Page 4 - AI CX White Paper by Mark Daley

The following definitions are questions and answers asked of ChatGPT by DaleyPros.
Define Artificial Intelligence:
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. It is a branch of computer science that aims to create systems that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing images and speech, making decisions and solving problems.
There are several types of AI, including:
• Reactive machines: These systems can only respond to the current situation; they don’t have the ability to remember past events or use previous experiences to inform their actions.
• Limited memory: These systems can remember past event and use them to inform their actions, but they don’t have the ability to form general concepts.
• Theory of mind: This type of AI system is able to understand the mental states of other agents and respond accordingly.
• Self-aware: This type of AI system has a sense of self, and understanding of its own mental states and the ability to reflect on its own experiences.
AI systems can be trained using techniques from machine learning which involves feeding substantial amounts of data into a system and allowing it to learn and improve over time. AI is being used in a variety of applications such as natural language processing, computer vision, robotics, self-driving cars and more.
What is the history of Artificial Intelligence?
The history of Artificial Intelligence (AI) can be traced back to ancient Greece, where stories of automatons, of self-operating machines can be found in myths and legends. However, the modern field of AI as we know it today began in the 1950s, with the Dartmouth Conference which brought together a group of researchers to discuss the possibility of creating, ‘thinking machines.’ This marked the birth of AI as a scientific discipline. Early AI research focused on developing programs that could perform specific tasks such as playing chess or solving a mathematical problem. In the 1960s and 1970s, AI research became more theoretical, with what development of the concept of ‘expert systems’ and the exploration of knowledge representation and reasoning. However, progress in AI slowed in the 1980s due to a lack of funding and the realization that some of the initial goals of AI were more difficult to achieve than initially thought. In recent years, there has been a resurgence of interest in AI, driven by advancements in areas such as machine learning, big data, and computational power. This has led to the development of practical applications of AI, such as self-driving cars, virtual personal assistants, and speech recognition.