-AI models are transforming from narrow, specialized tools into increasingly general-purpose systems that can handle complex tasks. Empirical trends show that scaling up - using more data, compute, and parameters - is leading to steady gains in both performance and generality. Rather than viewing AI progress through simple thresholds like "narrow" versus "general" intelligence, we introduce frameworks for measuring capabilities along continuous dimensions. The chapter covers things like definitions of capabilities, scaling patterns, performance trends, and forecasting methods. Understanding these concepts shapes how we think about potential risks, safety measures, and governance approaches throughout the rest of the book.
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