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Machine learning news and insights

Import AI 233: AI needs AI designers; estimating COVID risk with AI; the dreams of an old computer programmer.

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Facebook trains a COVID-risk-estimating X-ray image analysis system:…Collaboration with NYU yields a COVID-spotting AI model…Facebook has worked with NYU to analyze chest X-rays from people with COVID and has created an AI system that can roughly estimate risks for different people. One of the things this work sheds light on is the different amounts of data we need for training...





Building, automating, managing, and scaling ML workflows using Amazon SageMaker Pipelines

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We recently announced Amazon SageMaker Pipelines, the first purpose-built, easy-to-use continuous integration and continuous delivery (CI/CD) service for machine learning (ML). SageMaker Pipelines is a native workflow orchestration tool for building ML pipelines that take advantage of direct Amazon SageMaker integration. Three components improve the operational resilience and reproducibility of your ML workflows: pipelines, model […]


Import AI 232: Google trains a trillion parameter model; South Korean chatbot blows up; AI doesn’t use as much electricity as you think

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Uh-oh, Parler is about to step on a big ‘ol algorithm rake:…CEO says algorithms can filter hate speech. Good luck with that!…Parler, the social network used by far right activists and subsequently pulled offline due to failing to meet T&Cs from a variety of infrastructure services (including Amazon Web Services), has a plan to come back: it’s going to use...



Automating Amazon Personalize solution using the AWS Step Functions Data Science SDK

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Machine learning (ML)-based recommender systems aren’t a new concept across organizations such as retail, media and entertainment, and education, but developing such a system can be a resource-intensive task—from data labelling, training and inference, to scaling. You also need to apply continuous integration, continuous deployment, and continuous training to your ML model, or MLOps. The […]


How to train procedurally generated game-like environments at scale with Amazon SageMaker RL

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A gym is a toolkit for developing and comparing reinforcement learning algorithms. Procgen Benchmark is a suite of 16 procedurally-generated gym environments designed to benchmark both sample efficiency and generalization in reinforcement learning.  These environments are associated with the paper Leveraging Procedural Generation to Benchmark Reinforcement Learning (citation). Compared to Gym Retro, these environments have […]



Hosting a private PyPI server for Amazon SageMaker Studio notebooks in a VPC

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Amazon SageMaker Studio notebooks provide a full-featured integrated development environment (IDE) for flexible machine learning (ML) experimentation and development. Security measures secure and support a versatile and collaborative environment. In some cases, such as to protect sensitive data or meet regulatory requirements, security protocols require that public internet access be disabled in the development environment. […]

Import AI 231: US army builds nightvision facial recognition; 800GB of text for training GPT-3 models; fighting COVID with a mask detector

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Fighting COVID with a janky mask detector:…It’s getting really, really easy to homebrew surveillance tech…Researchers with Texas A&M university, the University of Wisconsin-Milwaukee, and the State University of New York at Binghamtom, have built a basic AI model that can detect whether construction site workers are wearing COVID masks or not. The model itself is super basic – they finetune...









Import AI 229: Apple builds a Hypersim dataset; ways to attack ML; Google censors its research

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Apple builds Hypersim, a dataset to help it understand your house:…High-resolution synthetic scenes = fuel for machine learning algorithms…Apple has built Hypersim, a dataset of high-resolution synthetic scenes with per-pixel labels. Hypersim consists of 77,400 images spread across 461 distinct indoor scenes; Apple bought the synthetic scenes from artists, then built a rendering pipeline to help it generate lots of...