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Dell’Oro Group: AI data center switch spending to exceed $100 billion by 2029

Dataconomy

Boujelbene noted that Ethernet is gaining traction as the primary fabric for large-scale AI clusters, driven by supply and demand dynamics. Notably, even major NVIDIA GPU-based clusters, such as xAI’s Colossus, are adopting Ethernet, prompting an advancement in the projected crossover timeline of Ethernet with InfiniBand by one year.

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Your next phone will live longer thanks to Brussels

Dataconomy

Why Brussels pulled the trigger The European Commission expects the EU smartphone ecodesign 2025 package to cut nearly 14 TWh of primary energy every year by 2030, shrink household gadget spending by 20 billion , and eliminate roughly 8.1 That means critical patches through 2030 for any handset launched in mid-2025.

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How climate tech startups are building foundation models with Amazon SageMaker HyperPod

Flipboard

SageMaker HyperPod is a purpose-built infrastructure service that automates the management of large-scale AI training clusters so developers can efficiently build and train complex models such as large language models (LLMs) by automatically handling cluster provisioning, monitoring, and fault tolerance across thousands of GPUs.

AWS 104
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How To Enhance Your Analytics with Insightful ML Approaches

Smart Data Collective

Clustering. ?lustering lustering is an approach where several data points are clustered according to the similarity between them, so they are easier to interpret and manage. ?lustering Once clustering is complete, domain experts can interpret these clusters to better understand the business or apply it to different classifications.

ML 132
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Five machine learning types to know

IBM Journey to AI blog

The most common unsupervised learning method is cluster analysis, which uses clustering algorithms to categorize data points according to value similarity (as in customer segmentation or anomaly detection ). K-means clustering is commonly used for market segmentation, document clustering, image segmentation and image compression.

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The internet of AI will be more powerful than any single AI. How do we keep it safe?

Dataconomy

trillion to the global economy by 2030. individual computers or clusters spread across the globe) continue to join the network, the IoA’s processing power can increase conjunctially. For example, a recent study by PwC predicts the AI industry contributing $15.7

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How To Learn Python For Data Science?

Pickl AI

million by 2030, with a staggering revenue CAGR of 44.8%, mastering this language is more crucial than ever. Scikit-learn covers various classification , regression , clustering , and dimensionality reduction algorithms. It enables analysts and researchers to manipulate and analyse vast datasets efficiently.