Machine Learning | MCQs

Explanation

In the fifth generation of computers, artificial intelligence was used.

Artificial Intelligence came into use in fifth-generation computing devices.

Fifth-generation computing devices were faster and more efficient.

Using high-speed logic, and memory chips help in using Artificial Intelligence.

The period of fifth-generation was 1980-onwards. ULSI-based microprocessors were used.

****

Explanation

Machine learning is a subset of artificial intelligence.

Explanation

The fifth generation of computers focuses on Artificial Intelligence (AI).

These computers use advanced technologies such as natural language processing, biochips, and expert systems.

Explanation

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on enabling machines to understand, interpret, and respond to human language in a meaningful way.

Explanation

Artificial intelligence is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans.

This is used in 5th generation computers

Explanation

Explanation

• Fuzzy logic is the AI that mimics human intuition by handling vague information.
• It allows machines to work with partial truths, thus making more nuanced decisions than traditional binary logic permits.

Explanation

There are two (universal and existential) types of quantification available in Artificial intelligence.

Explanation

• The "imitation game" was originally conceptualized and named by its creator, Alan Turing, as a means to assess a machine's ability to exhibit intelligent behavior indistinguishable from that of a human.
• The test involves a human evaluator engaging in natural language conversations with both a human and a machine, without knowing which is which. If the evaluator cannot reliably distinguish between the human and the machine based on the conversation, the machine is considered to have passed the Turing Test.

Explanation

• Data mining refers to the process of automatically discovering patterns, relationships, and insights from large datasets, using various machine learning and statistical techniques.
• It involves analyzing and extracting valuable knowledge or patterns from large databases, which can be used to make informed decisions or predictions.