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Sabtu, 12 Agustus 2017

Prodigies and idiot savants Wonders of human intelligence



Sergei Karjakin -The youngest Grand Master 

Comedy screen writer Andrew Marshall wrote in TIME magazine: “When he was nearly three years old, Nguyen Ngoc Truong Son would watch his mother and father playing chess in the family's ramshackle home in the Mekong Delta, and, like any toddler, pester them to let him play, too. Eventually they relented, assuming the pieces would soon wind up strewn around the kitchen, a plastic bishop stuffed into a teapot. To his parents' astonishment, Son did not treat the chess set as a plaything. He not only knew how to set up the board, which was crudely fashioned with a piece of plywood and a felt-tipped pen. He had, by careful observation, learned many of the complex rules of the game. Within a month, he was defeating his parents with ease. By age 4, Son was competing in national tournaments against kids many years older. By age 7, he was winning them. Now 12, he is Vietnam's youngest champion and a grand master in the making.” ("Small Wonders": TIME Monday, Feb. 17, 2003)
Nguyen Ngoc Truong Son is, no doubt a child prodigy. In the game of chess the youngest grandmaster is Sergei Karjakin of Ukraine. The standard definition of a prodigy is a child who by age 10 displays a mastery of a field usually undertaken only by adults. Prodigies are, by this definition, extraordinary ones whose standout accomplishments are obvious. Ellen Winner, a psychologist in Boston and author of Gifted Children: Myths and Realities says: "I always say to parents, 'If you have to ask whether your child is a prodigy, then your child isn't one.'"
Brains of prodigies
American psychologist Michael O'Boyle in Melbourne has been scanning the brains of young people gifted in mathematics. O'Boyle found that, compared with average kids, children with an aptitude for numbers show six to seven times more metabolic activity in the right side of their brains, an area known to mediate pattern recognition and spatial awareness—key abilities for mathematics and music. Scans also showed heightened activity in the frontal lobes, believed to play a crucial "executive" role in coordinating thought and improving concentration. This region of the brain is virtually inactive in average children when doing the same tasks.
O'Boyle believes prodigies also can switch very efficiently between the brain's left and right hemispheres, utilizing other mental resources and perhaps even shutting down areas that produce random distractions. In short, while their brains aren't physically different from ordinary children's, prodigies seem to be able to focus better—to muster the mental resources necessary to solve problems and learn. O'Boyle says: "For the longest time, these kids' brains were considered the same as everyone else's; they just did twice as much, twice as fast. It turns out those quantitative explanations don't fit. They're doing something qualitatively different."
Neuro-cognitive basis
What is the neuro-cognitive basis of this extraordinary brilliance? Are prodigies born different, gifted by genetic accident to be mentally more efficient? Or is the management of mental resources something that can be developed? Scientists aren't sure. Studies have shown that raw intelligence, as measured through IQ tests, is highly (though not completely) inheritable. But the connection between high intelligence and prodigious behavior is far from absolute. So-called idiot savants, for example, show unusual mastery of specific skills—they could even be described as prodigies were it not for their overall low intelligence. And many very creative children don't necessarily register high IQs because they don't test well on standardized intelligence tests and examinations, says McCann, the education specialist at Flinders University. Creative kids "are looking for different ways to answer the questions," she says. "They're looking for the trick questions."
Unlimited storage capacity of memory
Mauro Pesenti
In a pioneering study in this issue, neuroscientist Mauro Pesenti and colleagues have now used functional brain imaging to examine the calculating prodigy RĂ¼diger Gamm, and to compare his brain activity with that of normal control subjects as they perform mental arithmetical calculations. Gamm is remarkable in that he is able to calculate 9th powers and 5throots with great accuracy and he can find the quotient of 2 primes to 60 decimal places. The authors found that Gamm’s calculation processes recruited a system of brain areas implicated in episodic memory, including right medial frontal and parahippocampal gyri, whereas those of control subjects did not. They suggest that experts develop a way of exploiting the unlimited storage capacity of long-term memory to maintain task relevant information, such as the sequence of steps and intermediate results needed for complex calculation, whereas the rest of us rely on the very limited span of working memory.
No more idiot-savants
Human Calculator: RĂ¼diger Gamm   
Savant syndrome was first recognized by Dr. J. Langdon Down. He also originated the term Down’s syndrome. In 1887, he coined the term "idiot savant" to describe someone who had "extraordinary memory but with a great defect in reasoning power." Idiot is a person with low intelligence. Savant is derived from the French, savoir, meaning wise. The term idiot-savant is now little used because of its inappropriate connotations, and the term savant syndrome has now been more or less adopted. Another term, autistic savant, is also widely used, but this can be somewhat misleading. Although there is a strong association with autism, it is certainly not the case that all savants are autistic. It is estimated that about 50% of the cases of savant syndrome are from the autistic population, and the other 50% from the population of developmental disabilities and CNS injuries.
Savant talents usually appear spontaneously, without warning. The first encounter with a savant is often very charged. Perhaps because the gift is so extraordinary and so at odds with assumptions about the disability itself, it can sometimes seem as if the talent is being revealed, for the very first time, to a viewer's eyes. 
Although savants often take an immediate interest in their instrument or special skill, their fully-formed talents do not necessarily blossom overnight, contrary to the Hollywood notion of a savant. Musical progress is often non-linear. Some aspects of the talent may emerge before others (such as memory or technical ability); although, when the skills come together, there is a quantum leap in overall ability. Once that happens, savant talents can progress quite rapidly.
Nadia’s drawings
 One of Nadia’s drawings
“Nadia” was an autistic savant artist who, by her sixth year, demonstrated an astonishing ability to draw in what was described as ‘Renaissance-style’ perspective. Nadia was the subject of a widely-quoted 1977 book by British psychologist Lorna Selfe. As Nadia gained communicative speech later in childhood, she apparently lost her artistic talent. Selfe suggested a trade-off between language and artistic skills: that as language skills were refined, special artistic skills waned or disappeared. 
In fact, Nadia's loss of interest in drawing came in a shift in her care environment, and mostly in the wake of her mother's death. It is possible that Nadia simply lost her main source of encouragement, and that her artistic gift withered for a lack of praise and reinforcement. Fortunately, such trade-offs are rare. Savant skills are a very useful ‘conduit toward normalization’ in and of themselves, and when they exist, can be helpful in developing many other skills that allow the savant to communicate with the larger world.
A new explanation
The Indian born American neuroscientist V. S. Ramachandran writes: “Consider the possibility that savants suffer brain damage before or shortly after birth. Is it possible that their brains undergo some form of remapping as seen in phantom limb patients? Does prenatal or neonatal injury lead to unusual rewiring? In savants, one part of the brain may for some obscure reasons receive a greater than average input or some other equivalent impetus to become denser and larger—a huge angular gyrus, for example. What would be the consequence of mathematical ability? Would this produce a child who can generate eight-digit prime numbers? In truth, we know so little about how neurons perform such abstract operations that it’s difficult to predict what the effect of such change might be. An angular gyrus double in size could lead not to a mere doubling of mathematical ability but to a logarithmic or hundred fold increase. You can imagine an explosion of talent resulting form this simple but “anomalous” increase in brain volume. The same argument might hold for drawing, music, language, indeed any human trait.”
He continues: “a similar argument can be put forth to explain the occasional emergence of genius or extraordinary talent in the normal population, or to answer the especially vexing question of how such abilities cropped up in evolution in the first place.” (PHANTOMS IN THE BRAIN by Sandra Blakeslee & V. S. Ramachandran p. 192)

Minggu, 08 Januari 2017

Artificial intelligence and Chinese room argument


Marvin Lee Minsky

American cognitive scientist Marvin Lee Minsky once wrote: “Will robots inherit the earth? Yes, but they will be our children.”
Robots are machines run by artificial intelligence.  Artificial intelligence is a product of human intelligence.
But, what is intelligence?
 Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines.
Computation and calculation
Computation is a type of calculation. A calculation is a process for transforming one or more inputs into one or more results, with variable change.
The term is used in a variety of senses, from the very definite arithmetical calculation of using an algorithm to logically calculating a strategy in a competition or the chance of a successful relationship between two people.
For example, multiplying 7 by 8 is a simple algorithmic calculation. Estimating the fair price for financial instruments using the Black–Scholes model is a complex
algorithmic calculation.
To calculate means to ascertain by computing. The English word derives from the Latin calculus, which originally meant a small stone in the gall-bladder (from Latin calx). It also meant a pebble used for calculating, or a small stone used as a counter in an abacus. The abacus was an instrument used by Greeks and Romans for arithmetic calculations, preceding the slide-rule and the electronic calculator. It consisted of perforated pebbles sliding on an iron bars.
What is artificial intelligence?
John McCarthy
Artificial intelligence (AI) is the intelligence of machines. Generally, the term is applied to the branch of computer science that aims to create AI. The text books dealing with the subject define the field as "the study and design of intelligent agents" where an intelligent agent is a system or machine that perceives its environment and takes actions that maximize its chances of success. John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence". He defines AI as "the science and engineering of making intelligent machines." AI research is highly technical and specialized, divided into subfields. Machine implementation of human cognitive ability is an ambitious and challenging objective. Its ultimate goal includes total integration, understanding, and representation of animal behavours and cognitive processes of humans—namely, thinking, feeling, speaking, symbolic processing, remembering, learning, knowing, consciousness, problem solving, planning, and decision making. These processes compose a broad cognitive and behavioural spectrum of living systems.
Human mind consists of modules
Many cognitive scientists depict the mind as “modular”—consisting of different parts that interact to produce both external behaviors and internal phenomena such as introspection. Such compartmental paradigms make it possible to create models of mind and build machines that based on such modular concepts. This paradigm provides for emulating the human brain. Such forms of emulation are the very essence of artificial intelligence. Naturally the AI has different branches or subspecialties performing different functions.
Subspecialties or programs of artificial intelligence:
Logical AI
This program decides what to do by inferring that certain actions are appropriate for achieving its goals. Cognitive scientist Robert C. Moore distinguishes three uses of logic in AI; as a tool of analysis, as a basis for knowledge representation, and as a programming language.
Search
AI programs often examine large numbers of possibilities, e.g. moves in a chess game or inferences by a theorem-proving program.
Pattern recognition
When a program makes observations of some kind, it is often programmed to compare what it sees with a pattern. For example, a vision program may try to match a pattern of eyes and a nose in a scene in order to find a face.
Representation
Facts about the world have to be represented in some way. Usually languages of mathematical logic are used.
Inference
From some facts, others can be inferred. This is emulation of human reasoning. The simplest kind of non-monotonic reasoning is default reasoning in which a conclusion is to be inferred by default, but the conclusion can be withdrawn if there is evidence to the contrary. For example, when we hear of a bird, we may infer that it can fly, but this conclusion can be reversed when we hear that it is a penguin. It is the possibility that a conclusion may have to be withdrawn that constitutes the non-monotonic character of the reasoning.
Commonsense knowledge and reasoning
This is the area in which AI is farthest from human-level, in spite of the fact that it has been an active research area since the 1950s.
Learning from experience
Programs do that. Such programs are made imitating the neural networks of human brain.
Planning
Planning programs start with general facts about the world (especially facts about the effects of actions), facts about the particular situation and a statement of a goal. From these, they generate a strategy for achieving the goal. In the most common cases, the strategy is just a sequence of actions.
The list of programs is incomplete. Some of these may be regarded as concepts or topics rather than full branches.
Chinese room argument
Cognitive scientists Stuart Russell and Peter Norvig wrote in the third edition (2009) of the book Artificial Intelligence: A Modern Approach: “Once we have a complete, comprehensive theory of mind, it becomes possible to express the model in machine form.”  But some philosophers think this is over confidence and they believe the “Chinese-room-argument” is valid for ever.
The Chinese Room argument was put forward by American philosopher John Rogers Searle. It is an argument against the possibility of artificial intelligence which is true replica of human mind. The argument centers on a thought experiment in which someone who knows only English sits alone in a room following English instructions for manipulating strings of Chinese characters. To those outside the room watching the performer it appears as if someone in the room understands Chinese. Searle summarized the Chinese Room argument concisely:
Imagine a native English speaker who knows no Chinese locked in a room full of boxes of Chinese symbols (a data base) together with a book of instructions for manipulating the symbols (the program). Imagine that people outside the room send in other Chinese symbols which, unknown to the person in the room, are questions in Chinese (the input). And imagine that by following the instructions in the program the man in the room is able to pass out Chinese symbols which are correct answers to the questions (the output). The program enables the person in the room to pass the Turing Test for understanding Chinese without understand a word of Chinese.
Searle goes on to say, 
The point of the argument is this: if the man in the room does not understand Chinese on the basis of implementing the appropriate program for understanding Chinese then neither does any other digital computer solely on that basis because no computer, qua computer, has anything the man does not have.
John Rogers Searle 

Searle develops broader implications of his argument. Searle also aims to refute the functionalist approach to understanding minds, especially that form of functionalism known as the Computational Theory of Mind that treats minds as information processing systems. As a result of its scope, as well as Searle's clear and forceful writing style, the Chinese Room argument has probably been the most widely discussed philosophical argument in cognitive science to appear in the in the past 25 years. By 1991 computer scientist Pat Hayes had defined Cognitive Science as the ongoing research project of refuting Searle's argument.