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

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Reactions to the Bipartisan US House AI Task Force Report

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Partner spotlight: How Cerebras accelerates AI app development

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Sundar Pichai teases new Google AI products and more for 2025

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You can now fine-tune your own version of AI image maker...

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Samant Kumar, Portfolio Manager at Capgemini — Defining Agile Transformation, Overcoming...

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Controversial science: AI and Nobel Prizes

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Partner spotlight: How Cerebras accelerates AI app development

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Here’s our forecast for AI this year

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Movie Gen – the future of AI video generation

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Jessica Marie, Founder and CEO of Omnia Strategy Group — Philosophy...

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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...