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In the 1950s, the pioneers of artificial intelligence (AI) predicted that, by the end of this century, computers would be conversing with us at work and robots would be performing our housework. But powerful as computers are, they"re nowhere close to achieving anything remotely resembling these early aspirations for humanlike behavior. Never mind something as complex as conversation: the most powerful computers struggle to reliably recognize the shape of an object, the most elementary of tasks for a ten-month-old kid.A growing group of AI researchers think they know where the field went wrong. The problem, the scientists say, is that AI has been trying to separate the highest, most abstract levels of thought, like language and mathematics, and to duplicate them with logical, step-by- step programs. A new movement in AI, on the other hand, takes a closer look at the more roundabout way in which nature came up with intelligence. Many of these researchers study evolution and natural adaptation instead of formal logic and conventional computer programs. Rather than digital computers and transistors, some want to work with brain cells and proteins. The results of these early efforts are as promising as they are peculiar, and the new nature-based AI movement is slowly but surely moving to the forefront of the field.Imitating the brain"s neural (神经的) network is a huge step in the right direction, says computer scientist and biophysicist Michael Conrad, but it still misses an important aspect of natural intelligence. "People tend to treat the brain as if it were made up of color-coded transistors", he explains, "but it"s not simply a clever network of switches. There are lots of important things going on inside the brain cells themselves. " Specifically, Conrad believes that many of the brain"s capabilities stem from the pattern recognition proficiency of the individual molecules that make up each brain cell. The best way to build and artificially intelligent device, he claims, would be to build it around the same sort of molecular skills.Right now, the option that conventional computers and software are fundamentally incapable of matching the processes that take place in the brain remains controversial. But if it proves true, then the efforts of Conrad and his fellow AI rebels could turn out to be the only game in town. Which of the following is closest in meaning to the phrase "the only game in town" ( Line 3, Para. 4)
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In the 1950s, the pioneers of artificial intelligence (AI) predicted that, by the end of this century, computers would be conversing with us at work and robots would be performing our housework. But powerful as computers are, they"re nowhere close to achieving anything remotely resembling these early aspirations for humanlike behavior. Never mind something as complex as conversation: the most powerful computers struggle to reliably recognize the shape of an object, the most elementary of tasks for a ten-month-old kid.A growing group of AI researchers think they know where the field went wrong. The problem, the scientists say, is that AI has been trying to separate the highest, most abstract levels of thought, like language and mathematics, and to duplicate them with logical, step-by- step programs. A new movement in AI, on the other hand, takes a closer look at the more roundabout way in which nature came up with intelligence. Many of these researchers study evolution and natural adaptation instead of formal logic and conventional computer programs. Rather than digital computers and transistors, some want to work with brain cells and proteins. The results of these early efforts are as promising as they are peculiar, and the new nature-based AI movement is slowly but surely moving to the forefront of the field.Imitating the brain"s neural (神经的) network is a huge step in the right direction, says computer scientist and biophysicist Michael Conrad, but it still misses an important aspect of natural intelligence. "People tend to treat the brain as if it were made up of color-coded transistors", he explains, "but it"s not simply a clever network of switches. There are lots of important things going on inside the brain cells themselves. " Specifically, Conrad believes that many of the brain"s capabilities stem from the pattern recognition proficiency of the individual molecules that make up each brain cell. The best way to build and artificially intelligent device, he claims, would be to build it around the same sort of molecular skills.Right now, the option that conventional computers and software are fundamentally incapable of matching the processes that take place in the brain remains controversial. But if it proves true, then the efforts of Conrad and his fellow AI rebels could turn out to be the only game in town. What"s the author"s opinion about the new AI movement
Get to know your authentic self. Discover the real you. Don"t blindly accept the role you were conditioned by others to fill. You have your own path to follow. Be your own independent person. Don"t allow peer pressure to force you into an inauthentic role. Being a man or woman isn"t about blindly following popular gender patterns, nor is it about rejecting such patterns out of hand and rebelliously embracing their opposites. Ultimately you must define what kind of man or woman you will become. This is a choice you must make for yourself as an individual, regardless of what anyone else thinks. What kind of man / woman do you wish to be Life awaits your answer...
In the United States, the first day nursery, was opened in 1854. Nurseries were established in various areas during the 1 half of the 19th century; most of 2 were charitable. Both in Europe and in the U.S., the day nursery movement received great 3 during the First World War, when 4 of manpower caused the industrial employment of unprecedented (前所未有) numbers of women. In some European countries nurseries were established 5 in munitions (军火) plants, under direct government sponsorship. 6 the number of nurseries in the U.S. also rose 7 , this rise was accomplished without government aid of any kind. During the years following the First World War, 8 , federal, State, and local governments gradually began to exercise a measure of control 9 the day nurseries, chiefly by 10 them.The 11 of the Second World War was quickly followed by an increase in the number of day nurseries in almost all countries, as women were 12 called up on to replace men in the factories. On this 13 the U.S. government immediately came to the support of the nursery schools, 14 $6,000,000 in July, 1942, for a nursery school program for the children of working mothers. Many States and local communities 15 this Federal aid. By the end of the war, in August, 1945, more than 100, 000 children were being cared 16 in daycare centers receiving Federal 17 . Soon afterward, the Federal government 18 cut down its expenditures for this purpose and later 19 them, causing a sharp drop in the number of nursery schools in operation. However, the expectation that most employed mothers would leave their 20 at the end of the war was only partly fulfilled.
In the 1950s, the pioneers of artificial intelligence (AI) predicted that, by the end of this century, computers would be conversing with us at work and robots would be performing our housework. But powerful as computers are, they"re nowhere close to achieving anything remotely resembling these early aspirations for humanlike behavior. Never mind something as complex as conversation: the most powerful computers struggle to reliably recognize the shape of an object, the most elementary of tasks for a ten-month-old kid.A growing group of AI researchers think they know where the field went wrong. The problem, the scientists say, is that AI has been trying to separate the highest, most abstract levels of thought, like language and mathematics, and to duplicate them with logical, step-by- step programs. A new movement in AI, on the other hand, takes a closer look at the more roundabout way in which nature came up with intelligence. Many of these researchers study evolution and natural adaptation instead of formal logic and conventional computer programs. Rather than digital computers and transistors, some want to work with brain cells and proteins. The results of these early efforts are as promising as they are peculiar, and the new nature-based AI movement is slowly but surely moving to the forefront of the field.Imitating the brain"s neural (神经的) network is a huge step in the right direction, says computer scientist and biophysicist Michael Conrad, but it still misses an important aspect of natural intelligence. "People tend to treat the brain as if it were made up of color-coded transistors", he explains, "but it"s not simply a clever network of switches. There are lots of important things going on inside the brain cells themselves. " Specifically, Conrad believes that many of the brain"s capabilities stem from the pattern recognition proficiency of the individual molecules that make up each brain cell. The best way to build and artificially intelligent device, he claims, would be to build it around the same sort of molecular skills.Right now, the option that conventional computers and software are fundamentally incapable of matching the processes that take place in the brain remains controversial. But if it proves true, then the efforts of Conrad and his fellow AI rebels could turn out to be the only game in town. The shortcoming in artificial intelligence research stems from ______.
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