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Of Brains and Computers (Paperback)
Loot Price: R2,363
Discovery Miles 23 630
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Of Brains and Computers (Paperback)
Series: Foundations and Trends (R) in Integrated Circuits and Systems
Expected to ship within 10 - 15 working days
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The human brain, which is considered to be the prototypal
biological computer, in its current incarnation is the result of
more than a billion years of evolution. Its main functions have
always been to regulate the internal milieu and to help the
organism/being to survive and reproduce. With growing complexity,
the brain has adopted a number of design principles that serve to
maximize its efficiency in performing a broad range of tasks. The
physical computer, on the other hand, has had only 200 years or so
to evolve, and its perceived purpose is considerably different and
far more constrained - that is, to solve a set of mathematical
functions. This picture is rapidly changing however. One may argue
that the functions of brains and computers are converging. This
transition comes at a critical time when the roadmap for physical
computing is becoming murky after a long period of exponential
growth. Hence the existential questions arise if the underlying
design principles may converge or cross-breed, or if the different
mechanisms (physics versus biology) will always translate into
radically different solutions. Neuromorphic systems are just one
possible form of cross-fertilization between biological and
physical computing. Other neural concepts at different levels of
abstraction can help inspire us to rethink how to efficiently
perform a number of meaningful tasks and functions. This leads to
the topic of this monograph. This monograph reviews some of the
insights arising from both computational neuroscience and computer
engineering, and evaluates how these could combine to help us build
a next generation of "computing" systems. To create insights and
identify opportunities, this monograph firstly puts neural and
physical computing face-to-face, and compares how they arose, how
they differ right now with respect to a number of metrics such as
computational and power density, and how these metrics may change
over the future decades. A similar analysis is performed at the
architectural/computational model level. While doing so, ground
truths in terms of obtainable performance, bandwidth and
power/energy efficiency are established. Thereafter, a number of
neural design principles that may translate into design guidelines
for future computers are identified. On close examination of these
and other observations, it becomes apparent that
cross-fertilization between the domains is already happening at
multiple levels, albeit in an incremental way. The publication
completes with perspectives on where brain-inspired computing may
lead us, some speculative bets, and a number of forward-looking
reflections.
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