AWS Machine Learning Blog

OCTOBER 29, 2024

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. Organizations typically can’t predict their call patterns, so the solution relies on AWS serverless services to scale during busy times.

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AWS Machine Learning Blog

JANUARY 13, 2023

In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. We have developed an FL framework on AWS that enables analyzing distributed and sensitive health data in a privacy-preserving manner. Therefore, it brings analytics to data, rather than moving data to analytics. Conclusion.

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AWS Machine Learning Blog

APRIL 1, 2025

invoke(input_text=Convert 11am from NYC time to London time) We showcase an example of building an agent to understand your Amazon Web Service (AWS) spend by connecting to AWS Cost Explorer , Amazon CloudWatch , and Perplexity AI through MCP. This gives you an AI agent that can transform the way you manage your AWS spend.

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AWS Machine Learning Blog

NOVEMBER 18, 2024

This binary representation will convert high-dimensional data into a more efficient format for storage and computation. It makes it simple for you to build modern machine learning (ML) augmented search experiences, generative AI applications, and analytics workloads without having to manage the underlying infrastructure.

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Pickl AI

DECEMBER 25, 2024

Summary: Business Analytics focuses on interpreting historical data for strategic decisions, while Data Science emphasizes predictive modeling and AI. Introduction In today’s data-driven world, businesses increasingly rely on analytics and insights to drive decisions and gain a competitive edge. What is Business Analytics?

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AWS Machine Learning Blog

MAY 28, 2025

Each format requires different analytical approaches and specialized tools, creating workflow inefficiencies. You also need to deploy two AWS CloudFormation stacks: web_search and stock_data. You can also explore and run Amazon Bedrock multi-agent collaboration workshop with AWS specialists or on your own.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

In this post, we show how the Carrier and AWS teams applied ML to predict faults across large fleets of equipment using a single model. We first highlight how we use AWS Glue for highly parallel data processing. AWS Glue allowed us to easily run parallel data preprocessing and feature extraction. Additionally, 10.4%

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AWS Machine Learning Blog

JUNE 27, 2024

In this post, we describe how we built our cutting-edge productivity agent NinjaLLM, the backbone of MyNinja.ai, using AWS Trainium chips. We also used AWS ParallelCluster to manage cluster orchestration. For training, we chose to use a cluster of trn1.32xlarge instances to take advantage of Trainium chips. Arash co-founded Ninjatech.ai

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AWS Machine Learning Blog

OCTOBER 16, 2024

As we look to the future, the integration of ML and geospatial analytics promises to further enhance our understanding of the planet’s ecological systems. About the Author Xiong Zhou is a Senior Applied Scientist at AWS. He leads the science team for Amazon SageMaker geospatial capabilities. He is an ACM Fellow and IEEE Fellow.

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AWS Machine Learning Blog

MARCH 15, 2024

Therefore, ML creates challenges for AWS customers who need to ensure privacy and security across distributed entities without compromising patient outcomes. After a blueprint is configured, it can be used to create consistent environments across multiple AWS accounts and Regions using continuous deployment automation.

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AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. For Account ID , enter the AWS account ID of the owner of the accepter VPC.

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AWS Machine Learning Blog

APRIL 7, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies and AWS. Solution overview The following diagram provides a high-level overview of AWS services and features through a sample use case.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Technical challenges with multi-modal data further include the complexity of integrating and modeling different data types, the difficulty of combining data from multiple modalities (text, images, audio, video), and the need for advanced computer science skills and sophisticated analysis tools.

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AWS Machine Learning Blog

JUNE 25, 2024

Amazon Web Services is excited to announce the launch of the AWS Neuron Monitor container , an innovative tool designed to enhance the monitoring capabilities of AWS Inferentia and AWS Trainium chips on Amazon Elastic Kubernetes Service (Amazon EKS).

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AWS Machine Learning Blog

MAY 1, 2024

Llama2 by Meta is an example of an LLM offered by AWS. To learn more about Llama 2 on AWS, refer to Llama 2 foundation models from Meta are now available in Amazon SageMaker JumpStart. Virginia) and US West (Oregon) AWS Regions, and most recently announced general availability in the US East (Ohio) Region.

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AWS Machine Learning Blog

MARCH 13, 2025

In this post, we dive deeper into one of MaestroQAs key featuresconversation analytics, which helps support teams uncover customer concerns, address points of friction, adapt support workflows, and identify areas for coaching through the use of Amazon Bedrock. The best is yet to come.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Prerequisites To run this step-by-step guide, you need an AWS account with permissions to SageMaker, Amazon Elastic Container Registry (Amazon ECR), AWS Identity and Access Management (IAM), and AWS CodeBuild. Complete the following steps: Sign in to the AWS Management Console and open the IAM console. Dima has a M.Sc

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AWS Machine Learning Blog

MAY 1, 2025

Prerequisites To use this feature, make sure that you have satisfied the following requirements: An active AWS account. model customization is available in the US West (Oregon) AWS Region. Sovik Kumar Nath is an AI/ML and Generative AI senior solution architect with AWS. Meta Llama 3.2 As of writing this post, Meta Llama 3.2

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AWS Machine Learning Blog

JANUARY 31, 2025

With a serverless solution, AWS provides a managed solution, facilitating lower cost of ownership and reduced complexity of maintenance. Were excited to see how Travelers and AWS have harnessed these capabilities to create such an efficient solution, demonstrating the potential for AI to transform insurance processes.

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Flipboard

FEBRUARY 21, 2025

AWS recommends Amazon OpenSearch Service as a vector database for Amazon Bedrock as the building blocks to power your solution for these workloads. Amazon OpenSearch Service is a fully managed service that you can use to deploy and operate OpenSearch in the AWS Cloud.

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AWS Machine Learning Blog

OCTOBER 23, 2024

SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). To address customers’ requirements about data privacy and sovereignty, SnapLogic deploys the data plane within the customer’s VPC on AWS.

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AWS Machine Learning Blog

FEBRUARY 20, 2025

Verisk (Nasdaq: VRSK) is a leading data analytics and technology partner for the global insurance industry. Through advanced analytics, software, research, and industry expertise across more than 20 countries, Verisk helps build resilience for individuals, communities, and businesses.

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Flipboard

JUNE 9, 2025

Book here Ankush Das I am a tech aficionado and a computer science graduate with a keen interest in AI, Coding, Open Source, and Cloud. by Ankush Das It is no surprise that developers are using AI models to write their code. 📣 Want to advertise in AIM? Have a tip?

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Flipboard

DECEMBER 4, 2024

At re: Invent 2024, AWS unveiled the next generation of Amazon SageMaker (now generally available), a unified platform for Data, Analytics and AI on …

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AWS Machine Learning Blog

APRIL 30, 2025

This post explores key insights and lessons learned from AWS customers in Europe, Middle East, and Africa (EMEA) who have successfully navigated this transition, providing a roadmap for others looking to follow suit. Il Sole 24 Ore leveraged its vast internal knowledge with a Retrieval Augmented Generation (RAG) solution powered by AWS.

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AWS Machine Learning Blog

MARCH 28, 2024

For more information on Mixtral-8x7B Instruct on AWS, refer to Mixtral-8x7B is now available in Amazon SageMaker JumpStart. Before you get started with the solution, create an AWS account. This identity is called the AWS account root user. The Mixtral-8x7B model is made available under the permissive Apache 2.0

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AWS Machine Learning Blog

SEPTEMBER 9, 2024

To address customer needs for high performance and scalability in deep learning, generative AI, and HPC workloads, we are happy to announce the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P5e instances, powered by NVIDIA H200 Tensor Core GPUs. AWS is the first leading cloud provider to offer the H200 GPU in production.

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Pickl AI

JUNE 5, 2025

The role demands both technical skills and business acumen, as Indian companies increasingly seek professionals who can align analytics with strategic goals. Big Data Technologies: Familiarity with Hadoop, Apache Spark, and cloud platforms like AWS, Azure, and Google Cloud is increasingly important as Indian companies scale data operations.

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AWS Machine Learning Blog

MARCH 8, 2023

The workflow steps are as follows: Set up a SageMaker notebook and an AWS Identity and Access Management (IAM) role with appropriate permissions to allow SageMaker to access Amazon Elastic Container Registry (Amazon ECR), Secrets Manager, and other services within your AWS account. AWS Region Link us-east-1 (N.

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AWS Machine Learning Blog

OCTOBER 10, 2023

Your data is not used to improve the base models, is not shared with third-party model providers, and stays entirely within your secure AWS environment. SageMaker JumpStart models can be started and deployed in your AWS account on demand and are automatically shut down after two hours of inactivity.

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AWS Machine Learning Blog

DECEMBER 2, 2024

Before joining AWS, he worked in the management consulting industry as a data scientist, serving the financial services and telecommunications sectors. He holds a PhD in Computer Engineering from Bogazici University in Istanbul. He holds a PhD in Computer Engineering from Bogazici University in Istanbul.

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AWS Machine Learning Blog

APRIL 18, 2023

The following sections cover the business and technical challenges, the approach taken by the AWS and RallyPoint teams, and the performance of implemented solution that leverages Amazon Personalize. He specializes in building machine learning pipelines that involve concepts such as natural language processing and computer vision.

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Prerequisites To continue with the examples in this post, you need to create the required AWS resources.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. They’re looking for people who know all related skills, and have studied computer science and software engineering.

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Flipboard

MAY 9, 2025

Prerequisites This solution requires you to have an AWS account with the appropriate permissions. The following code is an example using the AWS SDK for Python (Boto3) that prompts the LLM for sentiment analysis: import boto3 import json # Initialize Bedrock Runtime client bedrock = boto3.client('bedrock-runtime')

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AWS Machine Learning Blog

MAY 31, 2024

The Falcon 2 11B model is available today for inferencing from 22 AWS Regions where SageMaker JumpStart is available. Prerequisites To try out the Falcon 2 model using SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all your AWS resources. Armando Diaz is a Solutions Architect at AWS.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

Prerequisites To implement this solution, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. Basic familiarity with SageMaker and AWS services that support LLMs. For more information, see Overview of access management: Permissions and policies.

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