IBM Journey to AI blog

SEPTEMBER 19, 2024

Eight client teams collaborated with IBM® and AWS this spring to develop generative AI prototypes to address real-world business challenges in the public sector, financial services, energy, healthcare and other industries. The upfront enablement helped teams understand AWS technologies, then put that understanding into practice.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

This wealth of content provides an opportunity to streamline access to information in a compliant and responsible way. Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Third, we’ll explore the robust infrastructure services from AWS powering AI innovation, featuring Amazon SageMaker , AWS Trainium , and AWS Inferentia under AI/ML, as well as Compute topics.

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Snorkel AI

NOVEMBER 19, 2024

That’s why at Snorkel AI, we believe data is the true differentiator, a vision we share with Amazon Web Services (AWS). In June, Snorkel and AWS signed a multi-year strategic collaboration agreement to help enterprises build, deploy, and evaluate custom, production-ready AI models.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

AWS can play a key role in enabling fast implementation of these decentralized clinical trials. By exploring these AWS powered alternatives, we aim to demonstrate how organizations can drive progress towards more environmentally friendly clinical research practices.

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AWS Machine Learning Blog

MAY 2, 2024

Today, we’re excited to announce the availability of Meta Llama 3 inference on AWS Trainium and AWS Inferentia based instances in Amazon SageMaker JumpStart. In this post, we demonstrate how easy it is to deploy Llama 3 on AWS Trainium and AWS Inferentia based instances in SageMaker JumpStart.

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AWS Machine Learning Blog

OCTOBER 24, 2024

RAG introduces an information retrieval component that uses the user input to first pull information from a new data source. You can use Amazon Comprehend or AWS Glue sensitive data detection capability to identify sensitive data and then use Spark to clean up and sanitize the data.

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AWS Machine Learning Blog

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. Some applications may need to access data with personal identifiable information (PII) while others may rely on noncritical data.

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

Legal tech professionals, like any other business handling sensitive customer information, require robust security and confidentiality practices. AWS AI and machine learning (ML) services help address these concerns within the industry. These capabilities are built using the AWS Cloud. At AWS, security is our top priority.

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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

OCTOBER 10, 2024

It generates answers using relevant information from across Amazon and the web to help Amazon customers make better, more informed shopping decisions. To achieve this, the Rufus team is using multiple AWS services and AWS AI chips, AWS Trainium and AWS Inferentia.

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AWS Machine Learning Blog

JULY 31, 2024

Amazon Web Services (AWS) is committed to supporting the development of cutting-edge generative artificial intelligence (AI) technologies by companies and organizations across the globe. Let’s dive in and explore how these organizations are transforming what’s possible with generative AI on AWS.

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AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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Hacker News

AUGUST 8, 2024

Welcome to the AWS Code Examples Repository. This repo contains code examples used in the AWS documentation, AWS SDK Developer Guides, and more. For more information, see the Readme.md awsdocs/aws-doc-sdk-examples file below.

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AWS Machine Learning Blog

OCTOBER 17, 2024

During re:Invent 2023, we launched AWS HealthScribe , a HIPAA eligible service that empowers healthcare software vendors to build their clinical applications to use speech recognition and generative AI to automatically create preliminary clinician documentation. AWS HealthScribe will then output two files which are also stored on Amazon S3.

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AWS Machine Learning Blog

SEPTEMBER 27, 2024

This capability opens up innovative avenues for image understanding, wherein Anthropic’s Claude 3 models can analyze visual information in conjunction with textual data, facilitating more comprehensive and contextual interpretations. AWS Fargate is the compute engine for web application.

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AWS Machine Learning Blog

NOVEMBER 21, 2024

Today, we’re excited to share the journey of the VW —an innovator in the automotive industry and Europe’s largest car maker—to enhance knowledge management by using generative AI , Amazon Bedrock , and Amazon Kendra to devise a solution based on Retrieval Augmented Generation (RAG) that makes internal information more easily accessible by its users.

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AWS Machine Learning Blog

JULY 17, 2024

As a customer, you rely on Amazon Web Services (AWS) expertise to be available and understand your specific environment and operations. This allows you to easily identify and reference the underlying information sources that informed the AI’s response, providing more context and enabling further exploration of the topic if needed.

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AWS Machine Learning Blog

APRIL 16, 2024

They’re often used with highly sensitive business data, like personal data, compliance data, operational data, and financial information, to optimize the model’s output. At AWS, our top priority is safeguarding the security and confidentiality of our customers’ workloads.

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Hacker News

APRIL 5, 2023

I heard multiple times that AWS scans public GitHub repositories for AWS credentials and informs its users of the leaked credentials. So I am curious to see this for myself, so I decided to intentionally leak AWS credentials to a Public GitHub repository. Below you will find detailed information about every event.

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AWS Machine Learning Blog

NOVEMBER 22, 2024

Because Amazon Bedrock is serverless, you don’t have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. client( service_name="bedrock-runtime", region_name="us-east-1" ) Define the model to invoke using its model ID.

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AWS Machine Learning Blog

APRIL 18, 2024

Tools like Terraform and AWS CloudFormation are pivotal for such transitions, offering infrastructure as code (IaC) capabilities that define and manage complex cloud environments with precision. AWS Landing Zone addresses this need by offering a standardized approach to deploying AWS resources.

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AWS Machine Learning Blog

JULY 30, 2024

Amazon Q Business uses AWS IAM Identity Center to record the workforce users you assign access to and their attributes, such as group associations. IAM Identity Center is used by many AWS managed applications such as Amazon Q. Why use trusted identity propagation? Promotes software design principles rooted in user privacy.

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AWS Machine Learning Blog

SEPTEMBER 4, 2024

A challenge for DevOps engineers is the additional complexity that comes from using Kubernetes to manage the deployment stage while resorting to other tools (such as the AWS SDK or AWS CloudFormation ) to manage the model building pipeline. SageMaker encrypts these by default using the AWS managed key for Amazon S3.

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AWS Machine Learning Blog

JULY 3, 2024

To solve this problem, this post shows you how to apply AWS services such as Amazon Bedrock , AWS Step Functions , and Amazon Simple Email Service (Amazon SES) to build a fully-automated multilingual calendar artificial intelligence (AI) assistant. It lets you orchestrate multiple steps in the pipeline.

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Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

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AWS Machine Learning Blog

NOVEMBER 22, 2024

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions.

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AWS Machine Learning Blog

MARCH 12, 2024

In this post, we explore what an audience overlap analysis is, discuss the current technical approaches and their challenges, and illustrate how you can run secure audience overlap analysis using AWS Clean Rooms. With AWS Clean Rooms, you can create a data clean room in minutes and collaborate with your partners to generate unique insights.

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

This post takes you through the most common challenges that customers face when searching internal documents, and gives you concrete guidance on how AWS services can be used to create a generative AI conversational bot that makes internal information more useful. The cost associated with training models on recent data is high.

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Towards AI

OCTOBER 4, 2024

this article, we will deploy resources on AWS through Terraform and create a CI/CD pipeline on Gitlab to automate the deployment process. You require the following tools for this project: AWS account and a user account — Preferred cloud computing resources provider that offers a free tier. You can follow this tutorial to install it.

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AWS Machine Learning Blog

AUGUST 5, 2024

RAG models first retrieve relevant information from a large corpus of text and then use a FM to synthesize an answer based on the retrieved information. Prerequisites To implement the solution provided in this post, you should have the following: An active AWS account and familiarity with FMs, Amazon Bedrock, and OpenSearch Serverless.

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AWS Machine Learning Blog

MAY 30, 2024

Organizations across media and entertainment, advertising, social media, education, and other sectors require efficient solutions to extract information from videos and apply flexible evaluations based on their policies. This solution, powered by AWS AI and generative AI services, meets these needs.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

QnABot on AWS is an open source solution built using AWS native services like Amazon Lex , Amazon OpenSearch Service , AWS Lambda , Amazon Transcribe , and Amazon Polly. In this post, we demonstrate how to integrate the QnABot on AWS chatbot solution with ServiceNow. Save this information to use in later steps.

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AWS Machine Learning Blog

MARCH 12, 2024

In this post, we discuss how Leidos worked with AWS to develop an approach to privacy-preserving large language model (LLM) inference using AWS Nitro Enclaves. Technical architectures need to be implemented in order to make sure that LLMs don’t expose sensitive information during inference.

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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

OCTOBER 4, 2023

Gather information necessary to support the prior authorization request. If needed, supplement the prior authorization request with additional required information (and resume at Step 4). When utilized, it provides information on coverage requirements to providers while patient care decisions are in progress.

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AWS Machine Learning Blog

FEBRUARY 26, 2024

By using AWS services, our architecture provides real-time visibility into LLM behavior and enables teams to quickly identify and address any issues or anomalies. In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda.

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