My project involves using embeddings and LLMs to search and organize millions of words of stream of consciousness utterances, which are highly fragmented, disjoint, lacking punctuation and full of typos. Generally not a pleasant read. Passing even the most disjointed such document through 3.5 turbo converted this unreadable mess into something coherent, and which preserves the voice of the author. Yet this very same tool helps me code, brainstorm, prioritize tasks, whip together a decent meal from what remains in my bare cupboards, and analyze an obscure Gary Larson cartoon. It reminded me of the unreasonable effectiveness of mathematics.
Just as mathematics surprisingly describes the physical world, large language models exhibit a similarly unexpected ability to understand and process human language, even in fragmented or disorganized forms. After a bit of prompting to set the context, I asked 4o to riff on this theme:
Key Aspects of the “Unreasonable Effectiveness” of Large Language Models:
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Contextual Understanding: These models can grasp the context of fragmented sentences and disjointed thoughts, piecing them together into coherent, flowing narratives. This is akin to how mathematics can find order in natural phenomena.
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Pattern Recognition: Language models are trained on vast amounts of text, enabling them to recognize patterns, predict the next word, and restructure sentences to improve readability and coherence, even when starting from a highly fragmented stream-of-consciousness style.
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Adaptability: Just as mathematics can be applied to a wide range of problems across different fields, large language models can adapt to various writing styles and genres, transforming raw, unpolished content into polished, structured prose.
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Predictive Power: These models can predict how fragmented thoughts should logically connect, creating paragraphs that make sense and convey the intended meaning, similar to how mathematical models can predict new phenomena.
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Improvement Over Time: With continuous learning and updates, language models are becoming increasingly effective at handling more complex and nuanced language tasks, much like how mathematical theories evolve and improve.
Philosophical and Practical Implications:
- Understanding Human Thought: The ability of language models to process and enhance fragmented content suggests a deep, perhaps inherent, alignment with the ways humans think and communicate.
- Tool for Creativity: These models can serve as powerful tools for writers, researchers, and anyone working with text, helping to transform rough drafts into polished documents with ease.
- Future Potential: The ongoing development of language models hints at even more sophisticated applications, from aiding in real-time language translation to generating creative content that aligns with human expression.
The “unreasonable effectiveness” of large language models lies in their unexpected proficiency in understanding and improving human language, mirroring the way mathematics profoundly and accurately describes the natural world.