AWS Machine Learning Blog

MAY 30, 2024

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders).

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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

SEPTEMBER 28, 2023

Enterprises today face major challenges when it comes to using their information and knowledge bases for both internal and external business operations. Internally, employees can often spend countless hours hunting down information they need to do their jobs, leading to frustration and reduced productivity.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. It works by analyzing the visual content to find similar images in its database. The AWS Command Line Interface (AWS CLI) installed on your machine to upload the dataset to Amazon S3.

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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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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

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 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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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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AWS Machine Learning Blog

MARCH 13, 2024

In this post, we introduce solutions that enable audio and text chat moderation using various AWS services, including Amazon Transcribe , Amazon Comprehend , Amazon Bedrock , and Amazon OpenSearch Service. Amazon Transcribe converts the audio into text, providing additional information about toxicity analysis.

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Flipboard

JUNE 26, 2023

In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. Run the AWS Glue ML transform job.

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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

MARCH 14, 2024

Generative AI with AWS The emergence of FMs is creating both opportunities and challenges for organizations looking to use these technologies. A key challenge is ensuring high-quality, coherent outputs that align with business needs, rather than hallucinations or false information.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

The following are a few popular use cases: Smart reporting and market intelligence – AI can analyze various sources of financial information to generate market intelligence reports, aiding analysts, investors, and companies to stay updated on trends. The following screenshot shows an example of the UI.

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AWS Machine Learning Blog

APRIL 16, 2024

Managing your Amazon Lex bots using AWS CloudFormation allows you to create templates defining the bot and all the AWS resources it depends on. AWS CloudFormation provides and configures those resources on your behalf, removing the risk of human error when deploying bots to new environments. Resources: # 1.

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Flipboard

NOVEMBER 7, 2023

“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift.

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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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Flipboard

MARCH 18, 2023

Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, offering storage, databases, … TL;DR: A wide range of online Amazon Web Services courses are available for free on edX. Are you familiar with Amazon Web Services? If not, you should change this situation as soon as possible.

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AWS Machine Learning Blog

SEPTEMBER 13, 2024

Managing cloud costs and understanding resource usage can be a daunting task, especially for organizations with complex AWS deployments. AWS Cost and Usage Reports (AWS CUR) provides valuable data insights, but interpreting and querying the raw data can be challenging.

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Data Science Blog

SEPTEMBER 19, 2023

Enhanced Security and Compliance Data Warehouses often store sensitive information, making security a paramount concern. The following Terraform script will create an Azure Resource Group, a SQL Server, and a SQL Database. So why using IaC for Cloud Data Infrastructures?

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AWS Machine Learning Blog

MARCH 10, 2023

For more information, refer to Train fraudulent payment detection with Amazon SageMaker. This approach allows you to react to the potentially fraudulent transactions in real time as you store each transaction in a database and inspect it before processing further. Process the transaction further in case of an approve response.

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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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Dataconomy

OCTOBER 19, 2023

Casio, a name synonymous with electronic excellence, found itself amid a cybersecurity storm when the company detected a database failure within its revered ClassPad education platform. However, it is important to note that Casio did not store credit card information within the compromised database, mitigating some of the potential damage.

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Flipboard

JANUARY 24, 2025

Use the AWS generative AI scoping framework to understand the specific mix of the shared responsibility for the security controls applicable to your application. The following figure of the AWS Generative AI Security Scoping Matrix summarizes the types of models for each scope.

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Flipboard

NOVEMBER 27, 2024

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. or a later version) database.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

This post explores a solution that uses the power of AWS generative AI capabilities like Amazon Bedrock and OpenSearch vector search to perform damage appraisals for insurers, repair shops, and fleet managers. These embedding vectors contain the necessary information of the image and the text metadata encoded in numerical representation.

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Dataconomy

NOVEMBER 27, 2024

Tens of thousands of cloud computing professionals and enthusiasts will gather in Las Vegas for Amazon Web Services’ (AWS) re:Invent 2024 from December 2-6. AWS re:Invent 2024: Generative AI in focus at Las Vegas event Attendees can expect a robust emphasis on generative AI throughout the event, with over 500 sessions planned.

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AWS Machine Learning Blog

DECEMBER 24, 2024

To simplify infrastructure setup and accelerate distributed training, AWS introduced Amazon SageMaker HyperPod in late 2023. In this blog post, we showcase how you can perform efficient supervised fine tuning for a Meta Llama 3 model using PEFT on AWS Trainium with SageMaker HyperPod. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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AWS Machine Learning Blog

MARCH 15, 2024

In addition to Amazon Bedrock, you can use other AWS services like Amazon SageMaker JumpStart and Amazon Lex to create fully automated and easily adaptable generative AI order processing agents. In this post, we show you how to build a speech-capable order processing agent using Amazon Lex, Amazon Bedrock, and AWS Lambda.

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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

JANUARY 7, 2025

To address this need, AWS generative AI best practices framework was launched within AWS Audit Manager , enabling auditing and monitoring of generative AI applications. The agent then interprets the users request and determines if actions need to be invoked or information needs to be retrieved from a knowledge base.

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Flipboard

NOVEMBER 19, 2024

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 AWS tools without having to manage infrastructure. This can lead to inefficiencies, delays, and errors, diminishing customer satisfaction.

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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

DECEMBER 6, 2023

Fortunately, we can also use source knowledge to inform our LLMs. Source knowledge is information fed into the LLM through an input prompt. Using RAG, we retrieve relevant information from an external data source and feed that information into the LLM. Sign up for a free-tier Pinecone Vector Database.

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AWS Machine Learning Blog

DECEMBER 23, 2024

In a world where decisions are increasingly data-driven, the integrity and reliability of information are paramount. Lettria , an AWS Partner, demonstrated that integrating graph-based structures into RAG workflows improves answer precision by up to 35% compared to vector-only retrieval methods.

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Flipboard

NOVEMBER 27, 2024

In this post, we show you how to integrate the popular Slack messaging service with AWS generative AI services to build a natural language assistant where business users can ask questions of an unstructured dataset. Chunks are vectorized and stored in a vector database.

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AWS Machine Learning Blog

APRIL 11, 2024

Manually processing these documents to classify and extract information remains expensive, error prone, and difficult to scale. For more information, see Amazon Comprehend document classifier adds layout support for higher accuracy. Vector databases – Vector databases are used to store embeddings.

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