Give a brief introduction to the Turing test in AI?
Turing test is one of the popular intelligence tests in Artificial intelligence. The Turing test was introduced by Alan Turing in the year 1950. It is a test to determine that if a machine can think like a human or not. According to this test, a computer can only be said to be intelligent if it can mimic human responses under some particular conditions.
In this test, three players are involved, the first player is a computer, the second player is a human responder, and the third player is the human interrogator, and the interrogator needs to find which response is from the machine on the basis of questions and answers.
What is a Depth-first Search Algorithm?
Depth-first search (DFS) is an algorithm that is based on LIFO (last-in, first-out). Since recursion is implemented with LIFO stack data structure, the nodes are in a different order than in BFS. The path is stored in each iteration from root to leaf nodes in a linear fashion with space requirement.
Explain applications of N.L.P?
a. Communication
- Basically, a computer is a medium to communicate with users. Also, to learn a new language we can’t force users. Although, for casual users, it’s most important. Such as Managers and children. As they don’t have time and inclination to learn new skills to learn new interaction skills.
- Basically, in natural language, it’s having a vast store of information. Also, we have to access via computers. Although, we have to generate information constantly. Also, it’s in the form of books, business, and government report.
- Generally, in natural language processing, problems of AI arise in a very clear and explicit form.
- Moreover, there are three major aspects of any natural language understanding theory:
b. Syntax
Basically, we use it to describe the form of the language. Also, grammar is used to specify it. further, we use natural language for the A.I languages of logic and computer programs. Also, these language is more complicated than other formal languages.
c. Semantics
Generally, utterances meaning provided with the of semantics. Although, if we want to build this understanding, general semantic theories exist for it.
d. Pragmatics
Basically, we use this component to explain how the utterances relate to the world.
What are iterative deepening depth-first search algorithms?
In iterative deepening DFS algorithms, the search process of level 1 and 2 takes place. It continues the exploration until it finds the solution. It generates nodes until it finds the goal node and saves the stack of nodes it had created.
What is the inference engine, and why it is used in AI?
In artificial intelligence, the inference engine is the part of an intelligent system that derives new information from the knowledge base by applying some logical rules.
It mainly works in two modes:
Backward Chaining: It begins with the goal and proceeds backward to deduce the facts that support the goal.
Forward Chaining: It starts with known facts, and asserts new facts.
In speech recognition what kind of signal is used?
In speech recognition, Acoustic signal is used to identify a sequence of words.
What are the types of AI?
Artificial intelligence can be divided into different types on the basis of capabilities and functionalities.
Based on Capabilities:
- Weak AI or Narrow AI: Weak AI is capable of performing some dedicated tasks with intelligence. Siri is an example of Weak AI.
- General AI: The intelligent machines that can perform any intellectual task with efficiency as a human.
- Strong AI: It is the hypothetical concept that involves the machine that will be better than humans and will surpass human intelligence.
Based on Functionalities: - Reactive Machines: Purely reactive machines are the basic types of AI. These focus on the present actions and cannot store the previous actions. Example: Deep Blue.
- Limited Memory: As its name suggests, it can store the past data or experience for the limited duration. The self-driving car is an example of such AI types.
- Theory of Mind: It is the advanced AI that is capable of understanding human emotions, people, etc., in the real world.Self-Awareness: Self Awareness AI is the future of Artificial Intelligence that will have their own consciousness, emotions, similar to humans.
Give some disadvantages of Artificial Intelligence?
a. High Cost Its creation requires huge costs as they are very complex machines. Also, repair and maintenance require huge costs.
b. No Replicating Humans As intelligence is believed to be a gift of nature. An ethical argument continues, whether human intelligence is to be replicated or not.
c. Lesser Jobs As we are aware that machines do routine and repeatable tasks much better than humans. Moreover, we use machines instead of humans. As to increase their profitability in businesses.
d. Lack of Personal Connections We can’t rely too much on these machines for educational oversights. That hurt learners more than help.
What is a Partial-Order Plan?
When a plan specifies all the actions you need to perform but specifies the order of the steps only when necessary, it’s called a partial-order plan.
What is Local Search Algorithms?
Basically, it’s Popular Search Algorithms. Also, a prospective solution. Further, moves to a neighboring solution. Moreover, returns a valid solution.
a. Hill-Climbing Search Algorithm
We can start this algorithm with an arbitrary solution to a problem. Also, it’s an iterative algorithm. Hence, the algorithm attempts to better solution by a single element of the solution. Although, we take an incremental change as a new solution. As if the change produces a better solution. Moreover, we have to repeat until there are no further improvements.
b. Local Beam Search Algorithm
In this algorithm, we have to hold k number of states at any given time. In the beginning, we have to generate states randomly.
Moreover, with the objective function, we have to compute successors of these k states. Also, this stop, if any of these successors is the maximum value of the objective function.
Otherwise, we have to put the (initial k states and k number of successors of the states = 2k) states in a pool. Also, a pool is then sorted numerically. Further, we have to select highest k states as new initial states. This process continues until a maximum value is reached.