Why AI Adoption Is Moving More Slowly

AI Copium17:43
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    Video summary

    Sam Altman says he expected GPT-4 to disrupt software and business much faster than it did. The missing factor was economic inertia: people keep buying familiar products, using established tools and defining productive work through habits that persist even when a better technical option is available.

    Sam Altman uses his own limited adoption of Codex as an example. Although an agent could handle email, task lists and routine computer work, moving between familiar interfaces still feels like work. He argues that AI products have not yet made the new workflow seamless enough to overcome those ingrained behaviors.

    The video separates slow social adoption from rapid capability growth. Sam Altman expects safety decisions to become harder as models surpass the smartest people, and points to cases where OpenAI paused some work to strengthen cybersecurity controls before continuing development.

    Sam Altman also acknowledges that the AI industry damaged public trust by warning about catastrophic risks and job losses while racing ahead. His proposed product direction is a persistent, context-aware interface and an API that make intelligence broadly useful without requiring OpenAI to build every downstream product.

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