题目内容：

Many leading AI researchers think that in a matter of decades, artificial intelligence will be able to do not merely some of our jobs, but all of our jobs, forever transforming life on Earth.

The reason why many reject this as science fiction is that we’ve traditionally thought of intelligence as something mysterious that can only exist in biological organisms, especially humans. But such an idea is unscientific.

From my point of view as a physicist and AI researcher, intelligence is simply a certain kind of information-processing performed by elementary particles(基本粒子) moving around, and there is no law of physics that says one can’t build machines more intelligent than us in all ways. This suggests that we’ve only seen the tip of the intelligence iceberg and that there is an amazing potential to unlock the full intelligence that is potential in nature and use it to help humanity.

If we get it right, the upside is huge. Since everything we love about civilization is the  product of intelligence, amplifying(扩大) our own intelligence with AI has the potential to solve tomorrow’s toughest problems. For example, why risk our loved ones dying in traffic accidents that self-driving cars could prevent or dying of cancers that AI might help us find cures for? Why not increase productivity through automation (自动化) and use AI to accelerate our research and development of affordable sustainable(可持续的) energy?

I’m optimistic that we can develop rapidly with advanced AI as long as we win the race between the growing power of our technology and the knowledge with which we manage it. But this requires giving up our outdated concept of learning form mistakes. That helped us win the race with less powerful technology: We messed up with fire and then invented fire extinguishers (灭火器), and we messed up with cars and then invented seat belts. However, it’s an awful idea for more powerful technologies, such as nuclear weapons or superintelligent AI— where even a single mistake is unacceptable and we need to get things right the first time.

1.How do many people feel about leading AI researchers’ predictions?

A. Worried    B. Curious

C. Doubtful    D. Disappointed

2.What does the author think of intelligence?

A. We know little about it.    B. It belongs to human beings.

C. It is too difficult to understand.    D. We have a good command of it.

3.What does the underlined word “upside” in Paragraph 4 probably mean?

A. Cost.    B. Potential.

C. Quantity.    D. Advantage.

4.What’s important for us in the race between people and technology?

A. Learning from failure.    B. Increasing our intelligence.

C. Avoiding making mistakes.    D. Making accurate predictions.