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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Dataconomy

FEBRUARY 6, 2024

With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

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AWS Machine Learning Blog

JANUARY 6, 2023

The recently published IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment positions AWS in the Leaders category. The tools are typically used by data scientists and ML developers from experimentation to production deployment of AI and ML solutions. AWS position.

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AWS Machine Learning Blog

AUGUST 7, 2023

In an effort to create and maintain a socially responsible gaming environment, AWS Professional Services was asked to build a mechanism that detects inappropriate language (toxic speech) within online gaming player interactions. Unfortunately, as in the real world, not all players communicate appropriately and respectfully.

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IBM Journey to AI blog

MAY 26, 2023

In 2017, 94% of hospitals used electronic clinical data from their EHR. The role of AWS and cloud security in life sciences However, with greater power comes great responsibility. Most life sciences companies are raising their security posture with AWS infrastructure and services.

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AWS Machine Learning Blog

SEPTEMBER 29, 2023

In late 2023, Planet announced a partnership with AWS to make its geospatial data available through Amazon SageMaker. In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Planet’s data is therefore a valuable resource for geospatial ML.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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AWS Machine Learning Blog

JULY 9, 2024

of its consolidated revenues during the years ended December 31, 2019, 2018 and 2017, respectively. Currently he helps customers in the financial service and insurance industry build machine learning solutions on AWS. Scott Mullins is Managing Director and General Manger of AWS’ Worldwide Financial Services organization.

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AWS Machine Learning Blog

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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Flipboard

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

JUNE 8, 2023

LLMs are based on the Transformer architecture , a deep learning neural network introduced in June 2017 that can be trained on a massive corpus of unlabeled text. This enables you to begin machine learning (ML) quickly. A SageMaker real-time inference endpoint enables fast, scalable deployment of ML models for predicting events.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

Examples include: Cultivating distrust in the media Undermining the democratic process Spreading false or discredited science (for example, the anti-vax movement) Advances in artificial intelligence (AI) and machine learning (ML) have made developing tools for creating and sharing fake news even easier.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. The following are a few example RGB images and their labels.

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AWS Machine Learning Blog

MARCH 21, 2023

Amazon SageMaker geospatial capabilities —now generally available in the AWS Oregon Region—provide a new and much simpler solution to this problem. The tool makes it easy to access geospatial data sources, run purpose-built processing operations, apply pre-trained ML models, and use built-in visualization tools faster and at scale.

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Towards AI

APRIL 19, 2024

Amazon (AWS) 👉Industry domain: Online retail and web services provider 👉Location: Over 175 Amazon fulfillment centers globally 👉Year founded: 1994 👉Key Products developed: Amazon Bedrock, Q, Code Whisperer, Sage Maker 👉Benefits: Fully managed generative AI service options, AWS free tier for experimentation 7.

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AWS Machine Learning Blog

MAY 5, 2023

This is a joint post co-written by AWS and Voxel51. For our example use case, we work with the Fashion200K dataset , released at ICCV 2017. Ideally, someone using your application only needs to take pictures of the clothes in their wardrobe, and your ML models work their magic behind the scenes. Then import the relevant modules.

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Snorkel AI

MAY 24, 2023

Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. He was previously a senior leader at AWS, and the CTO of Analytics & ML at IBM.

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Snorkel AI

MAY 24, 2023

Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. He was previously a senior leader at AWS, and the CTO of Analytics & ML at IBM.

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AWS Machine Learning Blog

OCTOBER 16, 2024

With the power of advanced language models and machine learning (ML) algorithms, generative AI can understand the context and intent behind a programmer’s code, offering valuable suggestions, completing code snippets, and even generating entire functions or modules based on high-level descriptions. link] swagger: '2.0'

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Mlearning.ai

AUGUST 6, 2023

That was in 2017. The first two rounds were highly technical and involved challenging leet-code style coding questions which I had to perform live, as well as discussions on ML theory. Do we really need to use ML, or can some rule-based approach work just as well? I also learnt about cloud computing, specifically, AWS.

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Flipboard

MARCH 23, 2023

All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. Facebook/Meta’s LLaMA, which is smaller than GPT-3 and GPT-4, is thought to have taken roughly one million GPU hours to train, which would cost roughly $2 million on AWS.

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IBM Journey to AI blog

JULY 19, 2023

In this blog post, we will showcase how IBM Consulting is partnering with AWS and leveraging Large Language Models (LLMs), on IBM Consulting’s generative AI-Automation platform (ATOM), to create industry-aware, life sciences domain-trained foundation models to generate first drafts of the narrative documents, with an aim to assist human teams.

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Dataconomy

APRIL 25, 2023

HubSpot can help you create engaging landing pages, email campaigns, social media posts, and chatbots using natural language processing (NLP) and machine learning (ML). AWS AI enables businesses to easily and quickly build and deploy AI applications using pre-trained models or custom ones. It is one of the best AI tools for business.

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AWS Machine Learning Blog

MARCH 30, 2023

Amazon Personalize is a fully managed machine learning (ML) service that makes it easy for developers to deliver personalized experiences to their users. You can get started without any prior ML experience, using APIs to easily build sophisticated personalization capabilities in a few clicks. Choose the new aws-trending-now recipe.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

You can easily try out these models and use them with SageMaker JumpStart, which is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. The model is deployed in an AWS secure environment and under your VPC controls, helping ensure data security.

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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 27, 2024

Solution overview The chess demo uses a broad spectrum of AWS services to create an interactive and engaging gaming experience. On the frontend, AWS Amplify hosts a responsive React TypeScript application while providing secure user authentication through Amazon Cognito using the Amplify SDK. The demo offers a few gameplay options.

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AWS Machine Learning Blog

NOVEMBER 6, 2024

Amazon Transcribe is a machine learning (ML) based managed service that automatically converts speech to text, enabling developers to seamlessly integrate speech-to-text capabilities into their applications. Transcribe audio with Amazon Transcribe In this case, we use an AWS re:Invent 2023 technical talk as a sample.

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