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Data News — Week 23.40

Christophe Blefari

To be honest this is not the first time I see LLMs and compression in the same paper and it opens, at least, to funny experiments. — Vantage did a price analysis between Microsoft Fabric and Databricks. Language Modeling is compression — Paper from Deepmind. Title looks cool. Goodbye Spark.

Python 130
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Our Learnings from the Early Days of Generative AI

LinkedIn Engineering

It’s been an exciting few months at LinkedIn, as our engineering and product teams have been working hard to build some new and advanced AI-powered experiences for our members and customers. We recently shared some big moments around new AI-powered experiences, specifically leveraging generative AI in our products.

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Six Sigma Green Belt Project Examples & How to Execute?

Knowledge Hut

These projects aim to solve the problems of customers (both internal and external). He suggests a number of relevant topics and areas for conversation that all Champions, Sponsors, and Belts should explore based on his 15 years of experience. Return to the same vantage points or angles after the improvements have been made.

Project 98
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How Air France-KLM Group Uses Cross-Channel Analytics to Smoothly Connect Over 100M Passengers

Teradata

Using Vantage, Air France-KLM Group performs cross-channel analytics of customer data to provide a seamless experience for their passengers.

Data 96
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Using COD and CML to build applications that predict stock data

Cloudera

Continuing from my previous blog post about how awesome and easy it is to develop web-based applications backed by Cloudera Operational Database (COD), I started a small project to integrate COD with another CDP cloud experience, Cloudera Machine Learning (CML). . App Serving – Build and Serve Custom applications for ML use-cases.

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Larry H Miller Sports & Entertainment

Teradata

The Utah Jazz create winning customer experiences using Teradata Vantage on AWS with consumption pricing for flexible and elastic modern cloud analytics.

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The evolution of Facebook’s iOS app architecture

Engineering at Meta

The app makes heavy use of code generation, spurred by Buck , our custom build system. The app’s codebase reflects 10 years of evolution , spurred by technical decisions necessary to support the growing number of engineers working on the app, its stability, and, above all, the user experience.