”

Intelligent document processing (IDP) has seen widespread adoption across enterprise and government organizations. Gartner estimates the IDP market will grow more than 100% year over year, and is projected to reach $4.8 billion in 2022. IDP helps transform structured, semi-structured, and unstructured data from a variety of document formats into actionable information. Processing unstructured data …

Read more “Improve data extraction and document processing with Amazon Textract”

Identifying, collecting, and transforming data is the foundation for machine learning (ML). According to a Forbes survey, there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. In addition, many of our customers face several challenges during the model operationalization phase …

Read more “Automated exploratory data analysis and model operationalization framework with a human in the loop”

Amazon SageMaker Autopilot automatically builds, trains, and tunes the best custom machine learning (ML) models based on your data. It’s an automated machine learning (AutoML) solution that eliminates the heavy lifting of handwritten ML models that requires ML expertise. Data scientists need to only provide a tabular dataset and select the target column to predict, …

Read more “Move Amazon SageMaker Autopilot ML models from experimentation to production using Amazon SageMaker Pipelines”

Editor’s note: This is the first in a series of blogs on researchers advancing science in the expanding universe of high performance computing. A perpetual shower of random raindrops falls inside a three-foot metal ring Dale Durran erected outside his front door (shown above). It’s a symbol of his passion for finding order in the …

Read more “Stormy Weather? Scientist Sharpens Forecasts With AI”

Editor’s note: This is the third post in the Palantir RFx Blog Series, which explores how organizations can better craft RFIs and RFPs to evaluate digital transformation software. Each post focuses on one key capability area within a data ecosystem, with the goal of helping companies ask the right questions to better assess technology. Introduction …

Read more “Data Pipeline Version Control: Tracking Code & Data Together (Palantir RFx Blog Series, #3)”

Machine learning (ML) has proven to be one of the most successful and widespread applications of technology, affecting a wide range of industries and impacting billions of users every day. With this rapid adoption of ML into every industry, companies are facing challenges in supporting low-latency predictions and with high availability while maximizing resource utilization …

Read more “Cost efficient ML inference with multi-framework models on Amazon SageMaker “