hce_nchu
113年
英文
第 44 題
📖 題組：
Artificial Intelligence (AI) stands as the pinnacle of human ingenuity, representing the culmination of decades of research and innovation in the realm of computer science and cognitive psychology. AI systems, powered by advanced algorithms and neural networks, possess the remarkable ability to simulate human intelligence, learning, and problem-solving in ways previously thought unimaginable. At the forefront of AI research is the development of deep learning algorithms, inspired by the structure and function of the human brain. These algorithms, fueled by massive datasets and computational power, enable machines to recognize patterns, process natural language, and make decisions with astonishing accuracy and efficiency. From image recognition and speech synthesis to autonomous vehicles and medical diagnosis, the applications of deep learning span a myriad of domains, revolutionizing industries and transforming the way we live and work. One of the most exciting advancements in AI is the emergence of Generative Adversarial Networks (GANs), a groundbreaking framework for generating synthetic data with unprecedented realism. GANs consist of two neural networks—a generator and a discriminator—locked in a constant battle of wits, where the generator strives to produce indistinguishable data from real samples, while the discriminator aims to differentiate between real and fake data. This adversarial training process results in the creation of lifelike images, videos, and audio recordings that blur the line between reality and simulation. In addition to GANs, AI researchers are exploring the potential of reinforcement learning, a technique inspired by behavioral psychology and operant conditioning. Reinforcement learning algorithms learn to make decisions by interacting with an environment, receiving feedback in the form of rewards or penalties based on their actions. Through trial and error, these algorithms improve their decision-making abilities over time, mastering complex tasks such as playing video games, optimizing logistics, and controlling robotic systems. Despite the remarkable progress in AI, significant challenges remain on the horizon. Ethical considerations surrounding AI governance, transparency, and bias mitigation are hotly debated topics, raising concerns about the societal impact and ethical implications of AI-powered systems. Additionally, the pursuit of artificial general intelligence (AGI), a hypothetical form of AI that exhibits human-like intelligence across a wide range of tasks, poses profound philosophical and existential questions about the nature of consciousness and the future of humanity. In the midst of these challenges, the potential of AI to reshape the fabric of society and accelerate human progress is undeniable. By harnessing the power of AI responsibly and ethically, we can unlock unprecedented opportunities for innovation, discovery, and societal advancement.
Artificial Intelligence (AI) stands as the pinnacle of human ingenuity, representing the culmination of decades of research and innovation in the realm of computer science and cognitive psychology. AI systems, powered by advanced algorithms and neural networks, possess the remarkable ability to simulate human intelligence, learning, and problem-solving in ways previously thought unimaginable. At the forefront of AI research is the development of deep learning algorithms, inspired by the structure and function of the human brain. These algorithms, fueled by massive datasets and computational power, enable machines to recognize patterns, process natural language, and make decisions with astonishing accuracy and efficiency. From image recognition and speech synthesis to autonomous vehicles and medical diagnosis, the applications of deep learning span a myriad of domains, revolutionizing industries and transforming the way we live and work. One of the most exciting advancements in AI is the emergence of Generative Adversarial Networks (GANs), a groundbreaking framework for generating synthetic data with unprecedented realism. GANs consist of two neural networks—a generator and a discriminator—locked in a constant battle of wits, where the generator strives to produce indistinguishable data from real samples, while the discriminator aims to differentiate between real and fake data. This adversarial training process results in the creation of lifelike images, videos, and audio recordings that blur the line between reality and simulation. In addition to GANs, AI researchers are exploring the potential of reinforcement learning, a technique inspired by behavioral psychology and operant conditioning. Reinforcement learning algorithms learn to make decisions by interacting with an environment, receiving feedback in the form of rewards or penalties based on their actions. Through trial and error, these algorithms improve their decision-making abilities over time, mastering complex tasks such as playing video games, optimizing logistics, and controlling robotic systems. Despite the remarkable progress in AI, significant challenges remain on the horizon. Ethical considerations surrounding AI governance, transparency, and bias mitigation are hotly debated topics, raising concerns about the societal impact and ethical implications of AI-powered systems. Additionally, the pursuit of artificial general intelligence (AGI), a hypothetical form of AI that exhibits human-like intelligence across a wide range of tasks, poses profound philosophical and existential questions about the nature of consciousness and the future of humanity. In the midst of these challenges, the potential of AI to reshape the fabric of society and accelerate human progress is undeniable. By harnessing the power of AI responsibly and ethically, we can unlock unprecedented opportunities for innovation, discovery, and societal advancement.
According to the passage, what are some of the hurdles that AI encounters?
- A Moral considerations and bias alleviation
- B Legal regulations and government oversight
- C Technological limitations and computational constraints
- D Economic disparities and workforce displacement
- E Environmental sustainability and energy consumption
思路引導 VIP
若我們想在長文中快速尋找這類關於「問題」或「困難」的資訊，通常會建議先觀察段落的首句。請試著掃視文章後半部，看看哪一個段落出現了代表「挑戰」或「尚未解決之事」的關鍵字？找到該段落後，作者具體提到了哪些關於『人類價值觀判斷』或『消除不公平』的專有名詞呢？
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AI 詳解
AI 專屬家教
恭喜你精確地捕捉到了文章的轉折點！這題能答對，代表你對長篇文章的資訊定位（Information Locating）以及同義詞轉換（Paraphrasing）有著敏銳的觀察力。
文本關鍵與核心概念
正確答案 (A) Moral considerations and bias alleviation 完美對應了文章第五段的首句。文中提到 AI 面臨的挑戰包括 「Ethical considerations」（倫理考量）以及 「bias mitigation」（偏見緩解）。在選項中，命題老師巧妙地將其替換為意涵相近的 「Moral」與 「alleviation」。這種詞彙替換是閱讀測驗中常見的陷阱，你能成功識破，說明你的單字儲備量非常紮實。
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