The Nature of Intelligence and the Universe

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Students have been known to ask the question, malady “Why should I study Computer Science?” One reply correctly advises that there are fascinating and lucrative careers in Computer Science. A second reply is that Computer Science helps us understand the nature of intelligence and the universe! Bertrand Russell reminded us that we do not have personal experience with creation or annihilation. Before we can begin to understand the nature of the universe, illness we must first understand the tools that we use to cialis bathtub understand the universe so that we might distinguish the effects of those tools against subjects that we analyze with those tools. We must understand the effects of the tools on the objects of analysis just as we must understand that the very act of observing the movement of an electron impacts buy cialis generic the movement itself. Results of observation themselves become part of what we observe. We use intelligence to study and think about and model and make sense of the universe, but the very nature of the artefacts of intelligence shape and distort our understanding of the universe. Thus it behoves us understand the nature of understanding so that we might better tease the nature of understanding itself from that which we seek to understand. Broadly speaking, there are two models of intelligence that we can study. One is the product of 500+ years of biological evolution. For lack of a more familiar term, we use the inaccurate phrase “natural intelligence” as we currently find it in our biosphere, perhaps most famously associated with the human brain. The other model, known by an equally inaccurate term, is the phrase “artificial intelligence”, currently manifested by things that we call “computers”. It is significant and telling that the adjectives “natural” and “artificial” are value laden by the arrogance of a species that finds itself reluctant to imagine that another entity could be more “intelligent” than itself, although by any and every measure this prospect seems virtually inevitable. Everything that our species is, knows and does is a derivative of “nature” and is thus “natural”, including all “man made” artefacts, be they moon busting rockets or silicon wafered circuitry because, notwithstanding the shame and queasiness inspired by such thoughts, our species is the result of, not independent of, processes that are as “natural” as rivers flowing cheap cialis and stars exploding. We too are products of 500 million years of evolution. The flip side of this lexiconial coin is that the toys and tools of civilization are no more “artificial” than twigs used by crows to fish grubs from cracks or rocks used by otters to crack open crustaceans. It is becoming evident that the twenty-first century belongs to two disciplines that study models of intelligence. Brain science is finally teasing the morphology and process of intelligence as it has evolved from eons of random mutation and environmental selection. Computer science continues to engineer the inculcation of algorithms by architectural design (mutation) and design motivated by human vanity and fashion and pecuniary pursuit. Do not be misled by the institutional trappings of these historical arrangements. The investigation of both models focuses upon the holy grail of academia – the nature of intelligence itself. The architectures of wetware and hardware differ significantly, but motivations to identify algorithms of adaptive design are the same. Paradigms and heuristics of these models differ significantly at operational levels of implementation, but ultimately the objectives of reaction and adaptation to environmental variation flow and ebb together. Understanding intelligence itself is the prize. As the twentieth century came to a close, we found ourselves disappointed by the failure of AI (“artificial intelligence”) to proceed as rapidly as early students of Turing might have predicted. Meanwhile we found ourselves equally disappointed by the failures of the psycho babble of cognitive science to identify empirical referents for so many Platonic shadows, and for neuroscientists to identify anatomical structures corresponding to so many pathological behaviours documented by health professionals. Now, in the first decade of the twenty-first century, it appears that parallel progress in the twin disciplines that study these two apparently disparate models of intelligence is changing rapidly, indeed, with empirical observations that are beginning to finally point to the correct questions to ask. Indeed, that has been the major obstacle to progress in the understanding of the nature of intelligence. We may not have canadian pharmacy online even been asking the right questions. If we ask how high the building is, we will not learn what the CEO had for lunch. If we study the colour of our children’s eyes, we will not learn how far they can throw a baseball. If we follow Alice down holes of distracting attention displacement, we will never get to the other end. Brain science has made more progress in the past five years than in its entire prior history. At last we are beginning to map external behaviours to morphological structures. For some time we have known that specific parts of the cortex correspond to specific parts of our body. We have known what part of the brain connects to the thumb and forearm. Five hundred million years of evolution has designed a wiring diagram manifested by our brains. Our brains are genetically pre-wired, but we now know that our brains are exceedingly plastic and that the brains “wiring” is modified and sometimes even over-hauled by life experiences. Amazingly, the frontier of brain research is now asking very “simple”, empirical questions that may be studied and documented, verified and peer-reviewed! We now want to identify the algorithms, or “computer code” that the brain uses to demonstrate skill movement. We know that the brain can “learn” to direct muscles to contract to shoot a basketball through a hoop! We know that the brain sends electro-biochemical impulses through the spinal chord to muscles. We now know that the brain also simulates skill movements in the brain without sending those impulses. This means that the brain can “practice” shooting basket balls without actually shooting basketballs. A famous urban legend (probably untrue) reports a “visualization” study said to have been conducted by one Dr. Judd Blaslotto at a University of Chicago physical education class. Three groups of basketball players prepared for a contest consisting of twenty free throws. Group A shot 100 free throws a day for 30 days. Group B practiced “normally”. Group C spent 15 minutes every day visualizing shooting perfect free throws. At the end of the month Groups A and C had essentially the same scores of 24% improvement while Group B lost dramatically. ( I was crushed when I failed to find a respectable source for this story because an entire generation of athletes have been motivated by it. Nevertheless, some of the top neuroscientists in the world now believe precisely what the mythical Dr. Blaslotto story suggests. My favourite talking head television program, “Charlie Rose”, just broadcast (23 December 2009) the third episode in a remarkable series on the brain. See a summary of the Brain series at: In that episode John Krakauer, Associate Professor of Neurology and Neuroscience at Columbia University, ( ( Not Finished … to be continued later! )


About the Author:

Gerry Donaldson was Calgary’s first high school teacher to use a lab of personal computers. Gerry taught CSE, including CTS, AP and IB Computer Science, for 30 years before teaching and consulting to the Department of Computer Science at the University of Calgary.
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