Artificial Intelligence (AI) is a technology aimed at simulating certain components of human intelligence through computers or machines. In its simplest form, AI enables machines to perform cognitive functions unique to humans, such as learning, problem-solving, and decision-making. The field encompasses multiple disciplines, including computer science, mathematics, philosophy, linguistics, and psychology, all of which contribute to the advancement of AI technologies. Key Concepts in Artificial Intelligence Since the introduction of AI into our lives, many new concepts have emerged. These concepts are designed both to facilitate our daily lives and to enhance efficiency in professional and academic fields. Although some of these terms may seem complex, we have summarized the fundamental points for you below:
  • Machine Learning (ML): The ability of machines to improve themselves using data and achieve a certain level of performance. Machine learning is the most widely used subfield of AI.
  • Deep Learning: A subfield of machine learning that processes large amounts of data using neural networks, allowing for more complex inferences.
  • Natural Language Processing (NLP): AI technology used to understand and generate text and speech data. Chatbots and language translation systems are examples of this.
  • Knowledge Graphs: Visual representations of relationships between data and information. Knowledge graphs are used in a wide range of applications, from search engines to business intelligence.
  • Autonomous Systems: Systems capable of making decisions independently and adapting to their environment. Autonomous vehicles are a striking example of this concept.
  • Augmented Reality (AR): A technology that integrates digital information into real-world environments. AI-powered augmented reality applications enhance accuracy and usability.
  • Artificial Neural Networks (ANNs): Mathematical models inspired by neural networks in the human brain, used to model and process data. Deep learning techniques are built upon these structures.
  • Fuzzy Logic: An AI technique that operates with imprecise or uncertain data. It is commonly used in areas where uncertainty is prevalent in real-world applications.
  • Natural Language Query (NLQ): A technology that enables users to ask questions in natural language and receive meaningful responses. Frequently used in database queries.
  • Symbolic and Connectionist Approaches: Two fundamental approaches to information processing in AI. The symbolic approach is logic-based, while the connectionist approach relies on artificial neural networks.

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