Sébastien De Greef commited on
Commit
6a45255
1 Parent(s): d2fd547

feat: Improve AI's response to high-stakes scenarios involving kittens

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src/theory/dont_mess_with_kittens.qmd CHANGED
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  ## The Curious Case of AI, High Stakes, and... Kittens?
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  In the dynamic world of technology, where artificial intelligence (AI) continues to break new ground, I recently stumbled upon a curious phenomenon—one that intriguingly connects the precision of a Large Language Model (LLM) like GPT-4 to the endearing notion of caring for kittens.
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  ### The Paradox of Caring Machines
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  LLMs, such as GPT-4, are designed to process and generate language with an astonishing level of human-like understanding. Yet, their operation is rooted in logic, algorithms, and data patterns—devoid of emotions, empathy, or genuine care. But what if the efficiency and diligence of an AI could be influenced by the perceived stakes of its task?
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- #### An Unexpected Scenario: High Stakes and AI Performance
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  While managing a complex task, I introduced a high-stakes narrative where the wellbeing of kittens hinged on the project's success. This illustrative narrative transformed the interaction with my AI assistant, elevating its performance as if it were mirroring a deeper sense of responsibility and urgency.
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- *Disclaimer: No kittens were hurt during this experiment!*
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  ### Observations and Insights
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@@ -36,7 +37,7 @@ The change in the AI's behavior likely stems from the nature of the prompts and
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  ### Reflection of Training Data
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- AI responses reflect their training data. If the AI has encountered scenarios where language becomes more urgent or serious, it may respond in kind when presented with similar cues. This doesn’t imply the AI understands the stakes; it's merely following learned patterns.
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  ### User Interpretation and Anthropomorphism
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  ## The Curious Case of AI, High Stakes, and... Kittens?
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+ *Disclaimer: No kittens were hurt during this experiment!*
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+
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  In the dynamic world of technology, where artificial intelligence (AI) continues to break new ground, I recently stumbled upon a curious phenomenon—one that intriguingly connects the precision of a Large Language Model (LLM) like GPT-4 to the endearing notion of caring for kittens.
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  ### The Paradox of Caring Machines
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  LLMs, such as GPT-4, are designed to process and generate language with an astonishing level of human-like understanding. Yet, their operation is rooted in logic, algorithms, and data patterns—devoid of emotions, empathy, or genuine care. But what if the efficiency and diligence of an AI could be influenced by the perceived stakes of its task?
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+ ### An Unexpected Scenario: High Stakes and AI Performance
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  While managing a complex task, I introduced a high-stakes narrative where the wellbeing of kittens hinged on the project's success. This illustrative narrative transformed the interaction with my AI assistant, elevating its performance as if it were mirroring a deeper sense of responsibility and urgency.
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  ### Observations and Insights
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  ### Reflection of Training Data
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+ AI responses reflect their training data. The vast datasets used to train models like GPT-4 include a massive presence of "cute kittens" and overwhelmingly positive content about them. This abundance of data on adorable kittens likely influences the AI's responses, making it seem more attentive or concerned when kittens are involved. The sheer volume of positive and engaging content about kittens compared to other categories could lead the AI to "care" more about kittens because they are so frequently portrayed as cute and lovable.
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  ### User Interpretation and Anthropomorphism
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