The object used to separate off or close sections of a road is usually in the shape of ______.

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 house work. But as useful 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 and 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 pro grams. 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 lost 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 an artificially intelligent device, he claims, would be to build it around the same sort of molecular skills.

Right now, the notion 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 Al rebels could turn out to be the only game in town.

The author says that the powerful computers of today ______.

A．are capable of reliably recognizing the shape of an object

B．are close to exhibiting humanlike behavior

C．are not very different in their performance from those of the 50's

D．still cannot communicate with people in a human language

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 as useful 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 Al, 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 re- suits 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 fore- front of the field.

Imitating the brain's neural 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 pat- tern-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 notion that conventional computers and software are fundamentally incapable of matching the processes that take place in the brain remains controversial. But if it pr. yes true, then the efforts of Conrad and his fellow Al rebels could turn out to be the only game in town.

The author says that the powerful computers of today ______.

A．are capable of reliably recognizing the shape of an object

B．are close to exhibiting humanlike behavior

C．are not very different in their performance from those of the 50's

D．still cannot communicate with people in a human language

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 as useful 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 tenmonth-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) network is a huge step in the right direction, says computer scientist and biophysicist Michael Conrad, but is 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 an artificially intelligent device, he claims, would be to build it around the same sort of molecular skills.

Right now, the notion 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 A1 rebels could turn out to be the only game in town.

The author says that the powerful computers of today______.

A．are capable of reliably recognizing the shape of an object

B．are close to exhibiting humanlike behavior

C．are not very different in their performance from those of the 50's

D．still cannot communicate with people in a human language

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 house-work. But as useful as computers are, they're nowhere close to achieving anything remotely resembling these early aspirations for human like 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 naturally 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 patternrecognition 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 author says that the powerful computers of today

A．are capable of reliably recognizing the shape of an object.

B．are close to exhibiting humanlike behavior.

C．are not very different in their performance from those of the 50's.

D．still cannot communicate with people in a human language.

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 as useful as computers are, they're nowhere close to achieving anything remotely resembling these early aspirations for human like 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 Al 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 net work 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 an artificially intelligent device, he claims, would be to build it around the same sort o{ 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 author says that the powerful computers of today ______.

A．are capable of reliably recognizing the shape of an object

B．are close to exhibiting humanlike behavior

C．are not very different in their performance from those of the 50's

D．still cannot communicate with people in a human language

In the 1950s, the pioneers of artificial intelligence (Al) predicted that, by the end of this century, computers would be conversing with us at work and robots would be performing our housework. But as useful as computers are, they're nowhere close to achieving anything remotely resembling these early aspirations for human like 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 Al 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 makeup each brain cell. The best way to build an 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 A1 rebels could turn out to be the only game in town.

The author says that the powerful computers of today ______.

A．are capable of reliably recognizing the shape of an object

B．are close to exhibiting humanlike behavior

C．are not very different in their performance from those of the 50's

D．still cannot communicate with people in a human language

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 as useful 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 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 an 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 author says that the powerful computers of today ______.

A．are capable of reliably recognizing the shape of an object

B．are close to exhibiting humanlike behavior

C．are not very different in their performance from those of the 50's

D．still cannot communicate with people in a human language

SECTION B PASSAGES

Directions: In this section, you will hear several passages. Listen to the passages carefully and then answer the questions that follow.

听力原文： The question of whether dogs have a sense of humor is often fiercely argued. My own opinion is that some have and some haven't. Dachshunds have, but not St Bernards or Great Danes. Apparently a dog has to be small to be fond of joke. You never find a Great Dane trying to be a comedian.

But it is fatal to let any dog know that he is funny, for he immediately loses his head and starts overdoing it. As an example of this I would point to Rudolph, a Dachshund I once owned, whose slogan was "Anything for a Laugh". Dachshunds are always the worst offenders in this respect because of peculiar shape. It is only natural that when a dog finds that his mere appearance makes the viewing public laugh, he should imagine that Nature intended him to be a comedian.

Sometimes Rudolph overplays his sense of humor, a typical example of which is he once stole ducks from a farm nearby and brought complaints on me. It is true that Dachshunds and other dogs have their faults, but they seem unimportant compared with their virtues.

According to the narrator, which kind of dogs is thought to have a sense of humor?

A．St Bernards.

B．Great Danes.

C．Dachshunds.

D．Shepherd dogs.