AI | Computer for GCSE/IGCSE - Year 11 PDF Download

What is Artificial Intelligence (AI)?

Artificial Intelligence refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction.

Applications of AI

• Virtual Assistants (e.g., Siri, Alexa)
• Recommendation Systems (e.g., Netflix recommendations)
• Self-driving Cars
• Fraud Detection in Banking

Importance of AI

• AI plays a crucial role in various fields such as healthcare, finance, transportation, and entertainment. 
• It enhances efficiency, accuracy, and decision-making processes.

Understanding Artificial Intelligence

• Artificial Intelligence (AI) is a field within computer science that focuses on developing computer systems capable of executing tasks that typically necessitate human intelligence.
• AI aims to replicate intelligent behaviors in machines, encompassing problem-solving, decision-making, and natural language processing.
• Examples of AI applications include Robotics, Natural Language Processing, Expert Systems, and Machine Learning.

Types of Artificial Intelligence

• Weak AI, also referred to as narrow AI, is engineered to perform specific tasks or a set of tasks.
• Strong AI, known as artificial general intelligence (AGI), is designed to undertake any intellectual task akin to humans.
• Superintelligence is a theoretical form of AI surpassing human intelligence comprehensively.

Advantages and Disadvantages of AI

• AI offers benefits such as enhanced efficiency, precision, and scalability in various domains.
• However, potential drawbacks of AI encompass the risk of job displacement, biased decision-making, and ethical dilemmas regarding its utilization.

Characteristics of AI

• Collection of Data and Rules: Artificial Intelligence (AI) systems rely on vast amounts of data to carry out tasks. This data is then processed using predefined rules or algorithms, allowing the system to make informed decisions and accurate predictions.
• Ability to Reason: AI systems possess the capability of logical reasoning. They can assess information logically and use this evaluation to make decisions based on the available data. For example, an AI-powered recommendation system on a streaming platform can analyze a user's viewing history to suggest relevant movies or shows.
• Ability to Learn and Adapt: An essential feature of AI is its capacity to learn from the data it encounters and adapt accordingly. This means that AI systems can modify their rules and adjust their responses based on new information. For instance, a self-driving car AI can improve its driving behavior over time by learning from different road situations.

Components

There are two main types of AI systems: 

Expert Systems

• Possess a knowledge base: Contains factual data to formulate rules utilized for problem-solving and decision-making.
• Possess a rule base: Comprises a set of logical rules utilized to apply the knowledge stored in the knowledge base to address particular issues.
• Possess an inference engine: Functions as a software program applying the rules from the rule base to the facts stored in the knowledge base to resolve problems.
• Possess an interface: Provides users with a means to interact with the system and offer input.

Machine Learning

• The software possesses self-adaptation capabilities, adjusting its processes and data automatically.
• It employs algorithms to scrutinize data, detecting patterns or correlations.
• The system learns from data and enhances its performance progressively.
• It can operate in either supervised or unsupervised modes:
  • Supervised machine learning employs labeled data to train the system.
  • Unsupervised machine learning utilizes unlabeled data.