Every AI hallucinates.
Or does it?
The fear-mongering on the street is LLMs will always hallucinate 😱.
These AI failure modes include:
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🤦♂️ in-context recall mistakes by LLMs
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👋 six-fingered hands by diffusion models
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🌐 foundational knowledge errors
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🧠 generative reasoning errors
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🙋♂️ your AI glitch
It would seem the sky is falling. Or is it?
Fortunately, we can stop hallucinations
Specifically, we've created a technology, hypertokens, that can eliminate such errors by any AI LLM model to any desired level of precision for any task:
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🌎 embedding — think better database indexes & searches
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📈 fine-tuning — align an AI model to your domain of interest
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💻 inference — think ChatGPT, Gemini or other chatbots
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💬 recalling — in-context or foundational knowledge
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💡 reasoning — drawing logical conclusions
Seriously?
Yes. Think of an AI prompt as a puzzle with many missing pieces!
Hypertokens add those missing pieces in a computationally rigorous way that leverages concepts from information theory, mathematics, stats, and many related artificial intelligence (AI) and machine learning (ML) disciplines.
More colloquially, we put the engineering in prompt engineering in a way that aligns any AI model for any task on any length of input.
