AI is referred to as Disruptive Technology for all these

Q: Answer-AI is referred to as Disruptive Technology for all these reasons EXCEPT:

All the factors except 4th are implied in the passage

reasons EXCEPT: Read the following passage and answer the following questions. Some words are given in bold letters to help you answer the related questions. Automation In agriculture is an emerging subject across the world. In recent times, Artificial Intelligence has been seeing a lot of direct application in farming. AI-powered solutions will not only enable farmers to do more with less, it will also improve quality and ensure faster go-to-market for crops. Advances in computer vision, mechatronics, artificial intelligence, and machine learning are enabling the development and deployment of remote sensing technologies to identify and manage plants, weeds, pests and diseases. This also provides a unique opportunity to develop intelligent seeding methods for precise fertilisation. Artificial intelligence solutions can enable farmers not only to reduce wastage, but also improve quality and ensure faster market access for the produce. Cognitive computing has become the most disruptive technology in agricultural services as it can learn, understand, and interact with different environments to maximise productivity. Microsoft is currently working with 175 farmers in Andhra Pradesh to provide agricultural, land and fertiliser advisory services. This initiative has already resulted in 30% higher average yield per hectare last year. Proximity sensing, remote sensing, Internet of Things (IoT) and image-based Precision Farming are being used for intelligent data integration related to historical meteorology, soil reports, recent research, rainfall, insect infections and along with drone imagery is being used for in-depth field analysis, crop monitoring and field surveys. Thousands of field data points are captured on the ground every day. With the help of artificial intelligence, farmers can now extract and analyse information such as weather, temperature, water consumption or soil conditions collected from their field which can also be collected in real-time. Artificial intelligence technology is already helping farmers achieve higher yields through better crop selection, hybrid seed selection and resource utilisation and also to improve the quality and accuracy of crops – something called precision farming. Precision farming uses artificial intelligence techniques to detect disease, pests, and malnutrition in the field. AI sensors can detect and target weeds and then determine the pesticides and weedicides to be used in the identified buffer zone. This helps in optimising the amount of pesticides and weedicides to be used by the farmers. AI is also aiding farmers to develop seasonal forecast models to improve farming accuracy and improve productivity. This can also help farmers to make better decisions using technologies to predict future weather trends over the next several months. Seasonal forecasts are mainly targeted at small farms in developing countries as data and knowledge may be limited. Since these small farms produce 70% of the world’s harvest, it is important that these small farmers produce the highest yields.

A Learning ability

B Perceptiveness

C Adaptability

D Predictability

E None of these

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