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🧠 Three Generations of Software: Karpathy introduces Software 1.0 (code written by humans), 2.0 (neural network weights), and 3.0 (prompts for LLMs). Software is now written in natural language, allowing for broader access and faster iteration.
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🚗 Neural Nets Replacing Code: Using Tesla’s Autopilot as an example, he shows how neural nets gradually replaced traditional code, signifying a profound industry transition.
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🧮 LLMs as Utilities and OSs: LLMs are described as akin to utilities (like electricity) due to centralized access, but function like operating systems, orchestrating memory and tools for problem-solving.
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👩💻 Rise of Partially Autonomous Apps: Tools like Cursor and Perplexity represent early successes in partial autonomy, where users can control how much power the AI takes over, using “autonomy sliders.”
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🎨 Importance of GUI & Fast Loops: Emphasizes how graphical interfaces speed up human-AI collaboration, making AI outputs easier to audit, especially important given LLMs' fallibility.
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📚 LLMs and Human-Like Psychology: LLMs are likened to "people spirits"—they're encyclopedic yet gullible, show jagged intelligence, and lack long-term memory, needing thoughtful handling.
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🛠️ Building for Agents: Advocates for reengineering digital infrastructure to be more accessible to LLMs—e.g., using markdown over HTML, designing docs for agents, and anticipating direct interaction with AI.
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🔧 From Vibe Coding to Infrastructure: Personal anecdotes about “vibe coding”—building apps quickly with LLM help—and the realization that deployment/devops, not code, is the bottleneck.
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🦾 Iron Man Suit Analogy: Encourages building augmentative, not autonomous agents—human-in-the-loop systems with flexible autonomy, aligning with real-world complexity and safety.
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🚀 Call to Action for New Developers: Ends with optimism, calling new industry entrants to help build the next wave of computing, driven by AI and partial autonomy.
- 70 years: Traditional programming remained mostly unchanged until recently—indicates the depth of transformation AI introduces.
- 2013–2025: Over a decade since Karpathy’s first self-driving experience, yet autonomy is still not “solved”—showing AI's complexity and the need for human oversight.
- Three paradigms (1.0, 2.0, 3.0): Highlights a radical shift in how software is written, from explicit code to data-driven models to language-prompted agents.