Flipboard

OCTOBER 9, 2023

This lesson is the 2nd of a 3-part series on Docker for Machine Learning : Getting Started with Docker for Machine Learning Getting Used to Docker for Machine Learning (this tutorial) Lesson 3 To learn how to create a Docker Container for Machine Learning, just keep reading.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. The need for federated learning in healthcare Healthcare relies heavily on distributed data sources to make accurate predictions and assessments about patient care.

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AWS Machine Learning Blog

JUNE 20, 2024

AWS customers that implement secure development environments often have to restrict outbound and inbound internet traffic. Therefore, accessing AWS services without leaving the AWS network can be a secure workflow. Therefore, accessing AWS services without leaving the AWS network can be a secure workflow.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

In order to improve our equipment reliability, we partnered with the Amazon Machine Learning Solutions Lab to develop a custom machine learning (ML) model capable of predicting equipment issues prior to failure. We first highlight how we use AWS Glue for highly parallel data processing. Additionally, 10.4%

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AWS Machine Learning Blog

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. The workflow steps are as follows: AWS Lambda running in your private VPC subnet receives the prompt request from the generative AI application.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. This complexity often leads to the need for distributed ML, where multiple machines are used to train a single model. The full code can be found on the aws-samples-for-ray GitHub repository.

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AWS Machine Learning Blog

APRIL 29, 2024

Close collaboration with AWS Trainium has also played a major role in making the Arcee platform extremely performant, not only accelerating model training but also reducing overall costs and enforcing compliance and data integrity in the secure AWS environment. Our cluster consisted of 16 nodes, each equipped with a trn1n.32xlarge

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Flipboard

NOVEMBER 18, 2024

Amazon Web Services(AWS) has introduced Multi-Agent Orchestrator, a framework, that offers a solution for managing multiple AI agents and handling complex conversations.

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Flipboard

NOVEMBER 18, 2024

Unleash your inner developer with AWS App Studio, the generative AI-powered application builder. Turn your idea into fully-fledged, intelligent, custom, secure, and scalable software in minutes.

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Flipboard

DECEMBER 5, 2024

Dive Brief: PwC is expanding its alliance with AWS in pursuit of industry-tailored generative AI applications, the two companies announced at AWS

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AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose using an open-source federated learning (FL) framework called FedML , which enables you to analyze sensitive HCLS data by training a global machine learning model from distributed data held locally at different sites. In the first post, we described FL concepts and the FedML framework.

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Flipboard

DECEMBER 3, 2024

Apple surprised everyone with its presence at AWS re:Invent 2024. During his keynote, AWS chief Matt Garman invited Benoit Dupin, Apple’s senior director of machine learning and AI, on stage to speak about how the company works with Amazon Web Services (AWS) and uses its servers to power its AI and machine learning features.

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AWS Machine Learning Blog

DECEMBER 14, 2023

This is a customer post jointly authored by ICL and AWS employees. To overcome this business challenge, ICL decided to develop in-house capabilities to use machine learning (ML) for computer vision (CV) to automatically monitor their mining machines.

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AWS Machine Learning Blog

SEPTEMBER 27, 2024

Architecting specific AWS Cloud solutions involves creating diagrams that show relationships and interactions between different services. Instead of building the code manually, you can use Anthropic’s Claude 3’s image analysis capabilities to generate AWS CloudFormation templates by passing an architecture diagram as input.

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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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Flipboard

DECEMBER 5, 2024

I sat down with AWS CEO Matt Garman at the company’s re:Invent conference in Las Vegas, Nevada to talk through Amazon’s AI strategy and plans for the future.

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AWS Machine Learning Blog

MARCH 30, 2023

In this post, we introduce a new interactive tool called Snapper, powered by a machine learning (ML) model that reduces the effort required of annotators. About the authors Jonathan Buck is a Software Engineer at Amazon Web Services working at the intersection of machine learning and distributed systems.

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Flipboard

NOVEMBER 27, 2023

Amazon AWS, the cloud computing giant, has been perceived as playing catch-up with its rivals Microsoft Azure and Google Cloud in the emerging and exciting field of generative AI. But this week, at its annual AWS Re:Invent conference, Amazon plans to showcase its ambitious vision for generative AI, …

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Flipboard

DECEMBER 3, 2024

AWS Database Migration Service Schema Conversion (DMS SC) helps you accelerate your database migration to AWS. Using DMS SC, you can assess, convert, …

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AWS Machine Learning Blog

AUGUST 28, 2024

This post demonstrates how to seamlessly automate the deployment of an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS Cloud Development Kit (AWS CDK), enabling organizations to quickly set up a powerful question answering system. The AWS CDK already set up. txt,md,html,doc/docx,csv,xls/.xlsx,pdf).

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insideBIGDATA

JANUARY 16, 2024

In this contributed article, Stefano Soatto, Professor of Computer Science at the University of California, Los Angeles and a Vice President at Amazon Web Services, discusses generative AI models and how they are designed and trained to hallucinate, so hallucinations are a common product of any generative model.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

In this post, we demonstrate how to use various AWS technologies to establish a serverless semantic cache system. The solution presented in this post can be deployed through an AWS CloudFormation template. The solution presented in this post can be deployed through an AWS CloudFormation template.

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AWS Machine Learning Blog

OCTOBER 31, 2024

By integrating human annotators with machine learning, SageMaker Ground Truth significantly reduces the cost and time required for data labeling. Create the labeling job using the CreateLabelingJob API You can also create the custom labeling job programmatically by using the AWS SDK to invoke the CreateLabelingJob API.

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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). Prometheus requires the Container Storage Interface (CSI) in the EKS cluster.

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AWS Machine Learning Blog

APRIL 25, 2023

In this release, you can run your local machine learning (ML) Python code as a single-node Amazon SageMaker training job or multiple parallel jobs. As a prerequisite, you must have the AWS Command Line Interface (AWS CLI), SageMaker Python SDK, and AWS SDK for Python (Boto3) installed in your local environment.

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Flipboard

DECEMBER 5, 2024

Amazon to quadruple performance of its AI processors by late 2025 as it readies giant ExaFLOPS supercomputer for AI.

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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. It involves training a global machine learning (ML) model from distributed health data held locally at different sites. Request a VPC peering connection.

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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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Flipboard

JULY 21, 2023

Dive Brief:• AWS launched a generative AI primer course aimed at executives Thursday, available for free on the AWS Skill Builder platform and its …

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AWS Machine Learning Blog

SEPTEMBER 15, 2023

In this post, we introduce LLM agents and demonstrate how to build and deploy an e-commerce LLM agent using Amazon SageMaker JumpStart and AWS Lambda. To power the LLM agent, we use a Flan-UL2 model deployed as a SageMaker endpoint and use data retrieval tools built with AWS Lambda.

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Flipboard

MAY 10, 2023

IBM is taking on the likes of Microsoft, AWS, and Google by introducing Watsonx, a new generative AI platform, which will help enterprises design and …

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AWS Machine Learning Blog

JUNE 18, 2024

Some examples include extracting players and positions in an NFL game summary, products mentioned in an AWS keynote transcript, or key names from an article on a favorite tech company. We extract the default generic entities through the AWS SDK for Python (Boto3) as follows: import pandas as pd comprehend_client = boto3.client("comprehend")

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AWS Machine Learning Blog

NOVEMBER 22, 2023

The AWS Well-Architected Framework provides a systematic way for organizations to learn operational and architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable workloads in the cloud. These resources introduce common AWS services for IDP workloads and suggested workflows.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Building a production-ready solution in AWS involves a series of trade-offs between resources, time, customer expectation, and business outcome. The AWS Well-Architected Framework helps you understand the benefits and risks of decisions you make while building workloads on AWS.

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AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. See Amazon SageMaker geospatial capabilities to learn more. About the Author Xiong Zhou is a Senior Applied Scientist at AWS.

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