LESSON 1 - Introduction Flashcards
What is the focus of neural computation in AI?
Neural computation focuses on brain-inspired artificial intelligence, mimicking human intelligence and understanding human brain and behavior.
Who is considered the father of AI, and what was his perspective on AI in the 1950s?
Turing is considered the father of AI. In the 1950s, he viewed AI as mimicking intelligence, highlighting the fundamental difference between engineering and cognitive science perspectives.
What is the Hype cycle for AI, and when did it experience a strong peak?
The Hype cycle for AI saw a strong peak in the mid-1980s, with high expectations followed by a return to the labs. Today, there is another strong peak.
What is the difference between the symbolic and neural computing approaches in AI?
Symbolic AI involves structures representing symbols manipulated by rules, similar to coding. Neural computing asserts that mimicking human cognitive intelligence requires simulating neural networks, emphasizing brain-like approaches.
How does symbolic AI operate, and what is its focus?
Symbolic AI operates with structures representing symbols manipulated by rules, akin to coding or programming. Its focus is on defining variables and implementing rules for deductive and inductive reasoning.
What is the role of machine learning in AI, and is it synonymous with artificial neural networks?
Machine learning involves learning from experience. While artificial neural networks are crucial to machine learning, they are not synonymous. Machine learning encompasses various methods, some of which are simple and not necessarily neural network-based.
How does the cognitive science perspective differ from the engineering perspective in AI?
In the cognitive science perspective, the goal is to reproduce aspects of human intelligence in a machine, mimicking human cognition. In the engineering perspective, the emphasis is on the machine’s intelligent behavior, with less concern about the internal mechanisms.
What is the main idea behind the neural computing approach in AI?
The neural computing approach asserts that it’s challenging to write a computer program mimicking human cognitive intelligence directly. Instead, it suggests using computers to simulate neural networks, resembling the structure and function of the human brain.
What is the significance of the mid-1980s in the Hype cycle for AI?
In the mid-1980s, there was a peak of expectations in the Hype cycle for AI, followed by a period where AI research returned to the labs. Today, there is another strong peak of interest and development in AI.
How does Brain-like AI view the role of a computer in implementing intelligence?
In Brain-like AI, the computer serves as a medium to implement intelligence, with the code focusing on simulating and implementing neural networks. The emphasis is on replicating the brain’s functionality.
What is the relationship between machine learning and artificial neural networks?
While artificial neural networks are a vital component of machine learning, machine learning as a whole includes various methods beyond neural networks. It involves learning from experience and adapting behavior based on data.
How does symbolic AI represent information, and what does it manipulate?
Symbolic AI represents information using structures that manipulate symbols. It involves defining variables and employing rules, similar to coding or programming, with a focus on symbolic representation and manipulation.
Is artificial neural networks the only method in machine learning, and what characterizes machine learning?
No, artificial neural networks are just one method in machine learning. Machine learning encompasses various approaches, all centered around the idea of learning from experience to improve performance.
