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Software's Evolution: From Code to AI Operating Systems
Source: https://www.youtube.com/watch?v=LCEmiRjPEtQ
Andrej Karpathy's presentation explores the evolving landscape of software development, introducing the concepts of Software 1.0 (traditional code), Software 2.0 (neural network weights), and the emerging Software 3.0 (Large Language Models or LLMs programmed via natural language prompts).
He analogizes LLMs to new operating systems or utilities, emphasizing their unique characteristics, such as human-like psychology with both superhuman capabilities and cognitive deficits like hallucination and memory limitations. Karpathy discusses the opportunities for building "partial autonomy apps" that allow humans to verify AI-generated work efficiently, and he highlights the revolutionary aspect of natural language programming enabling wider participation in software creation.
Finally, he proposes adapting existing digital infrastructure, including documentation and user interfaces, to be more "agent-friendly" for a future where AI agents play an increasingly significant role.
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By Benjamin Alloul 🗪 🅽🅾🆃🅴🅱🅾🅾🅺🅻🅼Source: https://www.youtube.com/watch?v=LCEmiRjPEtQ
Andrej Karpathy's presentation explores the evolving landscape of software development, introducing the concepts of Software 1.0 (traditional code), Software 2.0 (neural network weights), and the emerging Software 3.0 (Large Language Models or LLMs programmed via natural language prompts).
He analogizes LLMs to new operating systems or utilities, emphasizing their unique characteristics, such as human-like psychology with both superhuman capabilities and cognitive deficits like hallucination and memory limitations. Karpathy discusses the opportunities for building "partial autonomy apps" that allow humans to verify AI-generated work efficiently, and he highlights the revolutionary aspect of natural language programming enabling wider participation in software creation.
Finally, he proposes adapting existing digital infrastructure, including documentation and user interfaces, to be more "agent-friendly" for a future where AI agents play an increasingly significant role.