"The thing that got me started on the science that I've been building now for about 20 years or so was the question of okay, if mathematical equations can't make progress in understanding complex phenomena in the natural world, how might we make progress?"
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Restlessness is the engine here: a scientist admitting that the standard toolkit stalled out, and deciding that stalling is a clue, not a verdict. Wolfram frames “mathematical equations” not as eternal truth machines but as a historically successful interface that may simply be mismatched to certain kinds of complexity. That’s a provocative inversion of scientific piety. Instead of asking, “What equation governs this?” he asks, “What kind of representation would let us see progress at all?”
The intent is partly autobiographical myth-making - a origin story for two decades of work - but it’s also a quiet manifesto. By casting the problem as “complex phenomena in the natural world,” he’s gesturing at the messy zones where classical math feels elegant and insufficient: turbulence, biological morphogenesis, computational irreducibility, emergent behavior. The subtext: if nature is doing something that looks like computation, then our best description might be computational too. Equations give way to rules, algorithms, simulations, enumerations of possible behaviors. “Make progress” becomes a pragmatic metric: prediction, compression, generative models, not closed-form solutions.
Context matters because Wolfram’s career has long been a referendum on this wager. From cellular automata to “A New Kind of Science,” he’s argued that simple programs can yield the complexity we see, and that the bottleneck is our insistence on equation-first thinking. The quote works because it’s not anti-math; it’s pro-epistemic humility with an entrepreneur’s confidence: when the old language fails, invent a new one and call it science.
The intent is partly autobiographical myth-making - a origin story for two decades of work - but it’s also a quiet manifesto. By casting the problem as “complex phenomena in the natural world,” he’s gesturing at the messy zones where classical math feels elegant and insufficient: turbulence, biological morphogenesis, computational irreducibility, emergent behavior. The subtext: if nature is doing something that looks like computation, then our best description might be computational too. Equations give way to rules, algorithms, simulations, enumerations of possible behaviors. “Make progress” becomes a pragmatic metric: prediction, compression, generative models, not closed-form solutions.
Context matters because Wolfram’s career has long been a referendum on this wager. From cellular automata to “A New Kind of Science,” he’s argued that simple programs can yield the complexity we see, and that the bottleneck is our insistence on equation-first thinking. The quote works because it’s not anti-math; it’s pro-epistemic humility with an entrepreneur’s confidence: when the old language fails, invent a new one and call it science.
Quote Details
| Topic | Science |
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