Sublime

how to write algorithms that could change their code and get smarter as they develop. We now call this evolutionary programming.

not vary.

Perhaps the greatest “phase transition” in our thinking that such an approach could engender is the maturation in our willingness to live with relatively high levels of uncertainty in the domains of complex phenomena—and thus give up on ideas like complete “cures,” the elimination of “risk,” the design of perfect “stability,” and achieving total

publicly visible.