A Simple Explanation of the Differences Between AI and Traditional Programming

AI and Programs: Similar but Different

Both AI (artificial intelligence) and programs run on computers and are important technologies that support our lives and businesses. However, these two are fundamentally different, and each has different areas of expertise and roles. As AI rapidly evolves and permeates our lives, correctly understanding the difference between AI and programs is essential to effectively utilize these technologies.

In this article, we will explain the differences between AI and programs in an easy-to-understand way, and take a detailed look at their respective mechanisms, areas of expertise, use cases, and future possibilities. We will also touch upon common misconceptions about AI and programs, and consider the future in which these technologies coexist.

The fundamental difference between AI and programming

While AI and programs have in common that they both run on computers, the essential difference between them lies in their learning ability, flexibility, and versatility.

Differences in definition

• AI (Artificial Intelligence): A general term for technologies that mimic human intelligence and enable computers to perform intellectual activities such as learning, inference, and judgment.
• Program: A specific set of processing instructions written in a language that a computer can understand.

Ability to learn

• AI: AI uses a technique called machine learning to learn patterns and regularities from data and evolve autonomously.
• For example, an AI that can recognize cats from large amounts of image data can learn the characteristics of cats and then identify cats even in unfamiliar images.
• Programs: Programs faithfully carry out processing steps that have been predefined by humans.
• For example, a calculator program takes numbers entered and outputs the answer using a predefined calculation method.

Flexibility and versatility

• AI: AI can react to new situations and data based on learned knowledge and experience.
• For example, self-driving cars can navigate safely while adapting to a variety of road conditions and weather conditions.
• Programs: Programs can only execute their intended processing steps.
• For example, a calculator program cannot perform tasks other than calculations (such as writing text).

These differences mean that AI is good at solving problems in complex and changing environments and creative tasks, while programs are good at routine processing that requires accuracy and reproducibility.

Detailed explanation of how AI and programs work

Although both AI and programs run on computers, their internal mechanisms are very different. Here we will explain in detail how programs and AI work.

How the program works

A program is a set of instructions written in a programming language for a computer to execute. Programs operate based on algorithms designed by humans, and carry out predetermined processing steps on input data.

Programming languages and algorithms

• Programming language: A language for writing programs. There are various programming languages, such as Python, Java, C++, etc. Each language has its own grammar and characteristics, and is used according to the purpose.
• Algorithm: A clearly defined procedure for solving a problem. For example, a sorting algorithm defines the steps to rearrange data into a particular order.

Conditional branching and loop processing

Programs can achieve complex processing by using conditional branching and repetitive processing.

• Conditional Branching: Performing certain actions only if certain conditions are met, for example, “if it’s raining, bring an umbrella.”
• Repetitive Processing: Repeating the same process while a certain condition is met, such as “adding the numbers from 1 to 100.”

Program execution process

The program runs in the following process:

1. Writing source code: The program’s processing steps are written using a programming language.
2. Compiling or Interpretation: Converting source code into a form that the computer can run. Compiled languages (such as C++) convert the entire source code into machine code up front, while interpreted languages (such as Python) convert it line by line into machine code at run time.
3. Execution: The converted code is executed on the computer and the results are printed out.

How AI works

AI uses a technique called machine learning to learn patterns and regularities from data and perform tasks such as predictions and judgments. There are various types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning.

Machine Learning and Deep Learning

• Machine learning: A general term for technologies that allow computers to learn from data and discover patterns and regularities.
• Deep Learning: A type of machine learning that uses neural networks that mimic the neural circuits in the human brain to learn more complex patterns.

neural network

A neural network is a network structure in which many nodes (neurons) are interconnected. Each node receives input from other nodes, performs calculations, and outputs the results.

A neural network consists of three layers: an input layer, a hidden layer, and an output layer. The input layer receives data, the hidden layer extracts features, and the output layer outputs the results. The more hidden layers there are, the more complex patterns a neural network can learn.

Training data and models

• Training data: This is the data that an AI model uses to learn. There are various types of data, such as images, audio, and text. The quality and quantity of training data greatly affect the performance of an AI model.
• Model: A representation of patterns or regularities extracted from training data. An AI model makes predictions or decisions based on the training data.

AI inference process

AI performs inference through the following process.

1. Acquire input data: Acquire data from sensors, cameras, etc.
2. Data Preprocessing: Convert the acquired data into a format that is easy for the AI model to process.
3. Inference using AI models: Input data is fed into the AI model to make predictions or decisions.
4. Generate output: Generate appropriate actions or responses based on the inference results of the AI model.

Comparison table of AI and programs

Features	Program	AI
Definition	A description of specific processing procedures	Technology that imitates intellectual activity
How it works	It works based on algorithms	It learns from data and evolves autonomously
Areas of expertise	Accuracy, repeatability, routine processing, fast calculations	Pattern recognition, prediction and judgment, complex problem solving, creative tasks
Use cases	Business systems, web applications, database management	Customer analysis, demand forecasting, fraud detection, chatbots, autonomous driving, robot control

As you can see from this comparison table, AI and programs each have different characteristics and areas of expertise. AI can perform complex tasks that are difficult for programs to perform, but on the other hand, it cannot guarantee the same accuracy and reproducibility as programs.

AI and programs complement each other. AI solves problems that programs cannot solve, and programs are used as tools to maximize the capabilities of AI. By appropriately combining the two, we can develop more advanced systems and services.

Areas of expertise in AI and programming

AI and programs each have different strengths. Here, we will compare the areas in which they excel and explain them with concrete examples.

What programming is good at

Because the program operates based on algorithms designed by humans, it excels in three ways:

1. Accuracy and repeatability:
   Because programs follow predefined procedures, they always produce the same results for the same inputs. This accuracy and repeatability is especially important in areas where high reliability is required, such as bank ATM systems or aircraft control systems.

• Example: A bank’s ATM system must always perform accurate transactions such as checking deposit balances and withdrawing cash. Programs support the reliability of the financial system by executing these transactions accurately and reproducibly.

1. Routine Processing:
   Programs can efficiently execute routine processes that are repeated. For example, tasks such as data entry, tabulation, and calculations can be automated using programs, significantly reducing the time and effort required.

• Example: Accounting software automates routine accounting processes such as entering invoices and creating ledgers, reducing the burden on accounting staff and improving work efficiency.

1. Fast Calculation:
   The program can make the most of the computing power of the computer to perform high-speed calculations. It is used in fields that require large amounts of calculations, such as scientific and technological calculations, simulations, and data analysis.

• Example: Weather forecasts use supercomputers to perform numerical calculations based on complex weather models to achieve highly accurate predictions.

What AI is good at

AI uses machine learning to learn patterns and regularities from data, which gives it four advantages:

1. Pattern Recognition:
   AI can recognize complex patterns in large amounts of data and excels at tasks that mimic human sensory organs, such as image recognition, speech recognition, and natural language processing.

• Example: Facial recognition systems can identify individuals from images of their faces because AI has trained itself on large amounts of facial image data and is now able to pick out facial features.

1. Prediction and Judgment:
   AI can predict the future from past data and make optimal decisions based on the current situation. For example, it is used in demand forecasting, stock price forecasting, medical diagnosis, and more.

• Example: Demand forecasting AI analyzes past sales data and market trends to predict future demand, helping companies optimize their inventory management and production plans.

1. Complex problem solving:
   AI can solve complex problems that are difficult for humans to solve. For example, AI has beaten top human players in games such as Go and Shogi. AI is also used in the fields of science and technology, such as predicting the three-dimensional structure of proteins and developing new drugs.

• Example: AlphaFold is a protein three-dimensional structure prediction AI developed by Google DeepMind, which achieved accuracy far surpassing that of other participating teams at the protein structure prediction competition “CASP14” held in 2020.

1. Creative tasks:
   AI is also astonishing humans with its achievements in creative tasks such as music, painting, and novels. Some AI-generated works of art are of such high quality that they are indistinguishable from human works.

• Example: OpenAI’s DALL-E 2 is an AI that generates high-quality images from text, helping artists and designers with their creative work.

As such, AI and programs each have different strengths. AI excels in creativity and complex problem-solving, while programs excel in accuracy, reproducibility, and high-speed calculations.

Examples of using AI and programs

AI and programs are being used in various aspects of our lives and business. Here we will introduce examples of their use in business and everyday life.

Business Use

• Examples of how the program can be used:

Programs are essential for developing business-critical systems and applications.

• Business system: A system for making corporate operations more efficient. There are systems for various operations such as accounting, inventory management, and customer management. These systems are automated by programs, allowing operations to be processed accurately and efficiently.
• Web application: An application that runs on the Internet. Various web applications such as e-commerce sites, social networking sites, and online banking enrich our lives. These applications are developed by programs and provide functions such as user interface, data processing, and security.
• Database Management: A system for efficiently storing and managing large amounts of data. Various types of data are stored in databases, such as customer information, product information, sales data, etc. The program supports various aspects of database management, including database design, construction, operation, and maintenance.
• AI use cases:

AI is being used as a tool to solve various business problems and create new value.

• Customer analysis: Analyze customer attribute information, purchase history, website browsing history, etc. to understand customer needs and behavioral patterns. Based on this information, you can carry out targeted marketing measures and product development.
• Demand forecasting: Analyze past sales data and market trends to predict future demand. This allows you to optimize inventory management and production planning, leading to cost reduction and sales increase.
• Fraud Detection: We analyze data such as financial transactions and credit card usage to learn fraudulent patterns, which helps us improve our fraud detection systems and prevent fraud and unauthorized use before it happens.
• Chatbots: Automate customer inquiries on your website or in your app. By answering frequently asked questions and automating simple procedures, you can improve customer satisfaction and reduce support costs.

Use in everyday life

Programs and AI are deeply ingrained in our daily lives.

• Examples of how the program can be used:

Programs control a variety of products and services around us, including smartphone apps, home appliances, and transportation systems.

• Smartphone Apps: Smartphone apps that are indispensable to our lives, such as games, SNS, map apps, etc., are developed by programs. These apps provide user interfaces, data processing, communication functions, etc., making our lives more convenient.
• Home Appliances: Home appliances such as washing machines, refrigerators, and air conditioners are programmed to realize automatic operation and energy-saving functions. These home appliances not only make our lives more comfortable, but also contribute to energy conservation.
• Transportation systems: Public transportation systems such as trains and buses, as well as car navigation systems, are controlled by programs. These systems are essential for realizing safe and efficient transportation.
• AI use cases:

AI is being used in a variety of ways to make our daily lives more convenient.

• Voice Recognition: Voice assistants on smart speakers and smartphones use AI speech recognition technology to understand what we say and perform tasks such as playing music, getting weather forecasts, and managing schedules.
• Facial Recognition: It is widely used in the security field, such as unlocking smartphones and passport control at airports. AI facial recognition technology can accurately identify human faces and make identity verification more efficient.
• Recommendation system: On e-commerce sites, video streaming services, etc., AI analyzes large amounts of data and provides information that matches the user’s interests, improving convenience.

In this way, programs and AI are deeply integrated not only into business but also into our daily lives, supporting our lives in various ways.

The fusion of AI and programming: future possibilities

While AI and programs each have different strengths, they complement each other and can create even greater possibilities when combined. Here, we will explain the future that the fusion of AI and programs will bring about from two perspectives: AI-based programming and program-controlled AI.

AI-powered programming

AI is becoming a powerful partner for developers in the field of programming as well. By utilizing AI, we can expect to improve the efficiency of coding work, improve the quality of software, and even provide support to programming beginners.

• Code Generation:
• AI can automatically generate new code based on natural language instructions or existing code, freeing developers from routine coding tasks and allowing them to focus on more advanced design and algorithm development.
• GitHub Copilot: An AI programming support tool jointly developed by GitHub and OpenAI. When you enter a comment or function name in the code editor, the AI will suggest the code that follows.
• Tabnine: An AI tool that provides code completion. When a developer types code, the AI understands the context and suggests the most likely next code.
• Automatic Debugging:
• AI can automatically detect errors in your code and suggest fixes, which can make debugging more efficient.
• DeepCode: An AI-powered code review tool that detects potential bugs and security vulnerabilities in your code and suggests fixes.

Test Automation:

• AI can automatically generate software test cases and execute the tests, reducing the time and cost required for testing and contributing to improving software quality.
• Mabl: An AI-powered test automation platform that can automatically generate and execute test scenarios for web applications.

Programmed AI

AI can maximize its capabilities by being controlled by a program.

• Programmatically control AI learning, reasoning, and behavior:
• To train an AI model, a program is used to prepare training data, build a model, adjust hyperparameters, etc. The inferences and actions of the AI model are also controlled by the program.
• TensorFlow, PyTorch: These deep learning frameworks are tools for writing programs to train and perform inference on AI models.
• Self-driving cars, robots, etc.:
• Self-driving cars and robots are made possible by the cooperation of AI technology and programs. AI recognizes the surrounding situation from sensor data and determines the optimal action, but it is the program that actually carries out that action. The program controls the steering wheel and brakes of a car, the joints of a robot, etc. based on the judgment of the AI.

Common misconceptions about AI and programming

There are some common misconceptions about the relationship between AI and programs. Here we explain the most common misconceptions and their correct understanding.

Is AI better than programming?

AI can outperform humans in certain tasks, but only in those specific tasks. AI is realized by programs and cannot exist without programs.

AI and programs each have different strengths. AI excels at pattern recognition and complex problem solving, while programs excel at accuracy, reproducibility, and high-speed calculations.

It is not a question of which is superior, but rather that AI and programs complement each other by utilizing their respective strengths.

Will AI take away human jobs?

AI has the potential to take away human jobs by automating some tasks, but AI is merely a tool and cannot completely replace human work.

By performing tasks that humans are not good at, AI will allow humans to focus on more creative work and work that builds relationships. In addition, the evolution of AI may lead to the creation of new jobs that have never existed before.

AI should not be seen as a threat that will take away human jobs, but as a partner that will expand human capabilities and help build a more prosperous society.

Summary: Understand the differences between AI and programs and make the most of their respective strengths

Both AI and programs are important technologies that support our lives and businesses, but it is important to understand the essential difference between them. AI has the ability to learn from data and evolve autonomously, while programs perform accurate and reproducible processing based on algorithms designed by humans.

AI and programs each have different areas of expertise, so it is not possible to simply compare which is better. AI excels at pattern recognition and complex problem solving, while programs excel at accuracy, reproducibility, and high-speed calculations.

By understanding the differences between the two and leveraging their respective strengths, it will be possible to develop more advanced systems and services. For example, one possible collaboration would be one in which AI performs data analysis and predictions, and a program executes specific processing based on the results.

AI and programs are not competitors, but rather complement each other. As AI technology evolves, collaboration between AI and programs will become increasingly important.

The evolution of AI has the potential to bring about major changes in our lives and society. By correctly understanding the differences between AI and programs and leveraging the strengths of each, we can maximize the benefits of AI and build a richer future.