4
theoretical limits on the information processing attainable in a given lump of
matter. We can with much greater confidence establish lower bounds on
posthuman computation, by assuming only mechani sms that are already
understood.Forexample,EricDrexlerhasoutlinedadesignforasystemthesize
of a sugar cube
(excluding cooling and power supply) that would perform 10
21
instructionspersecond.
3
Anotherauthorgivesaroughestimateof10
42
operations
per second for a computerwitha mass on order of alarge planet.
4
(If wecould
createquantumcompu ters,orlearntobuildcomputersoutofnuclearmatteror
plasma, we could push closer to the theoretical limits. Seth Lloyd calculates an
upperboundfora1kg computerof5*10
50
logi cal operations persecondcarried
out on ~10
31
bits.
5
However, it suffices for our purposes to use the more
conservativeestimatethatpresupposesonlycurrentlyknowndesign‐principles.)
The amount of computing power needed to emulate a human mind can
likewise be roughly estimated. One estimate, based on how computationally
expensive it is to replicate the functionality of a
piece of nervous tissuethatwe
have already understood and whose functionality has been replicated in silico,
contrastenhancementintheretina,yieldsafigureof~10
14
operationspersecond
for the entire human brain.
6
An alternative estimate, based the number of
synapses in the brain and their firing frequency, gives a figure of ~10
16
‐10
17
operationspersecond.
7
Conceivably,evenmorecouldberequiredifwewantto
simulate in detail the internal workings of synapses and dendritic trees.
However,itislikelythatthehumancentralnervoussystemhasahighdegreeof
redundancy on the mircoscale to compensate forthe unreliability and noisiness
ofits neuronal
components.Onewouldtherefore expect a substantialefficiency
gainwhenusingmorereliableandversatilenon‐biologicalprocessors.
Memory seems to be a no more stringent constraint than processing
power.
8
Moreover,sincethemaximumhumansensorybandwidthis~10
8
bitsper
second, simulating all sensory events incurs a negligible cost compared to
simulating the cortical activity. We can therefore use the processing power
of Information Processing Superobjects: The Daily Life among the Jupiter Brains.” Journal of
EvolutionandTechnology,vol.5(1999)).
3
K. E. Drexler, Nanosystems: Molecular Machinery, Manufacturing, and Computation, New York,
JohnWiley&Sons,Inc.,1992.
4
R. J. Bradbury, “Matrioshka Brains.” Working manuscript (2002),
http://www.aeiveos.com/~bradbury/MatrioshkaBrains/MatrioshkaBrains.html.
5
S.Lloyd,“Ultimatephysicallimitstocomputation.”Nature406(31August):1047‐1054(2000).
6
H.Moravec,MindChildren,HarvardUniversityPress(1989).
7
Bostrom(1998),op.cit.
8
Seereferencesinforegoingfootnotes.