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This report tried to estimate AI energy usage, which is a...

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The Elephant in the Room in the Google Search Case: Generative...

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Pradeep Etikani, Staff Software Engineer at Walmart — AI and Cloud...

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The next evolution of AI for business: our brand story

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AI slashes cost and time for chip design, but that is...

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Thoughts on Watermarking AI-Generated Content

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Revolutionize Image Editing with Adobe’s AI Tool

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AI admin tools pose a threat to national security

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4 bold AI predictions for 2025

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The DataRobot Enterprise AI Suite: driving the next evolution of AI...

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What the European Commission’s focus on AI industrial policy means for...

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Sampling Without Data is Now Scalable: Meta AI Releases Adjoint Sampling...

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Meta Researchers Introduced J1: A Reinforcement Learning Framework That Trains Language...

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This AI Paper Introduces PARSCALE (Parallel Scaling): A Parallel Computation Method...

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Marktechpost Releases 2025 Agentic AI and AI Agents Report: A Technical...

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Sampling Without Data is Now Scalable: Meta AI Releases Adjoint Sampling...

Data Scarcity in Generative Modeling Generative models traditionally rely on large, high-quality datasets to produce samples that replicate the underlying data distribution. However, in fields like molecular modeling or physics-based inference, acquiring such data can be computationally infeasible or even impossible. Instead of labeled data, only a scalar reward—typically derived...