Emergent abilities, or a mirage of the ruler? How exact-match manufactures a cliff from a smooth skill
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Scaling laws say a model's loss falls as a smooth, forecastable power law. But downstream skills can behave differently: on many tasks a model scores essentially 0% across a huge range of sizes, then — past some threshold — accuracy leaps. That's an "emergent ability" (Wei et al. 2022), and it's unsettling, because you can't read the jump off the smooth loss curve. Then came the counter-argument (Schaeffer et al. 2023, "Are Emergent Abilities a Mirage?" ): much of that sudden jump is an…
1Key Takeaways
- Scaling laws say a model's loss falls as a smooth, forecastable power law.
- But downstream skills can behave differently: on many tasks a model scores essentially 0% across a huge range of sizes, then — past some threshold — accuracy leaps.
- That's an "emergent ability" (Wei et al.
- 2022), and it's unsettling, because you can't read the jump off the smooth loss curve.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that scaling laws say a model's loss falls as a smooth, forecastable power law.
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