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 …
(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 …
Read more “Kontinuierliches und skalierbares Schwachstellenmanagement bei Palantir”
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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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 …
Read more “Production Infrastructure at Palantir: User-minded API design”
Posted by Alexis Morvan and Trond Andersen, Research Scientists, Google Quantum AI When quantum computers were first proposed, they were hoped to be a way to better understand the quantum world. With a so-called “quantum simulator,” one could engineer a quantum computer to investigate how various quantum phenomena arise, including those that are intractable to …
Read more “Formation of Robust Bound States of Interacting Photons”
Data preparation is a principal component of machine learning (ML) pipelines. In fact, it is estimated that data professionals spend about 80 percent of their time on data preparation. In this intensive competitive market, teams want to analyze data and extract more meaningful insights quickly. Customers are adopting more efficient and visual ways to build …
Read more “Prepare data from Amazon EMR for machine learning using Amazon SageMaker Data Wrangler”
Across all industries, machine learning (ML) models are getting deeper, workflows are getting more complex, and workloads are operating at larger scales. Significant effort and resources are put into making these models more accurate since this investment directly results in better products and experiences. On the other hand, making these models run efficiently in production …
In this post, we show how to train, deploy, and predict natural disaster damage with Amazon SageMaker with geospatial capabilities. We use the new SageMaker geospatial capabilities to generate new inference data to test the model. Many government and humanitarian organizations need quick and accurate situational awareness when a disaster strikes. Knowing the severity, cause, …
Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning (ML) models based on your data, while allowing you to maintain full control and visibility. Autopilot can also deploy trained models to real-time inference endpoints automatically. If you have workloads with spiky or unpredictable traffic patterns that can tolerate cold starts, then deploying …
Read more “Deploy Amazon SageMaker Autopilot models to serverless inference endpoints”
Imagine trying to teach a toddler what a unicorn is. A good place to start might be by showing the child images of the creature and describing its unique features. Now imagine trying to teach an artificially intelligent machine what a unicorn is. Where would one even begin? Pretrained AI models offer a solution. A …