Equation 6 · Model Systems in 2035: Four Scenarios, Their Signals, and What Would Falsify Them
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subscript
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with and the annual growth factors. When > , grows without bound, and the batch size required to keep the arithmetic units busy grows with it. Autoregressive decoding sits on the wrong side of this: generating one token requires streaming the weights and the accumulated key–value cache, so decode time is bounded below by
Sources cited in the article section
- [6] Compute Trends Across Three Eras of Machine Learning ↗
- [2] Key Trends and Figures in Machine Learning ↗
- [3] Scaling Laws for Neural Language Models ↗
- [4] Training Compute-Optimal Large Language Models ↗
- [5] Will We Run Out of Data? Limits of LLM Scaling Based on Human-Generated Data ↗
These citations give research context. Read each source to check which claims it supports.
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