1 . Artificial intelligence (Al) has the potential to develop more efficient methods of farming in order to fight global warming.
Global warming threatens every aspect of our everyday lives, including crop production. It will reduce the soil moisture (水分) in areas close to the equator according to a study. We are already seeing the negative impact of these changed growing conditions on our crop production. Climate change harms poorer countries that do not have the money to import food. The result is growing food insecurity. However, agriculture is not just affected by global warming — agriculture is part of a vicious (恶性的) cycle in which farming leads to global warming, which in turn destroys agricultural production. The process of clearing land for agriculture results in widespread deforestation (毁林) and contributes to 40 percent of global methane production. Therefore, to deal with climate change, it is necessary to ensure reforestation — but how? What is the path to efficient, environmentally-conscious farming?
This is where AI enters the scene. Farmers use AI for methods such as precision agriculture; they can monitor crop moisture, soil composition, and temperature in growing areas, enabling farmers to increase production by learning how to take care of their crops and determine the ideal amount of water to use. Furthermore, this technology may help reduce deforestation by allowing humans to grow food in urban areas. It could be especially beneficial for countries in Latin America and the Caribbean, where much of the population lives in cities.
However, AI is far from a silver bullet — it could actually contribute to global warming as well. Due to the large amount of data that AI needs to process, training a single AI releases five times the emissions that an average car would give off during its lifetime. Further, securing access to AI on a global scale may pose some challenges. Countries will need experts in the field who can successfully use the technology and Internet connection, neither of which are always readily available. Therefore, there is still a long way for developing countries to take advantage of the benefits of AI.
Given these concerns, global leaders must consider the potential costs, and the environmental consequences of data processing before developing AI for use in agriculture.
1. What can we learn about today’s agriculture from paragraph 2?| A．It is the main challenge of reforestation. |
| B．Poorer countries rely on it more than before. |
| C．It is still dependent on deforestation for more land. |
| D．It is both a victim and a cause of global warming. |
| A．Building farming communities in cities. |
| B．Abandoning traditional farming methods. |
| C．Making the most of agricultural resources. |
| D．Balancing farming with farmers’ everyday lives. |
| A．There are technical barriers in developing countries. |
| B．The relevant technology is still under development. |
| C．The process of developing Al is difficult. |
| D．There is no one-size-fits-all AI technology. |
| A．The benefits of agricultural AI |
| B．The future of farming: AI and agriculture |
| C．A block to environmentally-conscious agriculture |
| D．Global warming and agriculture: a vicious cycle |
| A．Rainy. | B．Cloudy. | C．Sunny. |
1. What is the purpose of the speaker?
| A．To forecast the weather. | B．To keep people informed. | C．To make an advertisement. |
| A．A terrible storm. | B．Heavy air traffic. | C．Mechanical problems. |
| A．Allow them to change flight routes. |
| B．Offer them free hotels. |
| C．Return all their money. |
| A．Cairo. | B．Panama. | C．Buenos Aires. |
| A．Sunny. | B．Rainy. | C．Cloudy. |
1. What can we learn from the news?
| A．No villager was killed. |
| B．15 houses were badly damaged. |
| C．Over 200 people were made homeless. |
| A．His wife was missing. |
| B．His house was destroyed. |
| C．One of his children was killed. |
| A．She tried to take something out. |
| B．She rushed out with her children. |
| C．She told her husband not to leave. |
| A．The sun. | B．The rain. | C．The insects. |
| A．Cloudy. | B．Sunny. | C．Rainy. |
| A．Rainy | B．Sunny | C．Cloudy |
9 . Predicting extreme weather events is a tricky business. Changing climate conditions have increased the frequency of severe storms, floods, and heatwaves, along with larger wildfires. As a result, scientists are using artificial intelligence (AI) techniques for more accurate forecasts that help to minimize damage and save lives.
Researchers at Pennsylvania State University have worked together with meteorologists (气象学家) to analyze more than 50,000 weather satellite images to quickly identify storms. They found comma-shaped cloud formations that often lead to severe weather such as hail, blizzards, high winds, and thunderstorms.
Computers were then taught using computer vision and machine learning to automatically detect these clouds from satellite images, with almost 100 percent accuracy, in less than a minute. By refocusing meteorologists’ attention on potential storm cloud formation the AI tool helped predict 64 percent of severe weather events and beat established detection systems.
Expensive supercomputers are often used to process vast amounts of data needed for accurate weather prediction. But powerful AI methods can run on smaller computers. Climate risk and planning company ClimateAI uses a technique to downscale global weather forecasts to a local scale, cutting down on costs and computing power.
It uses a machine learning technique that pits two neural networks against each other. The neural networks - designed to work like neurons connected in the brain - fight and train each other using global weather data until they get a result.
Using this method ClimateAI researchers generate highly accurate and inexpensive local forecasts for hours or days ahead. And because it is not as costly, it allows poorer countries affected by climate change to use forecasts to change the way they farm, build bridges, roads, or homes, and adapt to extreme weather.
Average costs associated with extreme weather events in the United States have increased steadily since 1980. These have costly impacts on cities’ basic services, infrastructure, housing, human livelihoods, and health. AI helps us to calculate that risk and can be used as a preventive measure.
1. What can be inferred from Para.1?| A．Inaccurate forecasts minimize the destruction. |
| B．AI enhances accuracy in making weather prediction. |
| C．Less natural disasters are caused by climate change. |
| D．Changeable climate decreased the frequency of serious storms. |
| A．Being steadier. | B．Being cheaper. |
| C．Being quicker. | D．Being more precise. |
| A．To explain how Climate AI works. |
| B．To introduce why AI methods are used. |
| C．To show where ClimateAI can be applied. |
| D．To identify what effects of the AI tool has. |
| A．Critical. | B．Approving. | C．Objective. | D．Indifferent. |
| A．Sunny. | B．Windy. | C．Rainy. |
