Research
153d agoScaling Laws Predict Downstream Performance
Apple’s new study shows that a simple power‑law model can predict how language‑model accuracy scales with training budget, offering a more reliable alternative to two‑stage proxies.
The Signal
By linking token‑to‑parameter ratios directly to downstream benchmarks, the research provides a universal scaling framework that could streamline AI development worldwide, reducing costly trial‑and‑error cycles.