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AI Company Plans to Run Clusters of 10,000 Nvidia H100 GPUs in International Waters

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Del Complex hopes floating its computer clusters in the middle of the ocean will allow it a level of autonomy unlikely to be found on land. Government …

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xAI’s Colossus supercomputer cluster uses 100,000 Nvidia Hopper GPUs — and it was all made possible using Nvidia’s Spectrum-X Ethernet networking platform

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Nvidia has shed light on how xAI’s ‘Colossus’ supercomputer cluster can keep a handle on 100,000 Hopper GPUs - and it’s all down to using the …

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A Quick Overview of Voronoi Diagrams

Analytics Vidhya

Introduction Voronoi diagrams, named after the Russian mathematician Georgy Voronoy, are fascinating geometric structures with applications in various fields such as computer science, geography, biology, and urban planning.

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Boost your forecast accuracy with time series clustering

AWS Machine Learning Blog

In this post, we seek to separate a time series dataset into individual clusters that exhibit a higher degree of similarity between its data points and reduce noise. The purpose is to improve accuracy by either training a global model that contains the cluster configuration or have local models specific to each cluster.

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Create Audience Segments Using K-Means Clustering in Python

ODSC - Open Data Science

One of the simplest and most popular methods for creating audience segments is through K-means clustering, which uses a simple algorithm to group consumers based on their similarities in areas such as actions, demographics, attitudes, etc. In this tutorial, we will work with a data set of users on Foursquare’s U.S.

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Speed up your cluster procurement time with Amazon SageMaker HyperPod training plans

AWS Machine Learning Blog

However, customizing these larger models requires access to the latest and accelerated compute resources. In this post, we demonstrate how you can address this requirement by using Amazon SageMaker HyperPod training plans , which can bring down your training cluster procurement wait time. For Target , select HyperPod cluster.

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Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod

AWS Machine Learning Blog

It is important to consider the massive amount of compute often required to train these models. When using compute clusters of massive size, a single failure can often throw a training job off course and may require multiple hours of discovery and remediation from customers.