Computing Beyond the Turing-von Neumann Architecture | CCTP ...

Zach Schalk

This week’s readings and projects provided an interesting change of pace.  While touching on many abstract and theoretical concepts of computation, I felt like it was much easier to engage with and digest these topics without drowning in a new flood of vocabulary, metaphors and theories.  Also helpful is the fact that I’m currently working my way through my first ever programming class, Professor Evan Barba’s Tangible and Embodied Computing.  Let’s just say that the exasperated quotes from Princeton engineers working on the Maniac in Poundstone’s review of Turing’s Cathedral hit pretty close to home.

While I’m only a month into the course (I’ve also worked through some of the Codecademy course on javascript in the past, and now I’ve dipped my toe into Python as well), I feel like I’ve learned a great deal about computer programming (Lesson number one: sometimes the best course of action is to take a deep breath and step away from your program when you get stuck–the alternative might be a bit more destructive).  One thing we haven’t discussed in Professor Barba’s class, however, is computer architecture and the processes that allow our programs to work.  For that reason I was very interested in the readings seeking to illuminate these concepts, as well as the thinkers and engineers who brought them to life.  I had no idea that the basic architecture of the Turing-von Neumann model of computation remains at the foundation of most computing devices we interact with to this day–despite all the advances that have shaped the digital age in which we’ve grown up.  This startling (at least to me) fact is a true testament to the genius of modern computing’s forefathers such as Turing, von Neumann and Shannon.  It also begs the question of what, if anything, comes next.

I have long been interested in emerging computing technologies.  While I generally lack a rigorous understanding of these technologies beyond the explanations available in the popular press (trying to fix this was one of the reasons I first became interested in CCT!), a compelling case can be made that these emerging technologies have interesting and far-ranging implications for the manner in which humans will make use of computers in the future.  In his introduction to The Pattern on the Stone, Hillis makes a passing reference to a new conception of computer design and programming that breaks down the current reliance on top-down hierarchy and instead relies on an “evolutionary” model that builds on its own accumulation of processes.  He also mentions other experimental forms of computing such as quantum computers and those that attempt to more accurately mimic the neural pathways of the human brain.  These are very exciting concepts that, more than a decade after Hillis published his book, are finally starting to show up in the market.  Cognitive computing (as Prof. Irvine points out in his introduction to computation) made a splashy debut with IBM’s Watson–though that was just the first of IBM’s attempts.  Facebook recently created a new group working to apply the artificial intelligence concept of deep learning–simulating neural networks to process data–to their product in order to better manage the flood of unorganized data it collects daily, joining other tech giants such as Google and Microsoft in pushing the limits of machine learning.  And, to much fanfare, the Canadian company D-Wave has produced and sold the first commercially available quantum computers (though, as the linked article explains, there are many skeptics who believe the device is neither really quantum nor faster than a traditional machine).

What are the implications of these types of computational advances?  It depends on who you ask.  Can the advances in artificial neural networks help us link and organize the ever growing sea of unstructured data on computer networks, or find meaning in the ever increasing flow of data being collected by private companies and governments around the world?  Will quantum computers shatter our existing encryption paradigm with their ability to factor large numbers?  Will these new computers enable the creation of rich and immersive virtual worlds and new standards of human-computer interface?  Is the singularity near? Possibly most relevant for this class, might this new era of computational architecture allow the computer to grow into more than just a “remixing machine” of previous mediums and create something entirely new?  These are big and scary questions with implications that I can’t even imagine and I have no idea what the answers will be.  But, for me at least, it’s fun to ask.

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