AI Types, Branches, Techniques, Problem Solving, Big Data, and Full Benefits of AI
This updated version merges all previous content with the new slides. It includes summaries, many multiple choice questions, a read button, and an Arabic translation button for each question.
Quick Summary
Narrow AI
Weak AI used today for one specific task such as chat, recommendation, or voice assistance.
General AI
AGI is theoretical and would perform many intellectual tasks like humans using previous learning.
Super AI
Theoretical AI that would surpass human intelligence in thinking, learning, reasoning, and judgement.
Reactive Machine AI
Has no memory and works only with current data. IBM Deep Blue is a common example.
Limited Memory AI
Uses past and present data for a limited time and can improve performance from more data.
Self-Aware and Theory of Mind AI
Both are unrealized. Self-aware AI would know its own state; Theory of Mind AI would understand others’ thoughts and emotions.
AI Branches
Computer Vision handles images, Robotics automates tasks, Expert Systems simulate expertise, and NLP handles human language.
AI Tools vs Techniques
Tools are software platforms like TensorFlow or OpenCV. Techniques are methods like machine learning, deep learning, or rule-based reasoning.
Search-Based Approaches
AI explores possible solutions. Uninformed search includes BFS and DFS, while informed search includes A* and Greedy Best-First Search.
Knowledge and Constraints
Knowledge-based approaches include Expert Systems and Case-Based Reasoning. CSPs solve problems under rules and conditions such as Sudoku or timetabling.
Logic and Learning
Logical reasoning uses propositional, predicate, and fuzzy logic. Machine learning uses supervised, unsupervised, and reinforcement learning.
Optimisation and Probability
Evolutionary approaches include Genetic Algorithms and Swarm Intelligence. Probabilistic approaches include Bayesian Networks and MDPs.
Hybrid Approaches
Hybrid AI combines techniques together, such as Deep Reinforcement Learning, to improve problem-solving.
Big Data and Machine Learning
Big Data refers to very large datasets, and Machine Learning uses data to learn patterns and make predictions or decisions.
Benefits of AI
AI increases efficiency, saves costs, supports 24/7 service, personalizes content, improves security and healthcare, and accelerates scientific discovery.