A United Nations report forecasts that by 2033, artificial intelligence will grow into a global market worth $4.8 trillion—comparable in size to Germany’s current economy. However, without urgent action, AI could exacerbate global inequalities and widen the digital divide even further.

Let's learn some AI-related terms to better understand news and reports.

⭐Machine Learning, /məˈʃiːn ˈlɜrnɪŋ/

📖Definition: Teaching computers to learn from data and improve by themselves, like a robot student.

💬Example: Machine learning helps apps suggest movies you might like.

⭐Neural Network, /ˈnjʊrəl ˈnɛtwɜrk/

📖Definition: A computer system designed like a human brain to recognize patterns and solve problems.

💬Example: Neural networks can recognize your face in photos.

⭐Deep Learning, /diːp ˈlɜrnɪŋ/

📖Definition: A type of machine learning using many layers of neural networks to learn complex things.

💬Example: Deep learning helps self-driving cars understand their surroundings.

⭐Natural Language Processing, /ˈnætʃrəl ˈlæŋɡwɪdʒ ˈprɑsɛsɪŋ/

📖Definition: Teaching computers to understand and talk in human language.

💬Example: Virtual assistants use natural language processing to answer your questions.

⭐Computer Vision, /kəmˈpjutər ˈvɪʒən/

📖Definition: Giving computers the ability to see and understand images and videos.

💬Example: Computer vision helps smartphones recognize objects in pictures.

⭐Reinforcement Learning, /ˌriɪnˈfɔrsmənt ˈlɜrnɪŋ/

📖Definition: Teaching AI to learn by rewards and mistakes, like training a pet.

💬Example: Reinforcement learning helps AI play games better than humans.

⭐Supervised Learning, /ˈsupərvaɪzd ˈlɜrnɪŋ/

📖Definition: Learning from data that already has the right answers, like a teacher’s guide.

💬Example: Supervised learning is used to detect spam emails.

⭐Unsupervised Learning, /ʌnˈsupərvaɪzd ˈlɜrnɪŋ/

📖Definition: Finding patterns in data without any answers, like solving a puzzle on your own.

💬Example: Unsupervised learning helps group customers by their shopping habits.

⭐Overfitting, /ˌoʊvərˈfɪtɪŋ/

📖Definition: When a model learns the training data too well but fails on new data, like memorizing without understanding.

💬Example: The AI overfitted the test and made mistakes on new examples.

⭐Backpropagation, /ˌbækprəˌpæɡəˈʃeɪʃən/

📖Definition: A way to fix mistakes in a neural network by sending error messages backward to adjust it.

💬Example: Backpropagation helps the AI improve step by step.