Which approach has been demonstrated to reduce the carbon footprint of large language models by up to 90% while maintaining comparable performance?

Natural Language Processing (NLP) technologies have revolutionized how we interact with language, but many don't realize their environmental impact. Large language models require massive computing resources and energy consumption. This poll explores the sustainability aspects of language technology and what companies are doing to address their carbon footprint in the language tech industry. Test your knowledge about the intersection of linguistics, computing power, and environmental sustainability!

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Knowledge distillation (creating smaller, more efficient student models from large teacher models)
Using specialized quantum computing hardware for NLP tasks
Running models exclusively on solar-powered data centers
Replacing neural networks with traditional rule-based systems