Unlocking AI Potential: A New Perspective on Skills and Systems
In a thought-provoking case study, Ernaud Breissie examines the capabilities of modern Large Language Models (LLMs), including Gemini and DeepSeek. A pivotal inquiry highlights how these systems grapple with complex decision-making scenarios:
- The Dilemma: Choosing between becoming an excellent musician or coder.
- The Flaw: LLMs treat music and coding as disjoint skills, missing deeper connections.
Key Insights:
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Silo Logic Failures:
- AI compares labels instead of exploring how coding can encapsulate musical creation.
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User-Driven Analysis:
- Coding isn’t just an alternative; it’s a meta-skill that empowers musical creation through tools like Sonic Pi and SuperCollider.
Conclusion:
Leading models, while powerful, lack a systemic awareness crucial for advancing beyond binary choices. The next frontier is enhancing AI’s ability to identify interdependencies, optimize functional reach, and redefine what it means to be skilled.
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