Empower your business users to extract insights from company documents using Amazon SageMaker Canvas Generative AI

Favorite Enterprises seek to harness the potential of Machine Learning (ML) to solve complex problems and improve outcomes. Until recently, building and deploying ML models required deep levels of technical and coding skills, including tuning ML models and maintaining operational pipelines. Since its introduction in 2021, Amazon SageMaker Canvas has

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Shared by AWS Machine Learning October 27, 2023

Intuitivo achieves higher throughput while saving on AI/ML costs using AWS Inferentia and PyTorch

Favorite This is a guest post by Jose Benitez, Founder and Director of AI and Mattias Ponchon, Head of Infrastructure at Intuitivo. Intuitivo, a pioneer in retail innovation, is revolutionizing shopping with its cloud-based AI and machine learning (AI/ML) transactional processing system. This groundbreaking technology enables us to operate millions

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Shared by AWS Machine Learning October 27, 2023

Intelligently search Drupal content using Amazon Kendra

Favorite Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra helps you easily aggregate content from a variety of content repositories into a centralized index that lets you quickly search all your enterprise data and find the most accurate answer. Drupal is a content management

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Shared by AWS Machine Learning October 27, 2023

Detection and high-frequency monitoring of methane emission point sources using Amazon SageMaker geospatial capabilities

Favorite Methane (CH4) is a major anthropogenic greenhouse gas that‘s a by-product of oil and gas extraction, coal mining, large-scale animal farming, and waste disposal, among other sources. The global warming potential of CH4 is 86 times that of CO2 and the Intergovernmental Panel on Climate Change (IPCC) estimates that methane is

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Shared by AWS Machine Learning October 26, 2023

T-Mobile US, Inc. uses artificial intelligence through Amazon Transcribe and Amazon Translate to deliver voicemail in the language of their customers’ choice

Favorite This post is co-authored by Dhurjati Brahma, Senior Systems Architect at T-Mobile US, Inc and Jim Chao, Principal Engineer/Architect at T-Mobile US, Inc and Nicholas Zellerhoff Associate Systems Architect at T-Mobile US, Inc. T-Mobile US, Inc. provides a Voicemail to Text service to its customers, which allows customers to

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Shared by AWS Machine Learning October 25, 2023

Intelligent document processing with Amazon Textract, Amazon Bedrock, and LangChain

Favorite In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document processing methods often fall short in efficiency and accuracy, leaving room for innovation, cost-efficiency, and optimizations. Document processing has witnessed significant advancements with the advent

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Shared by AWS Machine Learning October 25, 2023

From text to dream job: Building an NLP-based job recommender at Talent.com with Amazon SageMaker

Favorite This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Founded in 2011, Talent.com is one of the world’s largest sources of employment. The company combines paid job listings from their clients with public job listings into a single searchable platform.

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Shared by AWS Machine Learning October 24, 2023

Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

Favorite 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. However, implementing security, data privacy, and governance controls are still key challenges

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Shared by AWS Machine Learning October 20, 2023