By Chuppala Nagesh Bhushan Silicon can already out-calculate humanity. Whether it can out-think Newton is a different question entirely In the summer of 1665, with plague stalking London, a 23-year-old Isaac Newton retreated to his mother's farm in Lincolnshire and, by his own later account, invented a new branch of mathematics more or less out of boredom and ambition. He wanted to know how planets moved, how a falling apple related to an orbiting moon, how change itself could be measured. Calculus was the result: arguably humanity's most consequential intellectual export, the mathematics underneath rocket trajectories, economic models and the machine-learning systems that now threaten to make Newton's achievement look almost pedestrian by comparison. Three and a half centuries later, a rather different kind of mind is trying its hand at mathematics. Large Language Models can already prove theorems, some of them previously unsolved. DeepMind's AlphaProof reached silve...
For most people, the word "calculus" triggers a kind of academic vertigo. It marks the spot where the intuitive world of numbers hardens into a thicket of dry, mechanical symbols — a gatekeeper meant to be endured rather than a window meant to be looked through. We remember it as a series of hurdles. Steven Strogatz, a professor of applied mathematics at Cornell, remembers it as an epic. Strogatz is what you might call a mathematics mensch . Despite his world-class credentials, he still describes himself as the "weakest math major" of his Princeton years, watching classmates solve problems at a speed he couldn't match. That humility is what makes him such an effective translator of the subject. Whether he's walking the hills of Ithaca dictating chapters to his dog, Murray, or trading ideas on the Into the Impossible podcast, Strogatz treats mathematics as a matter of human history and feeling, not formula. For him, calculus isn't a textbook subject. I...