AWS Machine Learning Blog

JANUARY 24, 2024

We demonstrate how to build an end-to-end RAG application using Cohere’s language models through Amazon Bedrock and a Weaviate vector database on AWS Marketplace. The user query is used to retrieve relevant additional context from the vector database. The user receives a more accurate response based on their query.

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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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DECEMBER 3, 2024

Syngenta and AWS collaborated to develop Cropwise AI , an innovative solution powered by Amazon Bedrock Agents , to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. The collaboration between Syngenta and AWS showcases the transformative power of LLMs and AI agents.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using Amazon Web Services (AWS) services without having to manage infrastructure. AWS Lambda The API is a Fastify application written in TypeScript.

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Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

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Smart Data Collective

NOVEMBER 7, 2022

One of the best known options is Amazon Web Services (AWS). What is Amazon Web Services (AWS)? AWS is a collection of remote computing services (or web services). AWS Cloud is a suite of hosting products used by such services as Dropbox, Reddit, and others. AWS is a cloud computing service. AWS Lambda.

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APRIL 13, 2023

At AWS, we have played a key role in democratizing ML and making it accessible to anyone who wants to use it, including more than 100,000 customers of all sizes and industries. AWS has the broadest and deepest portfolio of AI and ML services at all three layers of the stack.

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AWS Machine Learning Blog

MAY 30, 2024

Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. The framework for connecting Anthropic Claude 2 and CBRE’s sample database was implemented using LangChain.

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IBM Journey to AI blog

OCTOBER 26, 2023

In this journey, we are seeing an increased interest in migrating and deploying MAS on AWS Cloud. The growing need for Maximo migration to AWS Cloud Migrating to cloud helps organizations to drive the operational resiliency and reliability, at the same time keeping software up to date with minimal upgrade effort and infrastructure constraint.

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AWS Machine Learning Blog

MARCH 11, 2025

OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024. Vector database FloTorch selected Amazon OpenSearch Service as a vector database for its high-performance metrics. The implementation included a provisioned three-node sharded OpenSearch Service cluster.

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AWS Machine Learning Blog

JUNE 11, 2024

In this post, we describe the scale of our AI offerings, the challenges with diverse AI workloads, and how we optimized mixed AI workload inference performance with AWS Graviton3 based c7g instances and achieved 20% throughput improvement, 30% latency reduction, and reduced our cost by 25–30%.

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NOVEMBER 17, 2023

The Retrieval-Augmented Generation (RAG) framework augments prompts with external data from multiple sources, such as document repositories, databases, or APIs, to make foundation models effective for domain-specific tasks. Its vector data store seamlessly integrates with operational data storage, eliminating the need for a separate database.

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AWS Machine Learning Blog

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. Pre-built templates tailored to various use cases are included, significantly enhancing both employee and customer experiences.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. Innovative startups like Perplexity AI are going all in on AWS for generative AI.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

In addition to its groundbreaking AI innovations, Zeta Global has harnessed Amazon Elastic Container Service (Amazon ECS) with AWS Fargate to deploy a multitude of smaller models efficiently. IAM roles : Assign appropriate AWS Identity and Access Management (IAM) roles to the tasks for accessing other AWS resources securely.

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IBM Journey to AI blog

JANUARY 16, 2024

To aid in building more sustainable IT estates, IBM has partnered up with Amazon Web Services (AWS) to facilitate sustainable cloud modernization journeys. To read about other key scenarios and entry points of IBM Consulting® Custom Lens for Sustainability, check out the blog post: Sustainable App Modernization Using AWS Cloud.

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AWS Machine Learning Blog

JULY 17, 2023

As described in the AWS Well-Architected Framework , separating workloads across accounts enables your organization to set common guardrails while isolating environments. Organizations with a multi-account architecture typically have Amazon Redshift and SageMaker Studio in two separate AWS accounts. Select VPC Only , then choose Next.

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AWS Machine Learning Blog

AUGUST 21, 2023

Data is frequently kept in data lakes that can be managed by AWS Lake Formation , giving you the ability to implement fine-grained access control using a straightforward grant or revoke procedure. You can use the provided AWS CloudFormation stack to set up the architectural components for this solution.

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Analytics Vidhya

MAY 16, 2022

Elasticsearch acts a lot like a database and a distributed system […]. Introduction on Amazon Elasticsearch Service Amazon Elasticsearch Service is a powerful tool that allows you to perform a number of functions. Let us examine how this powerful tool works behind the scenes.

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AWS Machine Learning Blog

MAY 1, 2024

This post presents a solution for developing a chatbot capable of answering queries from both documentation and databases, with straightforward deployment. To retrieve data from database, you can use foundation models (FMs) offered by Amazon Bedrock, converting text into SQL queries with specified constraints. Virginia) AWS Region.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

Cost optimization – The serverless nature of the integration means you only pay for the compute resources you use, rather than having to provision and maintain a persistent cluster. SageMaker Studio runs inside an AWS managed virtual private cloud ( VPC ), with network access for SageMaker Studio domains, in this setup configured as VPC-only.

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AWS Machine Learning Blog

FEBRUARY 5, 2025

The listing indexer AWS Lambda function continuously polls the queue and processes incoming listing updates. These databases typically use k-nearest (k-NN) indexes built with advanced algorithms such as Hierarchical Navigable Small Worlds (HNSW) and Inverted File (IVF) systems. For data handling, 24 data nodes (r6gd.2xlarge.search

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AWS Machine Learning Blog

FEBRUARY 2, 2024

In this post, you’ll see an example of performing drift detection on embedding vectors using a clustering technique with large language models (LLMS) deployed from Amazon SageMaker JumpStart. In this pattern, the recipe text is converted into embedding vectors using an embedding model, and stored in a vector database.

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AWS Machine Learning Blog

DECEMBER 6, 2023

In this blog post, we’ll explore how to deploy LLMs such as Llama-2 using Amazon Sagemaker JumpStart and keep our LLMs up to date with relevant information through Retrieval Augmented Generation (RAG) using the Pinecone vector database in order to prevent AI Hallucination. Sign up for a free-tier Pinecone Vector Database.

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NOVEMBER 24, 2023

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

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AWS Machine Learning Blog

DECEMBER 29, 2022

AWS offers tools such as RStudio on SageMaker and Amazon Redshift to help tackle these challenges. Note: If you already have an RStudio domain and Amazon Redshift cluster you can skip this step. Amazon Redshift Serverless cluster. I acknowledge that AWS CloudFormation might create IAM resources with custom names.

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AWS Machine Learning Blog

FEBRUARY 7, 2025

Key AWS services used include: Amazon Bedrock Including Anthropics Claude 3.5 Additionally, if a user tells the assistant something that should be remembered, we store this piece of information in a database and add it to the context every time the user initiates a request.

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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. In the first post , we described FL concepts and the FedML framework.

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IBM Journey to AI blog

MARCH 27, 2024

Java is 1000 times faster than today’s database systems. While programming languages like Java offer microsecond processing speeds, external database servers that have been utilized for data processing over the past 40 years, are 1000 times slower with millisecond processing speeds.

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AWS Machine Learning Blog

DECEMBER 18, 2023

MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud. Make sure you have the following prerequisites: Create an S3 bucket Configure MongoDB Atlas cluster Create a free MongoDB Atlas cluster by following the instructions in Create a Cluster.

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AWS Machine Learning Blog

DECEMBER 15, 2023

Amazon DocumentDB is a fully managed native JSON document database that makes it straightforward and cost-effective to operate critical document workloads at virtually any scale without managing infrastructure. Enter a connection name such as demo and choose your desired Amazon DocumentDB cluster. Finally, select your read preference.

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AWS Machine Learning Blog

APRIL 16, 2024

For example, you can visually explore data sources like databases, tables, and schemas directly from your JupyterLab ecosystem. After you have set up connections (illustrated in the next section), you can list data connections, browse databases and tables, and inspect schemas. This new feature enables you to perform various functions.

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AWS Machine Learning Blog

FEBRUARY 14, 2024

In this post, we discuss how to use the comprehensive capabilities of Amazon Bedrock to perform complex business tasks and improve the customer experience by providing personalization using the data stored in a database like Amazon Redshift. An SSL certificate created and imported into AWS Certificate Manager (ACM). Open an SSH client.

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AWS Machine Learning Blog

AUGUST 8, 2024

Webex works with the world’s leading business and productivity apps—including AWS. The following diagram illustrates the WxAI architecture on AWS. Its solutions are underpinned with security and privacy by design.

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AWS Machine Learning Blog

APRIL 17, 2023

Using RStudio on SageMaker and Amazon EMR together, you can continue to use the RStudio IDE for analysis and development, while using Amazon EMR managed clusters for larger data processing. In this post, we demonstrate how you can connect your RStudio on SageMaker domain with an EMR cluster. Choose Create stack.

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AWS Machine Learning Blog

MARCH 30, 2023

Metadata of the match is processed within the AWS Lambda function MetaDataIngestion , while positional data is ingested using the AWS Fargate container called MatchLink. Additionally, the ball recovery times are sent to a specific topic in the MSK cluster, where they can be accessed by other Bundesliga Match Facts.

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Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. As the demand for the data solutions increased, cloud companies like AWS also jumped in and began providing managed data lake solutions with AWS Athena and S3. AWS Athena and S3. Indexing capabilities.

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