AWS Machine Learning Blog

NOVEMBER 7, 2024

Operating such large-scale forecasting requires resilient, reusable, reproducible, and automated machine learning (ML) workflows with fast experimentation and continuous improvements. To improve forecasting accuracy, all involved ML models need to be retrained, and predictions need to be produced weekly, and in some cases daily.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

From gaming and entertainment to education and corporate events, live streams have become a powerful medium for real-time engagement and content consumption. The extension delivers a web application implemented using the AWS SDK for JavaScript and the AWS Amplify JavaScript library.

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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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Flipboard

NOVEMBER 15, 2024

By harnessing the capabilities of generative AI, you can automate the generation of comprehensive metadata descriptions for your data assets based on their documentation, enhancing discoverability, understanding, and the overall data governance within your AWS Cloud environment. You need the following prerequisite resources: An AWS account.

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AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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AWS Machine Learning Blog

JULY 3, 2024

They often find themselves struggling with language barriers when it comes to setting up reminders for events like business gatherings and customer meetings. The steps could be AWS Lambda functions that generate prompts, parse foundation models’ output, or send email reminders using Amazon SES. Generate an action plan list for events.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

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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

JUNE 26, 2024

Artificial intelligence and machine learning (AI/ML) technologies can assist capital market organizations overcome these challenges. Intelligent document processing (IDP) applies AI/ML techniques to automate data extraction from documents. We built the solution using the event-driven principles as depicted in the following diagram.

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AWS Machine Learning Blog

OCTOBER 10, 2023

Machine learning (ML), especially deep learning, requires a large amount of data for improving model performance. Customers often need to train a model with data from different regions, organizations, or AWS accounts. Federated learning (FL) is a distributed ML approach that trains ML models on distributed datasets.

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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. API Gateway also provides a WebSocket API. These components are illustrated in the following diagram.

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AWS Machine Learning Blog

JANUARY 13, 2023

In this post, we show you how Parsons is building its next generation workforce by using machine learning (ML) and artificial intelligence (AI) with AWS DeepRacer in a fun and collaborative way. Parsons is on a mission to make AI/ML a foundation of business across the company.

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AWS Machine Learning Blog

JULY 25, 2024

In the post, we introduce the AWS Neuron node problem detector and recovery DaemonSet for AWS Trainium and AWS Inferentia on Amazon Elastic Kubernetes Service (Amazon EKS). Additionally, the node recovery agent will publish Amazon CloudWatch metrics for users to monitor and alert on these events. install.sh

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AWS Machine Learning Blog

NOVEMBER 21, 2024

The integrated approach and ease of use of Amazon Bedrock in deploying large language models (LLMs), along with built-in features that facilitate seamless integration with other AWS services like Amazon Kendra, made it the preferred choice. This workflow integrates AWS services to extract, process, and make content available for querying.

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AWS Machine Learning Blog

JUNE 22, 2023

Working with AWS, Light & Wonder recently developed an industry-first secure solution, Light & Wonder Connect (LnW Connect), to stream telemetry and machine health data from roughly half a million electronic gaming machines distributed across its casino customer base globally when LnW Connect reaches its full potential.

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AWS Machine Learning Blog

OCTOBER 10, 2024

To achieve this, the Rufus team is using multiple AWS services and AWS AI chips, AWS Trainium and AWS Inferentia. Inferentia and Trainium are purpose-built chips developed by AWS that accelerate deep learning workloads with high performance and lower overall costs. With these chips, Rufus reduced its costs by 4.5

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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. QnABot version 5.4+ Provide a name for the bot.

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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. AWS Support offers a range of capabilities powered by technology and subject matter experts that support the success and operational health of your AWS environments.

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AWS Machine Learning Blog

MARCH 1, 2023

The result of these events can be evaluated afterwards so that they make better decisions in the future. With this proactive approach, Kakao Games can launch the right events at the right time. Kakao Games can then create a promotional event not to leave the game. However, this approach is reactive.

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AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. By using a combination of AWS services, you can implement this feature effectively, overcoming the current limitations within SageMaker.

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AWS Machine Learning Blog

FEBRUARY 13, 2023

With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training models at scale.

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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. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities.

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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

MAY 14, 2024

RLHF is a technique that combines rewards and comparisons, with human feedback to pre-train or fine-tune a machine learning (ML) model. We present the solution and provide an example by simulating a case where the tier one AWS experts are notified to help customers using a chat-bot.

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AWS Machine Learning Blog

AUGUST 3, 2023

AWS intelligent document processing (IDP), with AI services such as Amazon Textract , allows you to take advantage of industry-leading machine learning (ML) technology to quickly and accurately process data from any scanned document or image. Generative AI is driven by large ML models called foundation models (FMs).

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AWS Machine Learning Blog

SEPTEMBER 27, 2024

Recent events including Tropical Cyclone Gabrielle have highlighted the susceptibility of the grid to extreme weather and emphasized the need for climate adaptation with resilient infrastructure. The workforce created a bounding box around stay wires and insulators and the output was subsequently used to train an ML model.

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AWS Machine Learning Blog

JUNE 21, 2023

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. For more information, refer to Working with the AWS CDK.

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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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AWS Machine Learning Blog

MAY 8, 2024

In 2022, Dialog Axiata made significant progress in their digital transformation efforts, with AWS playing a key role in this journey. Dialog Axiata runs some of their business-critical telecom workloads on AWS, including Charging Gateway, Payment Gateway, Campaign Management System, SuperApp, and various analytics tasks.

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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. AWS Prototyping developed an AWS Cloud Development Kit (AWS CDK) stack for deployment following AWS best practices.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Rocket Mortgage, America’s largest retail mortgage lender, revolutionizes homeownership with Rocket Logic – Synopsis, an AI tool built on AWS. By using existing solutions and AWS technical teams, Rocket significantly reduced the time to market, allowing for swift deployment. Opportunities for innovation Rocket services over 2.6

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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. Beyond hardware, data cleaning and processing, model architecture design, hyperparameter tuning, and training pipeline development demand specialized machine learning (ML) skills.

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ODSC - Open Data Science

OCTOBER 21, 2024

Fortunately, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. This topic is closely aligned with the Responsible AI track at ODSC West  — an event where experts gather to discuss innovations and challenges in AI.

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Flipboard

NOVEMBER 28, 2023

While it might be easier to start looking at an individual machine learning (ML) model and the associated risks in isolation, it’s important to consider the details of the specific application of such a model and the corresponding use case as part of a complete AI system. In this post, we focus on AI system risk, primarily.

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AWS Machine Learning Blog

SEPTEMBER 17, 2024

In this post, we demonstrate a solution using Amazon FSx for NetApp ONTAP with Amazon Bedrock to provide a RAG experience for your generative AI applications on AWS by bringing company-specific, unstructured user file data to Amazon Bedrock in a straightforward, fast, and secure way. Install the AWS Command Line Interface (AWS CLI).

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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. This feature helps isolate the enclave and your software, and significantly reduces the surface area for unintended events. hvm-2.0.20230628.0-x86_64-gp2

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