Artificial Intelligence (AI)

Major Goals

AI is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making.

Approaches

Learning: Algorithms that model human reasoning through step-by-step deduction.
Planning: Agents making decisions to achieve goals, with probabilistic and deterministic models.
Reasoning: Involving logical deductions and understanding complex relationships.

Applications

High-profile applications: Advanced web search engines (e.g., Google Search), recommendation systems (YouTube, Amazon, Netflix), virtual assistants (Google Assistant, Siri, Alexa), autonomous vehicles (Waymo), generative and creative tools (language models, AI art), and superhuman play and analysis in strategy games (chess, Go).

Philosophy

AI research draws from various disciplines, including philosophy, psychology, linguistics, and neuroscience. The goal of AI is to simulate human-like intelligence, aiming to achieve artificial general intelligence (AGI) or similar capabilities.

History

Founding: AI was founded as an academic discipline in 1956.
Winters: There were periods of disappointment and loss of funding, known as AI winters.
Growth: After 2012, GPU acceleration enabled deep learning, leading to progress in the AI boom.

Subfields of AI Research

Traditional Goals

Learning: Improving performance through experience.
Planning: Making decisions based on known situations.
Reasoning: Solving complex logical problems.

Techniques

Search and mathematical optimization.
Formal logic, artificial neural networks, statistics, and economics.
Psychology, linguistics, and philosophy.

Current Trends

Generative AI: AI can create and modify content, leading to unintended consequences and ethical concerns.
Ethical and Regulatory Issues: Discussions about AI safety and benefits are ongoing.
Future Research: Ongoing advancements in transformer-based models, AGI research, and affective computing.