Academic Reading Practice Task – Table Completion

The Development of Artificial Intelligence

Artificial Intelligence (AI) has rapidly evolved from a theoretical concept to a transformative technology that impacts various aspects of modern life. The journey of AI development has been marked by significant milestones in computer science, mathematics, and engineering.

The roots of AI can be traced back to the 1950s, when researchers began exploring the possibility of creating machines that could mimic human intelligence. One of the earliest milestones was the creation of the Turing Test by Alan Turing, which proposed a way to evaluate a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.

In the 1960s and 1970s, AI research saw the development of basic algorithms and early neural networks. These advancements laid the groundwork for machine learning, a subset of AI focused on creating systems that can learn from data and improve over time. Despite these early achievements, progress was slow due to limited computational power and data availability.

The 1980s and 1990s witnessed the rise of expert systems, which were designed to emulate the decision-making abilities of human experts. These systems found applications in various fields, including medical diagnosis, finance, and engineering. However, they were limited by their reliance on predefined rules and the inability to adapt to new information.

A major breakthrough came in the 2000s with the advent of big data and advancements in computational power. These developments enabled the creation of more sophisticated machine learning algorithms and deep learning models. Deep learning, which involves training large neural networks on vast amounts of data, revolutionized fields such as image recognition, natural language processing, and autonomous vehicles.

In the 2010s, AI began to permeate everyday life, with applications ranging from virtual assistants like Siri and Alexa to recommendation systems used by companies like Netflix and Amazon. The integration of AI into various industries has led to increased efficiency, cost savings, and the creation of new business models.

Today, AI continues to advance at a rapid pace, driven by ongoing research and development. Innovations such as reinforcement learning, generative adversarial networks (GANs), and quantum computing are pushing the boundaries of what AI can achieve. However, the rapid growth of AI also raises important ethical and societal questions, including concerns about privacy, job displacement, and the potential for biased algorithms.

Looking ahead, the future of AI holds tremendous potential. With continued investment and collaboration between academia, industry, and government, AI is poised to drive innovation and solve some of the world’s most pressing challenges. The transition from traditional computing to AI-driven technologies is not only reshaping industries but also redefining the way we interact with the world.

Complete the Table Below. Choose NO MORE THAN THREE WORDS from the Passage for Each Answer. Write your Answers in Boxes 9-13 on Your Answer Sheet.

Answers:

1. 1950s
2. 2010s

Questions:

1. What significant milestone in AI development is attributed to Alan Turing?
   • A) The creation of the first neural network
   • B) The proposal of the Turing Test
   • C) The development of big data analytics
   • D) The invention of expert systems
2. How did advancements in the 2000s revolutionize AI?
   • A) By introducing basic algorithms
   • B) By creating the Turing Test
   • C) By enabling deep learning models through big data and computational power
   • D) By developing the first expert systems
3. According to the passage, what was a limitation of expert systems developed in the 1980s and 1990s?
   • A) They were too slow to process data
   • B) They could not adapt to new information
   • C) They were too complex to understand
   • D) They required too much human intervention
4. What are some ethical and societal concerns related to the rapid growth of AI mentioned in the passage?
   • A) Increased efficiency and cost savings
   • B) Privacy, job displacement, and biased algorithms
   • C) Lack of computational power and data availability
   • D) The inability to solve complex problems

Answers:

1. B) The proposal of the Turing Test.
2. C) By enabling deep learning models through big data and computational power.
3. B) They could not adapt to new information.
4. B) Privacy, job displacement, and biased algorithms.

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