Want 98% accuracy mining huge document libraries while saving more than 80% on your AI spend?Stanford researchers developed minionS, a ridiculously smart process prompting single-step instructions on chunks of a document using Llama-3B locally with GPT-4 Turbo as the costly adjudicator-in-waiting.minionS resulted in 80% of tokens being processed locally - with 98% accuracy compared to 100% reliance on cloud compute.Large enterprise? We could be talking a saving of $2.3m on a $2.8m annual spend.Even if you run a small coffee shop franchise, the difference could be enough to open a new store this year.Think of the use cases: Knowledge base management and querying Report generation Real-time analytics.And if you love saving money while driving growth, this is just the beginning. Neural architecture search and dynamic model selection promise an additional 40% cost reduction by 2026.Thanks for listening to AI Today!

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