- Artificial Intelligence Tutorial
- AI - Home
- AI - Overview
- AI - History & Evolution
- AI - Types
- AI - Terminology
- AI - Tools & Frameworks
- AI - Applications
- AI - Real Life Examples
- AI - Ethics & Bias
- AI - Challenges
- Branches in AI
- AI - Research Areas
- AI - Machine Learning
- AI - Natural Language Processing
- AI - Computer Vision
- AI - Robotics
- AI - Fuzzy Logic Systems
- AI - Neural Networks
- AI - Evolutionary Computation
- AI - Swarm Intelligence
- AI - Cognitive Computing
- Intelligent Systems in AI
- AI - Intelligent Systems
- AI - Components of Intelligent Systems
- AI - Types of Intelligent Systems
- Agents & Environment
- AI - Agents and Environments
- Problem Solving in AI
- AI - Popular Search Algorithms
- AI - Constraint Satisfaction
- AI - Constraint Satisfaction Problem
- AI - Formal Representation of CSPs
- AI - Types of CSPs
- AI - Methods for Solving CSPs
- AI - Real-World Examples of CSPs
- Knowledge in AI
- AI - Knowledge Based Agent
- AI - Knowledge Representation
- AI - Knowledge Representation Techniques
- AI - Propositional Logic
- AI - Rules of Inference
- AI - First-order Logic
- AI - Inference Rules in First Order Logic
- AI - Knowledge Engineering in FOL
- AI - Unification in First Order Logic (FOL)
- AI - Resolution in First Order Logic (FOL)
- AI - Forward Chaining and backward chaining
- AI - Backward Chaining vs Forward Chaining
- Expert Systems in AI
- AI - Expert Systems
- AI - Applications of Expert Systems
- AI - Advantages & Limitations of Expert Systems
- AI - Applications
- AI - Predictive Analytics
- AI - Personalized Customer Experiences
- AI - Manufacturing Industry
- AI - Healthcare Breakthroughs
- AI - Decision Making
- AI - Business
- AI - Banking
- AI - Autonomous Vehicles
- AI - Automotive Industry
- AI - Data Analytics
- AI - Marketing
Artificial Intelligence - Overview
Since the invention of computers or machines, their capability to perform various tasks has continued to increase rapidly. Humans have achieved the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time. A branch of computer science named Artificial Intelligence is to build machines or computers that are as intelligent as people.
What is Artificial Intelligence?
Artificial intelligence is the technology that allows systems to replicate human behavior and thoughts. At its core, AI uses algorithms to train datasets that will generate AI models that let computer systems perform tasks like recommending songs, googling route directions, or providing text translations betweentwo languages. A few examples of AI are ChatGPT, Google Translate, Tesla, Netflix, and many more.
According to the father of artificial intelligence, John McCarthy, it is The science and engineering of making intelligent machines, especially intelligent computer programs..
History of AI
Artificial Intelligence has evolved since its inception in the mid-20th century. Initially, AI focused on automating simple tasks, and with advancements in machine learning and deep learning, it made significant improvements in understanding and processing data. Today, AI influences various fields, including healthcare, finance, and automobiles. Some of the key milestones in the history of AI are −
| Year | Milestone |
|---|---|
| 1923 | Karel apek play named Rossum's Universal Robots (RUR) opens in London, first use of the word "robot" in English. |
| 1956 | John McCarthy, a professor at Dartmouth College coined the term "Artificial Intelligence". |
| 1966 | Joseph Weizenbaum created ELIZA, that used natural language processing to make conversations with humans. |
| 1997 | Deep Blue was the first program to beat a human chess champion, Gray Kasparov. |
| 2012 | AlexNet is a convolution neural network (CNN) architecture that was designed by Alex Krizhevsky. |
| 2020 | OpenAI started beta testing GPT-3, a model that uses deep learning to create code, content, and other creative tasks. |
Goals of AI
The potential of AI is basically to mimic human skills and traits and apply them to machines. While the main objective of AI is to create a core technology that is able to allow computer systems to process intelligently and independently. Below are the essential goals of AI −
- To Create Expert Systems
- To Implement Human Intelligence in Machines
- To Develop Problem-Solving Ability
- To Allow Continuous Learning
- To Encourage Social Intelligence and Creativity
What Contributes to AI?
AI is a field that combines various scientific and technological disciplines, which include Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. The main objective of AI is to develop computer programs that can perform tasks with reasoning, learning, and solving problems similar to human intelligence.
AI Programming vs. Traditional Coding
Below is the difference between AI programming and traditional coding −
| AI Programming | Traditional Coding |
|---|---|
| Can deal with complex, undefined problems. | Can handle only well-defined, predictable problems. |
| Uses data-driven methods and algorithms. | Relies on explicit logic and rules. |
| Produces models that make predictions or decisions. | Generates specific functional software |
| Utilizes frameworks and libraries like TensorFlow, PyTorch. | Commonly uses languages like Python, Java. |
| Involves validation of model accuracy. | Focuses on debugging and unit testing. |
| Models learn patterns from data. | Programs execute pre-defined instructions. |
What is an AI Technique?
AI techniques refer to methods and algorithms that are used to create smart systems that perform tasks requiring human-like intelligence. Some of these techniques are Machine Learning, Natural Language Processing, Computer Vision and others. These AI techniques use the knowledge efficiently in such a way that −
- It should be perceivable by the people who provide it.
- It should be easily modifiable to correct errors.
- Elevate the speed of execution of the complex program it is equipped with.
Applications of AI
AI has been dominant in the following fields −
- Gaming − AI plays a crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.
- Natural Language Processing − It enables machines to interact with humans in natural language.
- Expert Systems − It is an AI based software that enables decision-making ability similar to a human expert.
- Computer Vision − These systems understand, interpret, and comprehend visual input on the computer.
- Speech Recognition − Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in humans noise due to cold, etc.
- Handwriting Recognition − The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text.
- Intelligent Robots − Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as temperature, movement, and sound. They have efficient processors, and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to new environment.
Challenges in AI
The main challenges in implementing AI includes −
- Data Quality and Accessibility − AI requires large, high-quality, and relevant datasets for effective learning.
- Technical Expertise − Implementing AI algorithms and models requires skilled professionals.
- Ethical and Legal Concerns − It is important to make sure that the AI systems are fair, unbiased, and don't harm anyone's safety.
- Integration − Integrating AI with existing systems can be complex.
- Cost − Developing and maintaining of AI infrastructure can be expensive.
Future of AI
As technology advances, we could witness greater integration of AI into our lives, and a more interactive relationship between humans and AI. Along with technology advancement is the need for ethical and privacy considerations including bias, privacy, and job displacement to help ensure that AI is beneficial to society as a whole.
The four key trends that define the future of AI include −
- Rise of Multimodal
- Emergence of Agentic platforms for AI Deployment
- Optimization of AI's performance
- Democratize AI Access.
Some of the other notable AI technologies that are going to shape various industries in the near future are rapid development of Generative AI and highlighting its transformative impact on various various industries.