09 December 2020

On Machines XI (Mind vs Machine III)

"A machine is a machine because it cannot think." (Gilbert K Chesterton, 1916)

"Thanks to the psycho-physical reversibility, we can materialize the act of creation. Undoubtedly, the inventive machine has not yet been created, but we can see its creation soon." (Stefan Odobleja, "Consonant Psychology", 1938)

"The act of discovery escapes logical analysis; there are no logical rules in terms of which a 'discovery machine' could be constructed that would take over the creative function of the genius. But it is not the logician’s task to account for scientific discoveries; all he can do is to analyze the relation between given facts and a theory presented to him with the claim that it explains these facts. In other words, logic is concerned with the context of justification." (Hans Reichenbach, "The Rise of Scientific Philosophy", 1951)

"He’s fed in enough data for a dozen forecasts - let the electronic brains do the rest. While the THINK machines grind out prophecies, he can relax and contemplate the cosmos." (Lydia Strong, "Sales Forecasting: Problems and Prospects", 1956)

"[...] the machine will still not be an adequate model of the mind. We are trying to produce a model of the mind which is mechanical which is essentially 'dead' but the mind being in fact 'alive', can always go one step better than any formal, ossified dead system can. [...] the mind always has the last word." (J R Lucas, "Minds and Machines", 1964)

"These machines have no common sense; they have not yet learned to 'think', and they do exactly as they are told, no more and no less. This fact is the hardest concept to grasp when one first tries to use a computer." (Donald Knuth, "The Art of Computer Programming, Volume 1: Fundamental Algorithms", 1968)

"Questions are the engines of intellect, the cerebral machines which convert energy to motion, and curiosity to controlled inquiry." (David H Fischer, "Historians’ Fallacies", 1970)

"The digital-computer field defined computers as machines that manipulated numbers. The great thing was, adherents said, that everything could be encoded into numbers, even instructions. In contrast, scientists in AI [artificial intelligence] saw computers as machines that manipulated symbols. The great thing was, they said, that everything could be encoded into symbols, even numbers." (Allen Newell, "Intellectual Issues in the History of Artificial Intelligence", 1983) 

"Fuzziness, then, is a concomitant of complexity. This implies that as the complexity of a task, or of a system for performing that task, exceeds a certain threshold, the system must necessarily become fuzzy in nature. Thus, with the rapid increase in the complexity of the information processing tasks which the computers are called upon to perform, we are reaching a point where computers will have to be designed for processing of information in fuzzy form. In fact, it is the capability to manipulate fuzzy concepts that distinguishes human intelligence from the machine intelligence of current generation computers. Without such capability we cannot build machines that can summarize written text, translate well from one natural language to another, or perform many other tasks that humans can do with ease because of their ability to manipulate fuzzy concepts." (Lotfi A Zadeh, "The Birth and Evolution of Fuzzy Logic", 1989)

"Machine consciousness refers to attempts by those who design and analyse informational machines to apply their methods to various ways of understanding consciousness and to examine the possible role of consciousness in informational machines." (Igor Aleksander, "Machine Consciousness", 2008)

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