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Meta’s open AI hardware vision

Hacker News

Over the course of 2023, we rapidly scaled up our training clusters from 1K, 2K, 4K, to eventually 16K GPUs to support our AI workloads. Today, we’re training our models on two 24K-GPU clusters. We don’t expect this upward trajectory for AI clusters to slow down any time soon. Building AI clusters requires more than just GPUs.

AI 180
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Racing into the future: How AWS DeepRacer fueled my AI and ML journey

AWS Machine Learning Blog

In 2018, I sat in the audience at AWS re:Invent as Andy Jassy announced AWS DeepRacer —a fully autonomous 1/18th scale race car driven by reinforcement learning. For 2018, because AWS DeepRacer had just been unveiled, re:Invent attendees could compete in person at the MGM Grand using pre-trained models.

AWS 91
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The mystery of indexing – A guide to different types of indexes in Python

Data Science Dojo

Clustered Indexes : have ordered files and built on non-unique columns. You may only build a single Primary or Clustered index on a table. In 2018, the old librarian asked an expert to create an index based on Book ID, assigned to each book at the time when it is stored in the library.

Python 369
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The history of Kubernetes

IBM Journey to AI blog

Borg’s large-scale cluster management system essentially acts as a central brain for running containerized workloads across its data centers. Omega took the Borg ecosystem further, providing a flexible, scalable scheduling solution for large-scale computer clusters. Control plane nodes , which control the cluster.

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Machine Learning Interview Questions to Land the Perfect Data Science Job

Smart Data Collective

The Bureau of Labor Statistics reports that there were over 31,000 people working in this field back in 2018. Is K-means clustering different from KNN? Are you looking to get a job in big data? That could be a wise career move. The median annual wage is $118,370. However, it is not easy to get a career in big data.

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Data-driven insight in the era PII

Precisely

The European Union’s General Data Protection Regulation (commonly known as GDPR) came into effect on the 25th May 2018. The number crunching statistical routines used to build these systems cluster neighborhoods of similar types together, revealing a national social taxonomy.

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Effectively solve distributed training convergence issues with Amazon SageMaker Hyperband Automatic Model Tuning

AWS Machine Learning Blog

Amazon SageMaker distributed training jobs enable you with one click (or one API call) to set up a distributed compute cluster, train a model, save the result to Amazon Simple Storage Service (Amazon S3), and shut down the cluster when complete. Finally, launching clusters can introduce operational overhead due to longer starting time.