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Building Meta’s GenAI Infrastructure

Engineering at Meta

By the end of 2024, we’re aiming to continue to grow our infrastructure build-out that will include 350,000 NVIDIA H100 GPUs as part of a portfolio that will feature compute power equivalent to nearly 600,000 H100s. RSC has accelerated our open and responsible AI research by helping us build our first generation of advanced AI models.

Building 145
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On-Premise vs Cloud: Where Does the Future of Data Storage Lie?

Monte Carlo

Imagine you’ve been building houses with a hammer and nails for most of your career, and I gave you a nail gun. We want to empower AutoTrader and its customers to make data-informed decisions and democratize access to data through a self-serve platform….As FINDING DATA ANOMALIES IS HARD, FIXING THEM IS HARDER.

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Managing Database Access Control For Teams With strongDM

Data Engineering Podcast

Summary Controlling access to a database is a solved problem… right? It can be straightforward for small teams and a small number of storage engines, but once either or both of those start to scale then things quickly become complex and difficult to manage. What are some of the most interesting workarounds that you have seen?

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Azure for Data Science: Overview, Challenges, Technologies

Knowledge Hut

Cloud computing, along with data science has been the buzzword for quite some time now. Companies have moved towards cloud architecture for their data storage and computing needs. This will help you in your journey to become an Azure Certified Data Scientist or Microsoft’s DP 100 exam preparation.

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Building Cloud Native Data Apps on Premises

Cloudera

Data is core to decision making today and organizations often turn to the cloud to build modern data apps for faster access to valuable insights. Can you achieve similar outcomes with your on-premises data platform? You absolutely can. Today’s end users demand speed, agility, and cutting-edge features.

Cloud 64
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How to Build a Data Pipeline in 6 Steps

Ascend.io

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

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Data Science vs Cloud Computing: Differences With Examples

Knowledge Hut

It is impossible to escape from technology in today’s modern world. Technology is prone to expeditious growth that consists of ways that can highly impact the business industry. With the help of data science, one can gather all the critical analyses from vast chunks of data stored in clouds.