Cloudy days are over: How local AI saves millions delivering excellence

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.

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