Epstein Secrets

rate of knowledge accumulation. John von Neumann also has a cameo in Zhe Human Use of Human Beings, for game theory. What Wiener missed here was von Neumann’s seminal role in digitizing computation. Whereas analog communication degraded with distance, analog computing (like the Differential Analyzer) degr

inging the programmability of bits to the world of atoms. By digitizing not just designs but the construction of materials, the same lessons that von Neumann and Shannon taught us apply to exponentially increasing fabricational complexity. I’ve defined digital materials to be those constructed from a disc

ow it an abstract painting and see what it says. But it does a pretty good job. It works using the same neural-network technology that McCulloch and Pitts imagined in 1943 and lots of us worked on in the early eighties. Back in the 1980s, people successfully did OCR—optical character recognition. They t

rate of knowledge accumulation. John von Neumann also has a cameo in Zhe Human Use of Human Beings, for game theory. What Wiener missed here was von Neumann’s seminal role in digitizing computation. Whereas analog communication degraded with distance, analog computing (like the Differential Analyzer) degr

inging the programmability of bits to the world of atoms. By digitizing not just designs but the construction of materials, the same lessons that von Neumann and Shannon taught us apply to exponentially increasing fabricational complexity. I’ve defined digital materials to be those constructed from a disc

ow it an abstract painting and see what it says. But it does a pretty good job. It works using the same neural-network technology that McCulloch and Pitts imagined in 1943 and lots of us worked on in the early eighties. Back in the 1980s, people successfully did OCR—optical character recognition. They t

r machine, now known as a Universal Turing Machine, an arbitrary set of computing instructions could be encoded on that same tape. In the 1940s, von Neumann developed an abstract self-reproducing machine called a cellular automaton. In this case it occupied a finite subset of an infinite two- dimensional

nces are intimately bound up in the idea of an impending technological singularity. His work on neuroscience and his initial support of McCulloch and Pitts adumbrated the startlingly effective deep-learning methods of the present day. Over the past decade, and particularly in the last five years, such de

r machine, now known as a Universal Turing Machine, an arbitrary set of computing instructions could be encoded on that same tape. In the 1940s, von Neumann developed an abstract self-reproducing machine called a cellular automaton. In this case it occupied a finite subset of an infinite two- dimensional

nces are intimately bound up in the idea of an impending technological singularity. His work on neuroscience and his initial support of McCulloch and Pitts adumbrated the startlingly effective deep-learning methods of the present day. Over the past decade, and particularly in the last five years, such de