Artificial Intelligence: Comparing the Types and Their Effects

GS paper 3

Curriculum: Scientific and technical developments and their applications and effects in everyday life

Source: TH

Context: AI can traditionally be divided into Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI).

AGI and ANI: The difference lies in their level of intelligence and their ability to generalize knowledge across different contexts.

AGI ANI ● Flexible and adaptable

● Designed to perform a variety of intellectual tasks without human intervention

● Unsupervised learning means that the AI ​​system can learn from data without being explicitly programmed to do so

● Lack of control leads to continued learning and decisions (based on incomplete or uncertain information) that even the creators are unable to predict.

● In the field of theoretical research and development.

● Designed to perform a single or a limited number of related tasks.

● Not necessarily able to think or learn like humans.

● Typically trained with machine learning algorithms, e.g. B. supervised learning, unsupervised learning or reinforcement learning.

● Widespread use in a variety of industries and applications

● For example ChatGPT – is a chatbot that allows users to engage in conversation on a variety of topics.

Benefits of AI:

Disruptive technology creates new jobs and skills by creating a demand for expertise in machine learning, data science and natural language processing. It will transform industries by creating new opportunities for growth and innovation. In industries like healthcare, AI can optimize transportation networks, design new materials, and even simplify manufacturing processes.

Threats: ChatGPT/similar solutions have the ability to automate routine and repetitive tasks (data entry, customer service) that could potentially replace low-skilled staff.

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Conclusion: The impact of AI on jobs and industries is likely to be uneven. Therefore, significant investments in education and training programs and proactive strategies are the need of the hour.

The Science behind AI: Neural Network

A neural network is a computer system designed to learn and recognize patterns, like a simplified version of the human brain. It’s made up of layers of interconnected nodes, or “neurons,” each of which performs a simple calculation.

Neural networks have become increasingly popular in recent years due to their ability to learn complex patterns and make accurate predictions. They have been used in a variety of applications including self-driving cars, speech recognition, and medical diagnostics.

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