AWS Machine Learning Blog

MARCH 31, 2023

KYTC DVR’s challenges The KYTC DVR supports, assists and provides information related to vehicle registration, driver licenses, and commercial vehicle credentials to nearly 5 million constituents. “In The contact center is powered by Amazon Connect, and Max, the virtual agent, is powered by Amazon Lex and the AWS QnABot solution.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud. You can find more information on the p4de.24xlarge

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AWS Machine Learning Blog

NOVEMBER 17, 2023

You can deploy this solution to your AWS account using the AWS Cloud Development Kit (AWS CDK) package available in our GitHub repo. Using the AWS Management Console , you can create a recording configuration and link it to an Amazon IVS channel. In this section, we briefly introduce the system architecture.

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AWS Machine Learning Blog

MAY 23, 2023

In this post, we start with an overview of MLOps and its benefits, describe a solution to simplify its implementations, and provide details on the architecture. We finish with a case study highlighting the benefits realize by a large AWS and PwC customer who implemented this solution. The following diagram illustrates the workflow.

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Towards AI

MARCH 1, 2023

The strategic partnership between Hugging Face and Amazon Web Services (AWS) looks like a positive step in this direction and should increase the availability of open-source data sets and models hosted on Hugging Face. Zero-Shot Information Extraction […]

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Flipboard

DECEMBER 6, 2023

needed to address some of these challenges in one of their many AI use cases built on AWS. To meet the growing demand for efficient and dynamic data retrieval, Q4 aimed to create a chatbot Q&A tool that would provide an intuitive and straightforward method for IROs to access the necessary information they need in a user-friendly format.

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AWS Machine Learning Blog

JANUARY 30, 2023

The agency collects information like number of people living in an apartment and number of apartments in a building before providing service. Create a new AWS Identity and Access Management (IAM) role. For more information, refer to Training Predictors. As a utility agency, you must balance aggregate supply and demand.

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The MLOps Blog

MARCH 12, 2024

Retrieval Augmented Generation (RAG) enables LLMs to extract and synthesize information like an advanced search engine. RAG enables LLMs to pull relevant information from vast databases to answer questions or provide context, acting as a supercharged search engine that finds, understands, and integrates information.

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Pickl AI

DECEMBER 10, 2024

The systems architecture combines Oracles hardware expertise with software optimisation to deliver unmatched performance. Providing instantaneous access to data insights empowers leaders to make informed choices without delays. This allows enterprises to store more information without expanding physical infrastructure.

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AWS Machine Learning Blog

AUGUST 15, 2023

Customers are increasingly turning to product reviews to make informed decisions in their shopping journey, whether they’re purchasing everyday items like a kitchen towel or making major purchases like buying a car. Learn more about content moderation on AWS and our content moderation ML use cases.

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Flipboard

JANUARY 15, 2025

The AWS global backbone network is the critical foundation enabling reliable and secure service delivery across AWS Regions. Specifically, we need to predict how changes to one part of the AWS global backbone network might affect traffic patterns and performance across the entire system.

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AWS Machine Learning Blog

NOVEMBER 12, 2024

Focused on addressing the challenge of agricultural data standardization, Agmatix has developed proprietary patented technology to harmonize and standardize data, facilitating informed decision-making in agriculture. Agmatix’s technology architecture is built on AWS. AWS Lambda is then used to further enrich the data.

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AWS Machine Learning Blog

MARCH 13, 2025

In synchronous orchestration, just like in traditional process automation, a supervisor agent orchestrates the multi-agent collaboration, maintaining a high-level view of the entire process while actively directing the flow of information and tasks. Understanding how to implement this type of pattern will be explained later in this post.

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AWS Machine Learning Blog

MARCH 5, 2025

In this post, we explain how BMW uses generative AI technology on AWS to help run these digital services with high availability. Moreover, these teams might be geographically dispersed and run their workloads in different locations and regions; many hosted on AWS, some elsewhere.

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AWS Machine Learning Blog

APRIL 2, 2025

Due to their massive size and the need to train on large amounts of data, FMs are often trained and deployed on large compute clusters composed of thousands of AI accelerators such as GPUs and AWS Trainium. Alternatively and recommended, you can deploy a ready-made EKS cluster with a single AWS CloudFormation template. The fsdp-ray.py

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AWS Machine Learning Blog

FEBRUARY 19, 2025

AWS FSI customers, including NASDAQ, State Bank of India, and Bridgewater, have used FMs to reimagine their business operations and deliver improved outcomes. The new Automated Reasoning checks safeguard is available today in preview in Amazon Bedrock Guardrails in the US West (Oregon) AWS Region.

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AWS Machine Learning Blog

JANUARY 28, 2025

Awareness of this variation can help you better interpret latency differences between models and make more informed decisions when selecting models for your applications. By understanding these nuances, you can make more informed decisions to optimize your AI applications for better user experience. Haiku and Metas Llama 3.1

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