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Source channel @githubtrending · Post #15123 · Sep 6

#rust#artificial_intelligence#big_data#data_engineering#distributed_computing#machine_learning#multimodal#python#rust Daft is a powerful, easy-to-use data engine that lets you process large-scale data using Python or SQL with high speed and efficiency. It supports complex data types like images and tensors, works well interactively for quick data exploration, and can scale to huge cloud clusters using Ray. Daft integrates smoothly with cloud storage and data catalogs, making it ideal for data engineering, analytics, and machine learning workflows. By using Daft, you can handle big, multimodal datasets faster and more flexibly, improving your ability to analyze and prepare data for AI models without complex setup or slowdowns. https://github.com/Eventual-Inc/Daft

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Google Facts™ [ ️@googlefactss🌎]

@googlefactss · Post #40776 · 03/11/2026, 11:01 PM

During World War II, engineers studied planes that returned from missions. They first thought the areas with the most bullet holes needed armor. Statistician Abraham Wald realized this was survivorship bias. Survivorship bias happens when you focus only on survivors and ignore failures.The undamaged areas on returning planes were actually the critical spots. Planes hit there did not survive. He recommended reinforcing those undamaged areas. ✈️📊🛡️ [Read more] @googlefactss #SurvivorshipBias#WWII#AbrahamWald#Planes#Statistics#History