AI explained for beginners
Artificial Intelligence, often called AI, has become a buzzword in the modern world, with its influence reaching various aspects of our daily lives. From virtual assistants to recommendation systems, AI is transforming the way we interact with technology and the way businesses operate. But what exactly is AI, and how does it work?
What is Artificial Intelligence?
Artificial Intelligence is a branch of computer science that aims to create intelligent machines capable of performing tasks that typically require human intelligence. These tasks cover a wide range, from natural language understanding to pattern recognition, as well as complex problem-solving and decision-making. AI seeks to simulate human cognitive abilities such as learning, reasoning, perception, and problem-solving within machines.
Types of AI: Narrow AI VS General AI
There are two main categories of AI: Narrow AI (or Weak AI) and General AI (or Strong AI).
Narrow AI (Weak AI)
Narrow AI refers to AI systems designed and trained for specific tasks and that excel at those tasks. For example, virtual assistants like Siri and Alexa are examples of Narrow AI. They excel at understanding voice commands and providing relevant information, but they cannot perform tasks outside their designated domain.
General AI (Strong AI)
General AI, on the other hand, represents a level of artificial intelligence equivalent to human cognitive abilities across a wide range of tasks. It is a field of AI that is still largely theoretical and remains a subject of research and development.
How does AI work?
AI systems learn from data through a process called Machine Learning. Machine Learning is a subfield of AI that enables machines to learn and improve their performance without being explicitly programmed. Instead, they use data to recognize patterns, make predictions, and adapt to changing circumstances.
Supervised learning
In supervised learning, the AI system is provided with labeled data, meaning the input data is associated with corresponding desired outputs. The system learns from these examples to make predictions or classifications for new, unseen data.
Unsupervised learning
In unsupervised learning, the AI system receives unlabeled data and must identify patterns or groupings in the data without explicit guidance. This makes it possible to discover hidden structures and relationships in the data.
Reinforcement learning
Reinforcement learning involves training AI systems through a system of rewards and penalties. AI learns by interacting with an environment and receiving feedback based on its actions.
Applications of AI in practice
AI is increasingly present in various industries, contributing to advances and innovations. Some practical applications of AI include:
What about HR?
Artificial intelligence has been a game changer in the field of human resources, revolutionizing traditional HR practices and opening up new possibilities for talent management, especially in recruitment, assessment, training, performance reviews, and much more.