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A new era of discovery

AI is revolutionizing the landscape of scientific research, enabling advancements at a pace that was once unimaginable — from accelerating drug discovery to designing new materials for clean energy technologies. The AI for Science Forum — co-hosted by Google DeepMind and the Royal Society — brought together the scientific community, policymakers, and industry leaders to…

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Addressing Missing Data. Understand missing data patterns (MCAR… | by Gizem Kaya | Nov, 2024

Understand missing data patterns (MCAR, MNAR, MAR) for better model performance with Missingno In an ideal world, we would like to work with datasets that are clean, complete and accurate. However, real-world data rarely meets our expectation. We often encounter datasets with noise, inconsistencies, outliers and missingness, which requires careful handling to get effective results.…

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Microsoft Research Introduces Reducio-DiT: Enhancing Video Generation Efficiency with Advanced Compression

Recent advancements in video generation models have enabled the production of high-quality, realistic video clips. However, these models face challenges in scaling for large-scale, real-world applications due to the computational demands required for training and inference. Current commercial models like Sora, Runway Gen-3, and Movie Gen demand extensive resources, including thousands of GPUs and millions…

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ChatGPT: Two Years Later. Tracing the impact of the generative AI… | by Julián Peller | Nov, 2024

This November 30 marks the second anniversary of ChatGPT’s launch, an event that sent shockwaves through technology, society, and the economy. The space opened by this milestone has not always made it easy — or perhaps even possible — to separate reality from expectations. For example, this year Nvidia became the most valuable public company…

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