Smarter Optimization, Less Math — One Solve Per Step

Imagine Newton's Method as a chef tasting their dish repeatedly; this new approach seasons more efficiently without sacrificing flavor, using only one careful taste test per iteration instead of three.

This means optimization problems that power machine learning and engineering could run faster without tradeoffs — saving time and computing power on problems that already consume resources at scale.