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Chronomics detects COVID-19 test results with Amazon Rekognition Custom Labels

Chronomics is a tech-bio company that uses biomarkers—quantifiable information taken from the analysis of molecules—alongside technology to democratize the use of science and data to improve the lives of people. Their goal is to analyze biological samples and give actionable information to help you make decisions—about anything where knowing more about the unseen is important. …

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How a steel distributor reinvents its data science & ML workflows with Vertex AI

Nowadays, many companies have to ask themselves: Do we want to wait until a startup disrupts our business model or will we just do it on our own? Klöckner, a German steel and metal distributor, chose the second option, leveraging the power of Google Cloud to  bring a more customer-focused, agile approach to an industry …

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2023 Predictions: AI That Bends Reality, Unwinds the Golden Screw and Self-Replicates

After three years of uncertainty caused by the pandemic and its post-lockdown hangover, enterprises in 2023 — even with recession looming and uncertainty abounding — face the same imperatives as before: lead, innovate and problem solve. AI is becoming the common thread in accomplishing these goals. On average, 54% of enterprise AI projects made it …

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Ferrari of Finance: Accelerated Computing Drives Milan Bank Forward

Banks require more than cash in the vault these days, they also need accelerated computing in the back room. “The boost we’re getting with GPUs not only significantly improved our performance at the same cost, it helped us redefine our business and sharpen our focus on customers,” said Marco Airoldi, who’s been head of financial …

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Image augmentation pipeline for Amazon Lookout for Vision

Amazon Lookout for Vision provides a machine learning (ML)-based anomaly detection service to identify normal images (i.e., images of objects without defects) vs anomalous images (i.e., images of objects with defects), types of anomalies (e.g., missing piece), and the location of these anomalies. Therefore, Lookout for Vision is popular among customers that look for automated …

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Amazon SageMaker JumpStart now offers Amazon Comprehend notebooks for custom classification and custom entity detection

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text. Amazon Comprehend provides customized features, custom entity recognition, custom classification, and pre-trained APIs such as key phrase extraction, sentiment analysis, entity recognition, and more so you can easily integrate NLP into your applications. We recently added …

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Building out your support insights pipeline

Getting into the details We wrote previously about how we used clustering to connect requests for support (in text form) to the best tech support articles so we could answer questions faster and more efficiently. In a constantly changing environment (and in a very oddball couple of years) we wanted to make sure we’re focused …

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Kontinuierliches und skalierbares Schwachstellenmanagement bei Palantir

(An English-language version of this post can be read here.) Disclaimer: Bei dem folgendem Blogpost handelt es sich um eine aktualisierte deutsche Version des bereits im Englischen veröffentlichten Blogposts “How Palantir Manages Continuous Vulnerability Scanning At Scale.” Er bezieht sich konkret auf Cloud-Implementierungen von Palantir-Produkten. Bei Kunden, die eine on-prem Installation verwalten, gelten u.U.. andere Prozesse …

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The Ontology: Operating at optimum complexity — as simply as possible

The Ontology: Operating at optimum complexity — as simply as possible Editor’s Note: In this blog post, Senior Director of Enterprise Technology Markus Löffler discusses the principles underlying his belief that the Palantir Foundry Ontology can transform any enterprise. I believe the Ontology is the foundational element for the modern software stack. In this post, I will tell you why. …

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Production Infrastructure at Palantir: User-minded API design

Intro It’s trendy right now for organizations to describe themselves as “outcome-oriented,” where members of the organization are accountable for the results of their work. The Production Infrastructure group at Palantir commits itself to being oriented around our users’ outcomes — but how does this translate into building good software? Our users’ outcomes are often dictated by …