Artificial Intelligence

Category: Amazon SageMaker

Generate a counterfactual analysis of corn response to nitrogen with Amazon SageMaker JumpStart solutions

In his book The Book of Why, Judea Pearl advocates for teaching cause and effect principles to machines in order to enhance their intelligence. The accomplishments of deep learning are essentially just a type of curve fitting, whereas causality could be used to uncover interactions between the systems of the world under various constraints without […]

Zero-shot prompting for the Flan-T5 foundation model in Amazon SageMaker JumpStart

The size and complexity of large language models (LLMs) have exploded in the last few years. LLMs have demonstrated remarkable capabilities in learning the semantics of natural language and producing human-like responses. Many recent LLMs are fine-tuned with a powerful technique called instruction tuning, which helps the model perform new tasks or generate responses to […]

Snapper provides machine learning-assisted labeling for pixel-perfect image object detection

Bounding box annotation is a time-consuming and tedious task that requires annotators to create annotations that tightly fit an object’s boundaries. Bounding box annotation tasks, for example, require annotators to ensure that all edges of an annotated object are enclosed in the annotation. In practice, creating annotations that are precise and well-aligned to object edges […]

HAYAT HOLDING uses Amazon SageMaker to increase product quality and optimize manufacturing output, saving $300,000 annually

This is a guest post by Neslihan Erdogan, Global Industrial IT Manager at HAYAT HOLDING. With the ongoing digitization of the manufacturing processes and Industry 4.0, there is enormous potential to use machine learning (ML) for quality prediction. Process manufacturing is a production method that uses formulas or recipes to produce goods by combining ingredients […]

Achieve effective business outcomes with no-code machine learning using Amazon SageMaker Canvas

On November 30, 2021, we announced the general availability of Amazon SageMaker Canvas, a visual point-and-click interface that enables business analysts to generate highly accurate machine learning (ML) predictions without having to write a single line of code. With Canvas, you can take ML mainstream throughout your organization so business analysts without data science or […]

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

This is joint post co-written by Leidos and AWS. Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets. Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where […]

Build a machine learning model to predict student performance using Amazon SageMaker Canvas

There has been a paradigm change in the mindshare of education customers who are now willing to explore new technologies and analytics. Universities and other higher learning institutions have collected massive amounts of data over the years, and now they are exploring options to use that data for deeper insights and better educational outcomes. You […]

Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and […]

Remote monitoring of raw material supply chains for sustainability with Amazon SageMaker geospatial capabilities

Deforestation is a major concern in many tropical geographies where local rainforests are at severe risk of destruction. About 17% of the Amazon rainforest has been destroyed over the past 50 years, and some tropical ecosystems are approaching a tipping point beyond which recovery is unlikely. A key driver for deforestation is raw material extraction […]

Best practices for viewing and querying Amazon SageMaker service quota usage

Amazon SageMaker customers can view and manage their quota limits through Service Quotas. In addition, they can view near real-time utilization metrics and create Amazon CloudWatch metrics to view and programmatically query SageMaker quotas. SageMaker helps you build, train, and deploy machine learning (ML) models with ease. To learn more, refer to Getting started with […]