Only in the deep sea ______ such wonderful animals.

His tastes and habits ______ with those of his wife's.

There is much truth in the idea ______ kindness is usually served by frankness.

—Is there anything else to discuss? — ______, I guess.

Math is the subject ______.

When he spoke, she had an unpleasant ______ into what life would be like as his wife.

Peter had intended to take a job in business, but ______ that plan after the unpleasant experience in Canada in 2010.

The company went ______ because of its poor management.

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 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 AI rebels could turn out to be the only game in town.

He seemed persistent and ______ no matter what happened.

One of our rules is that every student ______ wear school uniform while at school.

The beauty of Venice, which fascinates all the visitors, ______ the style of its ancient buildings.

—There were a dozen pens in this house, but I can hardly find one now. — ______. One is sure to turn up.

—What are you going to do this weekend? — ______. If time permits, I may go to Shanghai with my friends.

阅读理解Passage 3 The scientific name is the Holocene Age, but climatologists like to call our current climatic phase the Long Summer

阅读理解Passage One If the new art is not accessible to everyone, which certainly seems to be the case, this implies that its impulses are not of a generically human kind

阅读理解They couldnt borrow money from anywhere because their neighbors were all on bad terms with them

阅读理解Passage Two Science and Technology Optimism and empowerment

阅读理解Passage Three If animals do have intelligence, how do scientists measure it? Before defining animals intelligence, scientists defined what is not intelligence

阅读理解All their teachers looked for were mistakes, and there are so many kinds of mistakes in writing that their students despair of ever learning to avoid them