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Typo: missing apostrophe #23

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -634,7 +634,7 @@ Having covered each constraint individually, we can now put them all into perspe

The hard constraints are **data**, **compute**, and **energy** - these are rate-limited by slow processes - data currently being limited by the scaling growth of the internet and other data collection methods, compute being limited by individual company resources and supply chains, and energy constraints eventually being rate-limited by regulation.

Meanwhile, **parameters**, **optimization & regularization**, **architecture**, and **compute efficiency** can be thought of as forms of **leverage** on the hard constraints - they are all easy to vary and can be optimized to maximize a models intelligence given a fixed set of data, compute, and energy.
Meanwhile, **parameters**, **optimization & regularization**, **architecture**, and **compute efficiency** can be thought of as forms of **leverage** on the hard constraints - they are all easy to vary and can be optimized to maximize a model's intelligence given a fixed set of data, compute, and energy.

**Maximizing leverage constraints are important for individual training runs, but improving the hard constraints is what really pushed forward the increasing base intelligence of models now.**

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