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might sound like a risk, human understanding comes with its own limits; engineering
design is littered with what appeared to be good insights that have had bad consequences.
Declarative design rests on all the advances in AI, plus the improving fidelity of
simulations to virtually test designs.

The mother of all design problems is the one that resulted in us. The way we’re
designed resides in one of the oldest and most conserved parts of the genome, called the
Hox genes. These are genes that regulate genes, in what are called developmental
programs. Nothing in your genome stores the design of your body; your genome stores,
rather, a series of steps to follow that results in your body. This is an exact parallel to
how search is done in AI. There are too many possible body plans to search over, and
most modifications would be either inconsequential or fatal. The Hox genes are a
representation of a productive place for evolutionary search. It’s a kind of natural
intelligence at the molecular level.

AI has a mind-body problem, in that it has no body. Most work on AI is done in
the cloud, running on virtual machines in computer centers where data are funneled. Our
own intelligence is the result of a search algorithm (evolution) that was able to change
our physical form as well as our programming—those are inextricably linked. If the
history of AI can be understood as the working of scaling laws rather than a succession of
fashions, then its future can be seen in the same way. What’s now being digitized, after
communication and computation, is fabrication, bringing 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 discrete set of parts
reversibly joined with a discrete set of relative positions and orientations. These
attributes allow the global geometry to be determined from local constraints, assembly
errors to be detected and corrected, heterogeneous materials to be joined, and structures
to be disassembled rather than disposed of when they’re no longer needed. The amino
acids that are the foundation of life and the Lego bricks that are the foundation of play
share these properties.

What’s interesting about amino acids is that they’re not interesting. They have
attributes that are typical but not unusual, such as attracting or repelling water. But just
twenty types of them are enough to make you. In the same way, twenty or so types of
digital-material part types—conducting, insulating, rigid, flexible, magnetic, etc.—are
enough to assemble the range of functions that go into making modern technologies like
robots and computers.

The connection between computation and fabrication was foreshadowed by the
very pioneers whose work the edifice of computing is based on. Wiener hinted at this by
linking material transportation with message transportation. John von Neumann is
credited with modern computer architecture, something he actually wrote very little
about; the final thing he studied, and wrote about beautifully and at length, was self-
reproducing systems. As an abstraction of life, he modeled a machine that can
communicate a computation that constructs itself. And the final thing Alan Turing, who
is credited with the theoretical framework for computer science, studied was how the
instructions in genes can give rise to physical forms. These questions address a topic
absent from a typical computer-science education: the physical configuration of a

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