Computers, Information and Communication Technology: RAS Prelims MCQs
200 RAS Prelims MCQs on computers, information and communication technology cover the generations of computers, the parts of the CPU, memory types and networking. The first and second generations, analog computers, the control unit, cache and RAM, the memory hierarchy and the SSD are asked as definitions and sequences, with the explanations giving the reason for each design.
Practice questions based on the RPSC RAS Prelims syllabus. They follow the exam pattern but are not past-paper questions.
Showing 101–110 of 200 questions
I. Supervised learning uses labeled datasets to train algorithms.
II. Unsupervised learning looks for undetected patterns in unlabeled data.
III. Reinforcement learning trains algorithms via a reward and punishment mechanism.
IV. Deep learning strictly avoids the use of artificial neural networks.
Which of the above statement(s) is/are correct?
Explanation
Machine learning encompasses several distinct approaches. Supervised learning uses labeled data for training, while unsupervised learning identifies patterns in unlabeled data. Reinforcement learning utilizes a system of rewards and punishments to guide behavior. Importantly, deep learning relies heavily on artificial neural networks to process information, making the claim that it avoids their use factually incorrect within the context of computer science.Explanation
Artificial Neural Networks are computational models inspired by the structure of the human brain, consisting of interconnected layers of nodes. They are exceptionally effective at identifying complex patterns, making them a cornerstone of modern image and speech recognition technologies. Deep Learning specifically uses networks with many hidden layers to improve accuracy, contradicting the idea that these models are incapable of.Explanation
Natural Language Processing is the branch of artificial intelligence that focuses on the interaction between computers and human language. It enables machines to understand, interpret, and generate human-like text and speech. This technology is the core component of virtual assistants and chatbots, allowing them to process voice commands and provide meaningful responses, which is essential for modern human-computer interaction.Explanation
The Turing Test was designed to determine if a machine could exhibit intelligent behavior indistinguishable from that of a human. In this test, a human judge engages in natural language conversations with both a human and a machine. If the judge cannot reliably tell them apart, the machine is said to have passed. It remains a foundational concept in the.Explanation
Artificial intelligence is divided into various domains with specific practical applications. Computer vision enables machines to interpret and understand visual information from the world, directly powering technologies like facial recognition. In contrast, natural language processing handles text and speech, while reinforcement learning is often used for complex decision-making in gaming or robotics. Matching these domains with their correct applications.Statement I: Generative AI refers to algorithms capable of creating new text, images, or audio based on training data.
Statement II: ChatGPT and DALL-E are examples of Generative AI models.
Which of the above statement(s) is/are correct?
Explanation
Generative AI refers to advanced algorithms that can create entirely new content, including text, images, and audio, by learning from massive datasets. Prominent examples like ChatGPT and DALL-E demonstrate the power of these models to produce human-like responses and creative visuals. This technology represents a significant shift in AI, moving from simple data analysis to the active creation of.| AI Term | Definition |
|---|---|
| A. Algorithm | i. The collection of data used to teach an AI |
| B. Dataset | ii. The process of an AI applying learned knowledge to new data |
| C. Training | iii. A set of rules or instructions given to an AI |
| D. Inference | iv. The phase where an AI learns patterns from data |
Explanation
Understanding AI requires defining its core components. Algorithms provide the rules for processing, while datasets supply the information used for learning. Training is the active phase where the AI identifies patterns, and inference is the application of that learned knowledge to new situations. Together, these elements form the lifecycle of an AI system, from its initial development to its.Explanation
Artificial Intelligence encompasses fields like machine learning, robotics, and natural language processing, all focused on creating intelligent systems. These areas work together to enable machines to learn, move, and communicate. Relational database normalization, however, is a data management technique used to organize tables to reduce redundancy and improve integrity. While useful for storing data, it is not a core component.Explanation
Expert systems are specialized AI programs designed to solve complex problems by mimicking the decision-making ability of a human expert in a specific field. They utilize a knowledge base and an inference engine to provide advice or diagnoses, such as in medical or legal settings. Unlike general-purpose chatbots, expert systems are deeply focused on a single domain to.Answer key for these questions
| Q | Correct answer |
|---|---|
| 101 | (c) AI is the overarching concept, ML is a subset of AI, and DL is a specialized subset of ML. |
| 102 | (a) I, II, and III only |
| 103 | (d) They cannot be used for pattern recognition or image processing. |
| 104 | (a) Natural Language Processing (NLP) |
| 105 | (c) Measure human-like machine intelligence |
| 106 | (a) Computer Vision - Facial recognition systems |
| 107 | (a) Both Statement I and II are correct |
| 108 | (a) A-iii, B-i, C-iv, D-ii |
| 109 | (c) Relational Database Normalization |
| 110 | (d) Expert Systems |
Key facts from Computers, Information and Communication Technology
- First-generation computers used vacuum tubes; the second generation moved to transistors.
- Analog computers work on continuous variable data rather than discrete binary data.
- The Control Unit directs and coordinates the operations of the CPU.
- Cache memory gives the fastest access to the CPU; the hierarchy from fastest to slowest is registers, cache, RAM and magnetic disk.
- Adding more RAM to a system with many page faults reduces its dependence on virtual memory.
- An SSD differs from an HDD by the use of NAND flash memory.
Frequently asked questions
How many RAS Prelims practice MCQs are there on Computers, Information and Communication Technology?
This page has 200 practice MCQs on Computers, Information and Communication Technology (Science and Technology). Each has the correct answer, and most have an explanation.
What was used in first-generation computers?
Vacuum tubes. They were large, used much power and produced heat. The second generation replaced them with transistors, which were smaller, faster and more reliable, and later generations moved to integrated circuits and microprocessors.
Which memory is fastest for the CPU?
Cache memory, apart from the registers inside the CPU. The memory hierarchy from fastest to slowest is registers, cache, RAM and magnetic disk, and capacity increases as speed falls.
How does an SSD differ from an HDD?
An SSD stores data in NAND flash memory with no moving parts, while a hard disk drive uses spinning magnetic platters. As a result an SSD is faster, quieter and more resistant to shock.