The first attempts to create robots that could replace human intelligence were in the 1950s, when the fundamentals of artificial intelligence became eager to see.The 1956 Dartmouth Conference, in which pioneers such as John McCarthy, Marvin Minsky, and Alan Newell explored the possibility of creating intelligent machines, is often considered the beginning of artificial intelligence. Currently, AI systems that rely on rules and logic to solve problems are the main focus of AI research. The General Problem Solver (GPS), developed by Newell and Simon in 1957, was an early achievement that showed computers could use logical rules to solve complex problems. Artificial intelligence was on the rise in the 1980s with the advent of artificial intelligence. To solve complex problems, these machines use logical ideas and draw on human expertise.It is used in many fields, including professionals, engineering, finance, and medicine. Despite being effective in some areas, experts find it difficult to be proactive and fail to learn from new information. The 1990s saw a major shift in artificial intelligence research with the return of machine learning, particularly neural networks. The researchers set out to examine how neural networks could mimic the way the human brain learns and adapts. However, the lack of computer capabilities and large data sets hindered their development.The emergence of big data and powerful studies in the early 2000s encouraged the development of intelligence. Due to the availability of more data and more efficient algorithms, deep learning is becoming the main method of machine learning. Based on the process of tying nodes, deep neural networks are good at complex tasks such as image recognition and natural language processing.

 Health: With improved diagnosis, rapid drug discovery and improved patient care, artificial intelligence is revolutionizing the economy. AI-powered robots can assist with missions and dangerous tasks, while machine learning algorithms can analyze medical images to identify liver diseases.In addition, AI technology can be used to monitor public health, predict outbreaks and aid in self-healing.

 Finance: The financial industry has embraced artificial intelligence to increase efficiency, manage risk and deliver personalized services. Big financial data can be analyzed using AI-powered algorithms to detect patterns, predict market movements and improve investment planning. Chatbots and virtual assistants can improve the customer experience by providing real-time support and customized financial advice.

 Transportation: Autonomous driving and self-driving cars are one of the most important applications of artificial intelligence in the transportation industry.These innovations can improve mobility, reduce congestion and improve road safety. AI-driven solutions can improve supply chain and logistics processes and make shipping more efficient.

Manufacturing: AI is revolutionizing industrial sectors by enabling automation, quality control and predictive maintenance. Intelligent robots and AI-powered systems perform complex tasks effectively and efficiently, increasing efficiency and reducing costs. Artificial Intelligence will also make it easier to build "smart factories" with connected machines that increase productivity.

Education :AI is transforming education by providing intelligent, personalized learning experiences and management functions. Adaptive learning platforms use artificial intelligence to identify students' strengths and weaknesses and then adjust learning content accordingly. Virtual assistants and chatbots can facilitate the learning process by providing quick guidance and feedback to students.

The rise of artificial intelligence holds many promises for society. It can increase productivity, improve decision making and open new business.AI innovation has the power to solve complex problems, improve scientific results and transform entire industries. However, the rapid development of artificial intelligence brings with it problems.

Ethical decisions: AI raises ethical questions about responsibility, objectivity, and privacy. It is necessary to ensure that artificial intelligence is open, honest and based on human vision. Appropriate rules and ethics must be established to monitor AI use and protect individual rights.

Employee disruption: As automation replaces monotonous tasks, it can cause disruptions to some employees' work. But AI is opening up new jobs for people who value human creativity, problem solving, and emotional intelligence. A seamless transition requires support and support activities to prepare employees.

Data privacy and security: Artificial intelligence relies on data, which raises the issue of data security and privacy. Personal information and sensitive information must be protected to maintain public trust.It is important to strike a balance between information use and privacy.

Human-Machine Collaboration: The future of harmony between AI and humans is now. Collaborative models that artificial intelligence supports rather than change people's decision-making can empower people and produce better solutions.

The rise of intelligence is a new era of progress and innovation. Artificial intelligence is changing all industries, from healthcare to finance, transportation to education, and offers unprecedented opportunities.Empowering AI requires a solid understanding of its capabilities, ethical concerns, and potential challenges. By supporting the evolution of the role of artificial intelligence, we can use its power to create a future where humans and machines augment each other for a better life together.