Artificial Intelligence (AI) is a field of science and engineering that aims to enable machines to perform tasks that typically require human intelligence—such as reasoning, learning, decision-making, and problem-solving. AI technologies allow machines to analyze environmental data, make logical inferences, and respond appropriately. Today, AI is actively used in sectors such as healthcare, education, agriculture, industry, defense, transportation, and finance.
1956: The term "Artificial Intelligence" was first introduced by John McCarthy at the Dartmouth Conference, marking the formal birth of AI as a field.
1950s – 1970s: Rule-based systems and symbolic AI approaches were dominant.
1980s: Expert systems gained popularity with high performance in specific tasks.
1990s – 2000s: Machine Learning (ML) and Artificial Neural Networks started to develop.
Post-2010: Deep learning, big data, and increased computational power revolutionized AI applications. Breakthroughs were observed in areas like image recognition, natural language processing, autonomous systems, and recommendation engines.
Narrow (Weak) AI: Systems designed for specific tasks with limited capabilities (e.g., voice assistants, spam filters).
General (Strong) AI: Aimed to perform any intellectual task that a human can do (still under development).
Superintelligent AI: Hypothetical systems that surpass human intelligence (currently theoretical).
Diagnostic systems in healthcare
Crop monitoring and prediction in agriculture
Automation in industrial systems
Personalized learning in education
Autonomous vehicles in transportation
Natural Language Processing (NLP)
Image and facial recognition
Cybersecurity and risk analysis
At Tokat Gaziosmanpaşa University, various activities in artificial intelligence are supported through undergraduate and graduate curricula, research projects, academic publications, and international collaborations. The Coordination Office for Artificial Intelligence and Digital Transformation plays a key role in promoting AI applications university-wide and fosters interdisciplinary projects.
Machine Learning
Deep Learning
Artificial Neural Networks
Data Mining
Big Data
Algorithm and Modeling