Crack the Code: IT Interview Questions and Answers - Programming Language Institute

Programming practice questions and answer

Artificial Intelligence.

 
1

Question- What is Artificial Intelligence (AI)?



Answer- AI is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction. AI enables machines to perform tasks that would typically require human intelligence, like problem-solving, decision-making, and pattern recognition.

2

Question- What are the main types of AI?



Answer- AI is often categorized into three types:

  • Artificial Narrow Intelligence (ANI): AI specialized in a single task (e.g., image recognition, recommendation systems).
  • Artificial General Intelligence (AGI): Hypothetical AI that can perform any intellectual task a human can.
  • Artificial Superintelligence (ASI): Hypothetical AI that surpasses human intelligence in all aspects.

3

Question- What is machine learning, and how is it related to AI?



Answer- Machine Learning (ML) is a subset of AI that enables systems to learn and improve from experience without explicit programming. ML focuses on creating algorithms that can recognize patterns, make predictions, and enhance performance over time based on data.

4

Question- What is the difference between supervised, unsupervised, and reinforcement learning?



Answer-

  • Supervised Learning: Uses labeled data to train models, where input-output pairs are known (e.g., classification, regression).
  • Unsupervised Learning: Uses unlabeled data to find patterns or groupings (e.g., clustering, association).
  • Reinforcement Learning: Trains agents through rewards and punishments for taking actions in an environment to maximize cumulative rewards.

    • 5

    Question- What are neural networks, and how do they work?



    Answer- Neural networks are computational models inspired by the human brain. They consist of layers of interconnected nodes (neurons) that process input data, detect patterns, and learn from data by adjusting weights based on error minimization, typically using algorithms like backpropagation.

    6

    Question- What is deep learning, and how is it different from traditional machine learning?



    Answer- Deep learning is a subset of ML focused on neural networks with multiple layers (deep neural networks). Unlike traditional ML, which may rely on feature engineering, deep learning models can automatically extract high-level features from raw data, making it effective for complex tasks like image recognition and natural language processing.

    7

    Question- What is natural language processing (NLP)?



    Answer- NLP is a branch of AI that enables machines to understand, interpret, and generate human language. Applications of NLP include language translation, sentiment analysis, speech recognition, and chatbots.

    8

    Question- What is computer vision, and how is it used in AI?



    Answer- Computer vision is a field of AI that enables machines to interpret and make decisions based on visual data, such as images or videos. Applications include facial recognition, object detection, autonomous vehicles, and medical image analysis.

    9

    Question- What is the Turing Test, and why is it important in AI?



    Answer- The Turing Test, proposed by Alan Turing, assesses a machine’s ability to exhibit behavior indistinguishable from a human. If a machine can converse with a human without the human realizing it’s a machine, it is said to have passed the test. It’s a benchmark for evaluating machine intelligence.

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