The first artificial intelligence (AI) projects were developed in the 1950s and 1960s, and focused on creating simple programs that could mimic basic human cognitive functions such as learning and problem-solving.
One of the first AI projects was the Logic Theorist, developed by Allen Newell and Herbert Simon in 1955.
Logic Theorist

It was one of the first AI programs to be developed and was designed to mimic the problem-solving abilities of a human logician.
The Logic Theorist was able to prove theorems in symbolic logic and was able to solve problems in propositional and predicate logic. It was able to do this by searching through a large number of possible solutions and selecting the one that best fit the constraints of the problem.
The Logic Theorist was a significant achievement in the field of AI because it demonstrated that it was possible to create a program that could solve complex logical problems using a set of rules and a search algorithm. It also showed that it was possible to encode knowledge in a computer program and use it to reason and solve problems.
The Logic Theorist was an important influence on the development of other AI programs and helped to lay the foundation for the development of more advanced AI systems in the following decades. It also contributed to the development of the field of artificial intelligence as a whole and helped to establish it as a serious area of study and research.
GPS

Another early AI project was the General Problem Solver (GPS), developed by Newell and Simon in 1957. It was one of the first AI programs to be developed and was designed to be a general-purpose problem-solver that could find solutions to a wide variety of problems.
GPS was designed to work by searching through a large number of possible solutions and selecting the one that best fit the constraints of the problem. It used a set of heuristics, or rules of thumb, to guide its search and was able to solve a wide range of problems, including puzzles, logic problems, and mathematical equations.
GPS was a significant achievement in the field of AI because it demonstrated that it was possible to create a program that could solve complex problems using a set of rules and a search algorithm. It also helped to establish the field of artificial intelligence as a serious area of study and research.
While GPS was a promising early AI project, it had several limitations and was not able to solve all problems. It was also quite resource-intensive, as it required a large amount of computing power to run. Despite these limitations, GPS was an important influence on the development of other AI programs and helped to pave the way for the development of more advanced AI systems in the following decades.
ELIZA

Other early AI projects included ELIZA, it was a natural language processing program developed by Joseph Weizenbaum in 1966. It was one of the first AI programs to be developed and was designed to mimic human conversation by using a set of rules and patterns to generate responses to user input.
ELIZA was designed to simulate a therapist and was able to carry on a conversation with a user by asking questions and responding to the user’s answers. It used a set of rules and patterns to recognize key words and phrases in the user’s input and generate appropriate responses.
ELIZA was able to engage in a surprisingly realistic conversation with users and was able to convincingly mimic a human therapist. It was able to do this by using simple language processing techniques and a set of rules and patterns to recognize and respond to user input.
ELIZA was a pioneering AI project that demonstrated the potential of natural language processing and helped to establish the field of artificial intelligence as a serious area of study and research. It also influenced the development of other AI programs and helped to pave the way for the development of more advanced natural language processing systems in the following decades.
These early AI projects laid the foundation for the development of more advanced AI systems in the following decades, and many of the principles and techniques developed in these early projects are still used in modern AI research and development.