AWS Machine Learning Blog

OCTOBER 5, 2023

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia. 2048 256 10.4

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AWS Machine Learning Blog

JUNE 13, 2023

AWS Inferentia2 was designed from the ground up to deliver higher performance while lowering the cost of LLMs and generative AI inference. In this post, we show how the second generation of AWS Inferentia builds on the capabilities introduced with AWS Inferentia1 and meets the unique demands of deploying and running LLMs and FMs.

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Data Science 101

MAY 23, 2019

Here is the latest data science news for May 2019. Microsoft Build 2019 – This is a huge conference hosted by Microsoft for the developer community. Google I/O 2019 Videos – Google’s big annual conference. From Data Science 101. General Data Science. Many of the presentation are available to watch online.

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DataCentric podcast

DECEMBER 9, 2019

Amazon's massive AWS ReInvent Conference is nearly overwhelming in its breadth and scope, with dozens of announcements spanning numerous areas, from ARM to AI to on-premises Outpost.

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KDnuggets

DECEMBER 12, 2019

This post attempts to summarize my recent detour into NLP, describing how I exposed a Huggingface pre-trained Language Model (LM) on an AWS-based web application.

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Towards AI

AUGUST 10, 2023

PC Magazine: # 4 Companies Control 67% of the World’s Cloud Infrastructure Amazon Web Services: The Swiss Army Knife Approach With its vast array of cloud infrastructure offerings and unrivaled scale, Amazon Web Services (AWS) has firmly established itself as the dominant player in the space. Enter Amazon Bedrock, launched in April 2023.

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IBM Journey to AI blog

JULY 19, 2023

In this blog post, we will showcase how IBM Consulting is partnering with AWS and leveraging Large Language Models (LLMs), on IBM Consulting’s generative AI-Automation platform (ATOM), to create industry-aware, life sciences domain-trained foundation models to generate first drafts of the narrative documents, with an aim to assist human teams.

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ODSC - Open Data Science

AUGUST 4, 2023

Recently, we spoke with Emily Webber, Principal Machine Learning Specialist Solutions Architect at AWS. She’s the author of “Pretrain Vision and Large Language Models in Python: End-to-end techniques for building and deploying foundation models on AWS.” And then I spent many years working with customers.

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Mlearning.ai

JUNE 7, 2023

AWS Inferentia accelerators are custom-built machine learning inference chips designed by Amazon Web Services (AWS) to optimize inference workloads on the AWS platform. The AWS Inferentia chips are designed with a focus on delivering high performance, low latency, and cost efficiency for inference workloads.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Note that you can also use Knowledge Bases for Amazon Bedrock service APIs and the AWS Command Line Interface (AWS CLI) to programmatically create a knowledge base. Create a Lambda function This Lambda function is deployed using an AWS CloudFormation template available in the GitHub repo under the /cfn folder.

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AWS Machine Learning Blog

APRIL 9, 2024

In the following sections, we explain how you can use these features with either the AWS Management Console or SDK. The correct response for this query is “Amazon’s annual revenue increased from $245B in 2019 to $434B in 2022,” based on the documents in the knowledge base. We ask “What was the Amazon’s revenue in 2019 and 2021?”

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Tableau

NOVEMBER 24, 2019

November 25, 2019 - 4:39am. To help customers unlock the power and flexibility of self-service analytics in the cloud, we’re continuously investing in our Modern Cloud Analytics initiative, which we announced at Tableau Conference in 2019. Core product integration and connectivity between Tableau and AWS. Jason Dudek.

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Tableau

NOVEMBER 24, 2019

November 25, 2019 - 4:39am. To help customers unlock the power and flexibility of self-service analytics in the cloud, we’re continuously investing in our Modern Cloud Analytics initiative, which we announced at Tableau Conference in 2019. Core product integration and connectivity between Tableau and AWS. Jason Dudek.

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Tableau

NOVEMBER 24, 2019

November 25, 2019 - 4:39am. To help customers unlock the power and flexibility of self-service analytics in the cloud, we’re continuously investing in our Modern Cloud Analytics initiative, which we announced at Tableau Conference in 2019. Core product integration and connectivity between Tableau and AWS. Jason Dudek.

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Data Science 101

NOVEMBER 11, 2019

SQL Server 2019 SQL Server 2019 went Generally Available. If you are at a University or non-profit, you can ask for cash and/or AWS credits. AWS Parallel Cluster for Machine Learning AWS Parallel Cluster is an open-source cluster management tool. It can be used to do distributed Machine Learning on AWS.

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Hacker News

SEPTEMBER 15, 2024

Amazon Web Services (AWS) got there ahead of most of the competition, when they purchased chip designer Annapurna Labs in 2015 and proceeded to design CPUs, AI accelerators, servers, and data centers as a vertically-integrated operation. Rami Sinno AWS Rami Sinno : Amazon is my first vertically integrated company. Tell no one.”

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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

OCTOBER 2, 2023

On top of that, the whole process can be configured and managed via the AWS SDK, which is what we use to orchestrate our labeling workflow as part of our CI/CD pipeline. For more information about best practices, refer to the AWS re:Invent 2019 talk, Build accurate training datasets with Amazon SageMaker Ground Truth.

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Data Science 101

NOVEMBER 7, 2019

It is now possible to deploy an Azure SQL Database to a virtual machine running on Amazon Web Services (AWS) and manage it from Azure. This allows Azure to manage a completely hybrid infrastructure of: Azure, on-premise, IoT, and other cloud environments. It’s true, I saw it happen this week. R Support for Azure Machine Learning.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Amazon Bedrock Knowledge Bases offers a streamlined approach to implement RAG on AWS, providing a fully managed solution for connecting FMs to custom data sources. This shift by so many companies (along with the economy recovering) helped re-accelerate AWS’s revenue growth to 37% Y oY in 2021.nConversely, These areastounding numbers.

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Data Science 101

NOVEMBER 22, 2019

AWS Storage Day On November 20, 2019, Amazon held AWS Storage Day. Many announcements came out regarding storage of all types at AWS. Much of this is in anticipation of AWS re:Invent, coming in early December 2019. Much of this is in anticipation of AWS re:Invent, coming in early December 2019.

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AWS Machine Learning Blog

JULY 17, 2024

AWS announced the availability of the Cohere Command R fine-tuning model on Amazon SageMaker. About the Authors Shashi Raina is a Senior Partner Solutions Architect at Amazon Web Services (AWS), where he specializes in supporting generative AI (GenAI) startups. Start building with Cohere’s fine-tuning model in SageMaker today.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

Architecture The solution uses Amazon API Gateway , AWS Lambda , Amazon RDS, Amazon Bedrock, and Anthropic Claude 3 Sonnet on Amazon Bedrock to implement the backend of the application. Model deployment accounts – The LLMs offered by various vendors are hosted and operated by AWS in separate accounts dedicated for model deployment.

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Data Science 101

JANUARY 3, 2020

Machine Learning with Kubernetes on AWS A talk from Container Day 2019 in San Diego. A First Look at AWS Data Exchange (Webinar) AWS Data Exchange is a product for finding and using third party data. No significant news to report. Hopefully some releases and announcements will be coming next week. Courses/Education.

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AWS Machine Learning Blog

APRIL 19, 2024

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution. I need numbers."

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

“Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to use it“ Only 18% of organizations in a 2019 survey by Deloitte reported being able to take advantage of unstructured data. The majority of data, between 80% and 90%, is unstructured data.

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AWS Machine Learning Blog

MAY 17, 2023

AWS delivers services that meet customers’ artificial intelligence (AI) and machine learning (ML) needs with services ranging from custom hardware like AWS Trainium and AWS Inferentia to generative AI foundation models (FMs) on Amazon Bedrock. SageMaker Model SageMakerModel: Type: AWS::SageMaker::Model Properties: ModelName: !Sub

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AWS Machine Learning Blog

MARCH 14, 2024

In this post we highlight how the AWS Generative AI Innovation Center collaborated with the AWS Professional Services and PGA TOUR to develop a prototype virtual assistant using Amazon Bedrock that could enable fans to extract information about any event, player, hole or shot level details in a seamless interactive manner.

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AWS Machine Learning Blog

JULY 3, 2024

To answer this question, the AWS Generative AI Innovation Center recently developed an AI assistant for medical content generation. 2019 Apr;179(4):561-569. Epub 2019 Jan 31. Liza (Elizaveta) Zinovyeva is an Applied Scientist at AWS Generative AI Innovation Center and is based in Berlin. Am J Med Genet A. Int J Nurs Stud.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. The AWS P5 EC2 instance type range is based on the NVIDIA H100 chip, which uses the Hopper architecture. In November 2023, AWS announced the next generation Trainium2 chip.

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AWS Machine Learning Blog

MARCH 31, 2023

Also, the introduction of federal REAL ID requirements in 2019 resulted in increased call volumes from drivers with questions. The contact center is powered by Amazon Connect, and Max, the virtual agent, is powered by Amazon Lex and the AWS QnABot solution. We’d love to hear from you. Let us know what you think in the comments section.

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AWS Machine Learning Blog

DECEMBER 29, 2022

This is why we launched Amazon Textract in 2019 to help you automate your tedious document processing workflows powered by AI. Integration with AWS Service Quotas. You can now proactively manage all your Amazon Textract service quotas via the AWS Service Quotas console. Increased default service quotas for Amazon Textract.

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AWS Machine Learning Blog

OCTOBER 11, 2024

You can set up the notebook in any AWS Region where Amazon Bedrock Knowledge Bases is available. You also need an AWS Identity and Access Management (IAM) role assigned to the SageMaker Studio domain. Configure Amazon SageMaker Studio The first step is to set up an Amazon SageMaker Studio notebook to run the code for this post.

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AWS Machine Learning Blog

SEPTEMBER 10, 2024

We provide insights on interpretability, robustness, and best practices of architecting complex ML workflows on AWS with Amazon SageMaker. by AWS, which aimed to mitigate the limitations of PORPOISE. Each environment sits in its own isolated AWS account. 2022 ) was implemented (Section 2.1). per cancer type in survival analysis.

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IBM Journey to AI blog

JANUARY 10, 2023

This data will be analyzed using Netezza SQL and Python code to determine if the flight delays for the first half of 2022 have increased over flight delays compared to earlier periods of time within the current data (January 2019 – December 2021). Figure 5 – Bar graph of current flight delay data (2019 – June 2022).

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KDnuggets

SEPTEMBER 25, 2019

And as these implementations have required models that can perform on larger and larger datasets in real-time, an awful lot of data science problems have become engineering problems.

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