Mind, Body, World- Foundations of Cognitive Science, 2013a

a word in memory to be accessed in parallel, though operations on this retrieved
information were still conducted in serial.
To get a word from the memory in this scheme requires, then, one switching mechanism
to which all 40 tubes are connected in parallel. Such a switching scheme
seems to us to be simpler than the technique needed in the serial system and is, of
course, 40 times faster. We accordingly adopt the parallel procedure and thus are
led to consider a so-called parallel machine, as contrasted with the serial principles
being considered for the EDVAC. (Burks, Goldstine & von Neumann, 1989, p. 44)
Interestingly, the extreme serial design in EDVAC resurfaced in the pocket calculators
of the 1970s, permitting them to be simple and small (Ceruzzi, 1997).
The brief historical review provided above indicates that while some of the early
computing devices were serial processors, many others relied upon a certain degree
of parallel processing. The same is true of some prototypical architectures proposed
by classical cognitive science. For example, production systems (Newell, 1973, 1990;
Newell & Simon, 1972) are serial in the sense that only one production manipulates
working memory at a time. However, all of the productions in such a system scan
the working memory in parallel when determining whether the condition that
launches their action is present.
An alternative approach to making the case that the serial processing is not a
mark of the classical is to note that serial processing also appears in non-classical
architectures. The serial versus parallel distinction is typically argued to be one of
the key differences between connectionist and classical theories. For instance, parallel
processing is required to explain how the brain is capable of performing complex
calculations in spite of the slowness of neurons in comparison to electronic
components (Feldman & Ballard, 1982; McClelland, Rumelhart, & Hinton, 1986;
von Neumann, 1958). In comparing brains to digital computers, von Neumann
(1958, p. 50) noted that “the natural componentry favors automata with more, but
slower, organs, while the artificial one favors the reverse arrangement of fewer, but
faster organs.”
It is certainly the case that connectionist architectures have a high degree of parallelism.
For instance, all of the processing units in the same layer of a multilayered
perceptron are presumed to operate simultaneously. Nevertheless, even prototypical
parallel distributed processing models reveal the presence of serial processing.
One reason that the distributed memory or the standard pattern associator
requires external, central control (Dawson & Schopflocher, 1992a) is because this
kind of model is not capable of simultaneous learning and recalling. This is because
one of its banks of processors is used as a set of input units during learning, but is
used completely differently, as output units, during recall. External control is used
to determine how these units are employed and therefore determines whether the
machine is learning or recalling. External control also imposes seriality in the sense
Marks of the Classical? 337