Living with Al: Digital data Chapter Notes | IGCSE Cambridge Computing for Year 6 - Class 6 PDF Download

Applications and systems software

1. Software: It’s the set of instructions or programs that tell a digital device what to do.

2. Two Main Types:

   • Systems Software: This includes the operating system (like Windows or macOS) and utility programs. The operating system is crucial because it provides a user interface—the means for you to interact with the computer’s hardware and other software.

   • Applications Software: These are the programs used for specific tasks, like making a video call, creating documents, or browsing the internet. Examples include mobile apps, word processors, image editors, and web browsers.

3. Necessity: All digital devices need both types of software to function properly.

4. AI in Applications: Nowadays, some applications use artificial intelligence (AI) to enhance interaction. For instance, when you ask a digital assistant about the weather, it uses AI to understand your question and respond appropriately.

Al around us

Artificial Intelligence (AI) is a technology that enables digital devices to perform tasks that typically require human intelligence. This includes:

• Speech Recognition: Understanding and processing human speech.
• Image Recognition: Identifying objects, faces, and scenes in images.
• Self-Driving Cars: Navigating and driving without human intervention.
• Smart Assistants: Providing help and performing tasks through voice commands.
• Search Engines: Finding relevant results based on complex queries.
• Social Media Monitoring: Analyzing and understanding social media content.

The unique aspect of modern AI is its ability to learn from experience, much like humans. This means AI devices can improve their responses over time as they learn from past interactions.

For example, AI improves through:

• Voice Recognition: Becoming better at understanding a user’s voice and commands.
• Personalized Recommendations: Suggesting music or products based on the user’s preferences.
• Navigation Systems: Recognizing frequently visited locations and providing timely journey updates.

Here are five devices that commonly use AI in the home:

1. Smart Speakers: They learn your music tastes and voice commands.
2. Smartphones: They adapt to your usage patterns and preferences.
3. Smart Thermostats: They adjust the temperature based on your routine.
4. Security Cameras: They identify familiar faces and alert you to strangers.
5. Robot Vacuums: They learn the layout of your home for more efficient cleaning.

Over time, interactions with these AI devices improve as they adapt to individual behaviors, making the user experience more intuitive and personalized.

AI isn’t just about robots or automating mundane tasks; it’s integrated into many aspects of daily life. For instance:

• Spam Filters: Learn to identify unwanted emails more accurately.
• Digital Assistants: Get better at controlling home devices through voice.
• Search Engines: Understand natural language queries more effectively.
• Driverless Cars and Speed Cameras: Use image recognition for safer navigation.
• Security Devices: Recognize users even with changes in appearance.

Originally developed for games like chess, AI now enhances gaming experiences by creating dynamic non-player characters (NPCs) that interact with players.

AI is transforming lifestyles, work, shopping habits, and leisure activities. It’s constantly evolving, with research focused on developing AI that can even understand and respond to human emotions. 

Al in industry

 Let’s explore how artificial intelligence (AI) impacts various industries:

1. Sales Predictions:

   • AI analyzes past sales data stored in large databases.
   • Predictions about future sales help businesses order the right amount of goods, minimizing waste.

2. Fraud Detection:

   • AI monitors consumer purchases over time.
   • Unusual activity on a customer’s bank card triggers automated alerts to prevent fraud.

3. Chatbots:

   • AI-powered chatbots interact with users in a conversation-like manner.
   • They handle initial inquiries, answering questions or directing users to human assistants when needed.

4. Manufacturing:

   • AI designs computer programs for manufacturing processes.
   • Examples include adding contents to canned food products or assembling car parts.

5. Advertising:

   • AI collects data from users’ digital devices (via cookies).
   • Based on this data, AI targets personalized advertisements.
   • Ever noticed ads for something you were just discussing or searching online? That’s AI at work!

6. Healthcare:

   • AI assists in diagnosing illnesses and developing medicines.
   • Smartwatches monitor heart rates, alerting doctors to health issues.
   • Remote patient care benefits from AI applications.

Let’s explore the pros and cons of using artificial intelligence (AI) in various areas:

Pros of AI:

1. Reduction in Errors:

   • AI improves accuracy, especially in fields like weather forecasting.
   • Fewer mistakes mean better outcomes.

2. 24/7 Availability:

   • AI systems work continuously without breaks.
   • They monitor production standards, ensuring consistency.

3. Speed of Decision-Making:

   • Self-driving cars use AI to react faster to environmental changes than human drivers.
   • Quick responses enhance safety and efficiency.

4. Research and Development:

   • AI predicts health trends and informs decisions about healthcare facilities.
   • It adapts to changing societal needs.

Cons of AI:

1. Expensive Development:

   • Creating AI applications and associated devices is complex and costly.
   • Maintenance can also be expensive.

2. Unemployment Concerns:

   • AI performs tasks more efficiently than humans.
   • Some fear job losses due to automation.

3. Lack of Emotional Connection:

   • AI decisions are based on facts, not emotions.
   • For example, medical recommendations may not consider patients’ personal circumstances.

Collecting the input

When it comes to collecting input for AI systems, here’s a simplified breakdown of the process and some examples:

1. Input-Process-Output Model:

   • Input: Data supplied to the device, like a voice command.
   • Process: Analysis of the input, such as voice pattern recognition.
   • Output: The result, such as turning a lightbulb on or off.

2. Data Collection Methods:

   • Touchscreens: For typing queries.
   • Microphones: For voice commands.
   • Sensors: For environmental data.

3. AI in Everyday Life:

   • Traffic Cameras: Detect traffic build-up and adjust lights.
   • Facial Recognition: Alert services to potential crimes.
   • Mobile Phones: Provide local information like banks or restaurants.

4. Sensor Examples:

   • Temperature Sensor: Monitors body temperature in crowded places.
   • Proximity Sensor: Warns workers of approaching vehicles on construction sites.
   • Infrared Sensor: Used in drones to study wildlife in remote areas.

5. Uses of Sensors with AI:

   • Humidity Sensors: Control building environments.
   • Touch Sensors: Give robots a sense of touch to handle objects without damage.

Designing your own Al system

Smart homes are becoming increasingly common, and they offer a variety of convenient features:

1. Sensor-Activated Devices: Many devices in smart homes are activated by sensors. These can range from motion sensors that turn lights on and off to temperature sensors that adjust the thermostat.

2. Voice-Activated Instructions: Digital assistants like Amazon Alexa or Google Assistant allow users to control devices through voice commands. This hands-free control is one of the most popular features of smart homes.

3. Interconnectivity: Devices in a smart home are often interconnected, meaning they can communicate with each other. This network is typically connected to the internet, allowing for remote control and monitoring.

4. Control Through Various Devices: Users can control smart home devices through multiple interfaces, including smartphones, tablets, laptops, and even game consoles.

5. Convenience and Security: Smart homes not only offer convenience but also enhanced security. For example, users can remotely activate a burglar alarm system or check if they’ve left the lights on.

Representing data: Images

Data in AI systems can be represented in various formats, and images are a key example of this. 

1. Analogue vs. Digital Images:

   • Analogue Cameras: Used film to capture images, which then needed to be developed in a lab.
   • Digital Cameras: Capture images that are immediately available in digital format.

2. Binary Representation:

   • All data in computers, including images, is stored in binary format, using 1s and 0s.
   • A single binary digit is called a bit.

3. Converting Analogue to Digital:

   • Images must be converted to digital (binary) format for AI processing.
   • This is done by dividing an image into pixels, each represented by binary digits.

4. Bitmap Graphics:

   • Images are made up of pixels on a grid.
   • Each pixel’s color is represented by a set of binary digits.
   • Black and white images can use 1 bit per pixel (1 for black, 0 for white).

5. Resolution and Color Depth:

   • The resolution is measured in pixels per inch (ppi).
   • Higher resolution means more pixels and more data, resulting in larger file sizes.
   • Color depth refers to the number of bits used to represent the color of each pixel.

6. Storing Color Images:

   • More bits per pixel allow for more colors.
   • For example, 2 bits per pixel can represent four different colors (00 for white, 01 for black, 10 for green, etc.).

7. Memory Considerations:

   • Higher color depth and resolution lead to larger image files, which require more memory for processing and storage.

Vector graphics

Let’s explore the difference between vector graphics and bitmap images:

1. Vector Graphics:

   • Made up of shapes (like lines, curves, and polygons) placed on the screen.
   • Created using instructions about where each part of the image should be positioned.
   • Describes each part, including color and line length.
   • Doesn’t store information about every pixel individually.
   • Takes up less memory.
   • Ideal for scalability (no loss of quality when resized).

2. Bitmap Images (Raster Images):

   • Composed of individual pixels arranged in a grid.
   • Each pixel has its own color value (e.g., black, white, or shades in between).
   • When zoomed in, you can see individual pixels.
   • Each pixel can be edited or deleted.
   • Higher resolution means more pixels and larger file sizes.

3. Converting Analogue to Digital:

   • Analogue images (e.g., photographs) are converted into digital format.
   • The computer identifies each component and generates instructions to recreate the image.
   • These instructions are stored for further processing.

Representing data: Sound and text

1. AI Devices and Cameras:

   • Many AI devices, like driverless cars, use cameras and digital images to provide information to the processor.
   • These devices mimic the human brain and eyes by using sensors (such as cameras, speakers, and radar) to understand their environment.
   • For example, in self-driven cars, cameras help detect details in road signs, like speed limits, based on the surroundings.

2. Microphones and Sound:

   • Self-driven cars also use microphones to detect sounds, such as sirens from emergency vehicles or unusual engine noises.
   • But how do processors handle sound and text?

3. Converting Sound to Digital Format:

   • Data, including sound, must be converted into digital format before it can be stored on a computer.
   • Sound initially creates an analog signal, which enters the computer via a microphone.
   • Since computers can’t store analog data directly, the sound wave is converted into binary format using an analog-to-digital converter.

4. Processing Text:

   • Instructions can be programmed into AI systems using typed text.
   • When you type instructions or data via a keyboard, it’s stored in binary format.
   • Each key press on a keyboard generates a unique binary pattern.
   • For example, typing the word “HELLO” results in the following binary digits:
     • H: 01001000
     • E: 01100101
     • L: 01101100 (twice)
     • O: 01101111

Introduction to logic gates

Let’s simplify the concept of logic gates and how they function in digital devices:

1. What are Logic Gates?

   • Logic gates are the basic building blocks in digital circuits found inside processors.
   • They are used to process binary inputs (which are just 1s and 0s) to produce a single binary output.

2. How do Logic Gates Work?

   • Logic gates analyze the inputs (1s and 0s) to make decisions and create an output.
   • The inputs and outputs are represented by electricity, which can be in two states: ON (1) or OFF (0).
   • This ON/OFF state is perfect for representing binary digits because binary only has two digits: 1 and 0.

3. Combining Inputs:

   • A logic gate can take one or two inputs, process them, and then produce one output.
   • For more complex decisions, the output from one logic gate can feed into another, creating a chain of logic gates, which forms an electronic circuit.

4. Types of Logic Gates:

   • The output from a logic gate depends on its type and the combination of inputs it receives.
   • There are different types of logic gates, like AND, OR, NOT, NAND, NOR, XOR, and XNOR, each with its own rules for processing inputs.

5. Logic Gates in Everyday Devices:

   • You can find logic gates in many household digital devices that use electronic circuits to process data.
   • Examples include:
     • Burglar alarms: to decide if there is an intrusion based on sensor inputs.
     • Door bells: to sound the bell when someone presses the button.
     • Street lights: to turn on/off based on light sensors.
     • TV remote controls: to send different signals based on button presses.
     • Automatic lights on cars: to turn on/off based on external lighting conditions.

Types of logic gate

1. Boolean Logic:

   • Boolean logic deals with conditions that can only be true or false.
   • It uses operations like AND and OR to combine conditions and return a true or false value after comparison.

2. Logic Gates and Boolean Logic:

   • Logic gates use Boolean logic to process data inputs.
   • Different types of logic gates represent different Boolean operations.
   • Every action a processor takes involves millions of these Boolean logic operations.

3. Types of Logic Gates:

   • AND Gate: It has two inputs (1 or 0). It will only output 1 if both inputs are 1.
   • OR Gate: It has two inputs (1 or 0). It will output 1 if at least one of the inputs is 1.
   • NOT Gate: It has one input (1 or 0). The output will always be the opposite of the input.

4. Examples of Logic Gates in Action:

   • AND Gate Example: Think of deciding if you can have a cheese sandwich. You need two things: bread (Input A) and cheese (Input B). You can only have a sandwich (Output Z) if both are available (both inputs are true).
   • OR Gate Example: Consider deciding to play online games during the weekend. You have two friends (Inputs A and B). You will play (Output Z) if either friend A or friend B is online (if either input is true).
   • NOT Gate Example: Imagine an alarm system at home. If you are home (Input is 1), the alarm is off (Output is 0). If you are not home (Input is 0), the alarm is on (Output is 1).