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Hugging Face Researchers Warn AI-Generated Video Consumes Much More Power Than Expected
"Researchers have found that the carbon footprint of generative AI-based tools that can turn text prompts into images and videos is far worse than we previously thought," writes Futurism: As detailed in a new paper, researchers from the open-source AI platform Hugging Face found that the energy de...
"Researchers have found that the carbon footprint of generative AI-based tools that can turn text prompts into images and videos is far worse than we previously thought," writes Futurism: As detailed in a new paper, researchers from the open-source AI platform Hugging Face found that the energy demands of text-to-video generators quadruple when the length of a generated video doubles — indicating that the power required for increasingly sophisticated generations doesn't scale linearly. "These findings highlight both the structural inefficiency of current video diffusion pipelines and the urgent need for efficiency-oriented design," the researchers concluded in their paper... Fortunately, there are ways to slim down those demands, including intelligent caching, the reusing of existing AI generations, and " pruning," meaning the sifting out of inefficient examples from training datasets. Video Killed the Energy Budget: Characterizing the Latency and Power Regimes of Open Text-to-Video Mode."
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