Most asked questions for Generative AI

Ever wondered how AI writes captivating stories/poems, creates new images, or even composes music? dive into fascinating world of Generative AI as we unravel the most frequently asked questions, from its fundamental workings to its potential impact on various industries. Whether you're an AI enthusiast, a curious learner, or a business leader seeking innovative solutions, this guide will equip you with the knowledge to navigate the exciting landscape of Generative AI. Let's discuss these most asked questions on Generative AI with explanations.

Part Two of Gen AI questions and answers.

Part Three of Gen AI question and Answers.

Stay tuned for more.


1. Determine the statement is True or False: Large Language Models are a subset of Foundation Models.

    a) FALSE
    b) TRUE  

Answer: b) True

Explanation: 

Foundation Models are nothing but large machine learning models which are trained on a huge amount of unlabeled data. The aim of  such a training is to teach general representations of language, images etc. to models. Large Language Models (LLMs) are a specific type of foundation model focused on understanding and generating human language.


2. Which of the following is NOT a type of Generative AI model? 

    a) Generative Adversarial Network (GAN) 
    b) Transformer 
    c) Autoencoder 
    d) Decision Tree

Answer: d) Decision Tree

Explanation: 

A model will be categorized under Generative AI if it creates new data based on the existing data. Decision trees are used for classification tasks, but they will not be considered generative as they do not create new data. GANs (Generative Adversarial Network), transformers, and autoencoders these are types of generative AI models which can generate new content like images, text, music.


3. Pre-Trained Multi Task Generative Al Models are called as

    a) Machine Learning Models 
    b) Deep Learning Models
    c) Foundation Models
    d) All are correct

Answer: c) Foundation Models

Explanation: 

Foundation Models are pre-trained on large dataset of unlabeled data which helps it to learn general patterns and representations. Being trained on the large dataset the foundational model, it can be used for the multitude of tasks like such as generating text, images, or code. These models can be later trained for the specific tasks which does not require it to train from the scratch.


4. What is the primary function of a Generative Adversarial Network (GAN)? 

    a) Classify data into predefined categories 
    b) Translate conversations, regular text from one language to another 
    c) Generate realistic images, videos, or audio 
    d) Detect anomalies in data

Answer: c) Generate realistic images, videos, or audio

Explanation: 

Generative Adversarial Networks (GAN's) primarily consist of two neural networks as it's building blocks: 

  1. generator :- it creates new data.
  2. discriminator :- it evaluates the generated data for authenticity and provides feedback to generator.

Through a tighter integration between generator and discriminator, GANs learn to generate highly realistic content such as images, videos, or audio. 


5. You need to create a chatbot for your website that can answer customer queries in real time. Which Al approach would you use?

    a) Machine Learning 
    b) Deep Learning
    c) Data Science
    d) Generative AI

Answer: d) Generative AI

Explanation: 

Generative AI can be helpful to generate new content based on the input from user. It can generate answer text for customer queries, which is required for the application of chatbot. It can be trained to work on the natural language generation required for chatbot functionality. Therefore Generative AI can be a good option for the chatbot creation which will address the customer queries in real time. 

6. What is the purpose of the General Data Protection Regulation (GDPR)?

    a) To ensure the responsible use of Al technologies by normal people.
    b) To ensure the development of Al technologies.
    c) To ensure the use of Al technologies.
    d) To ensure personal data protection and privacy. 

Answer: d) To ensure personal data protection and privacy.

Explanation: 

The General Data Protection Regulation (GDPR) is a European law for safeguarding peoples rights in terms of the personal information. GDPR is not directly connected with AI.


7. BARD, the conversational Al chatbot, is developed by which company?

    a) Google 
    b) Open Al
    c) Amazon
    d) Microsoft

Answer: a) Google 

Explanation: 

Google developed BARD as generative artificial intelligence chatbot. BARD is currently known as Gemini.


8. Which Generative AI model is known for its ability to process and generate text in a human-like manner? 

    a) Recurrent Neural Network (RNN) 
    b) Convolutional Neural Network (CNN)
    c) Transformer 
    d) Boltzmann Machine

Answer: c) Transformer

Explanation: 

Models based on Transformers have revolutionized natural language processing (NLP) tasks as they are able to capture long-range dependencies in text. Example of Transformer architecture is GPT (Generative Pre-trained Transformer). They are widely used for text generation, translation between languages and summarization.


9. Below statement is True or False? 

Artificial intelligence (Al) is the theory and development of computer systems capable of performing tasks that historically requires human intelligence such as recognizing speech, making decisions, and identifying patterns.

    a) TRUE 
    b) FALSE

Answer: a) TRUE 

Explanation: 

Artificial Intelligence are the computer programs that are generated to perform the tasks like Language translation, subtitles generation in the video conference calls, text recognition on vehicle number plates etc. and so on. Artificial intelligence has lot of categories under it such as Natural Language Processing, Generative AI, Machine Learning for the variety of tasks.


10. A news agency wants to use Al to create unique news articles based on a given topic. This is an example for which kind of generative Al use case?

    a) Question and Answers Generation
    b) Content Generation. 
    c) Content Summarization
    d) All the above.

Answer: b) Content Generation. 

Explanation: 

Generative AI models like Chat GPT are capable of generating task based on the given prompt. It can help in copywriting tasks with engaging headings, content full of SEO keywords that will rank well in the search engine results etc. 


11. What are some potential ethical concerns associated with Generative AI? 

    a) Job displacement and automation 
    b) Bias and discrimination in generated content 
    c) Misuse for creating deepfakes and misinformation 
    d) All of the above

Answer: d) All of the above

Explanation: 

Generative AI currently have lot of ethical issues, such as creation of deep-fake content, potential for job losses, biased output generation, unethical use of AI and so on. These issues and concerns needs to be tackled for generation of responsible and ethical AI development.


12. Which of the following is an example of a Generative AI application in the creative arts? 

    a) Automated customer service chatbots 
    b) Fraud detection systems 
    c) Music composition tools 
    d) Inventory management software

Answer: c) Music composition tools

Explanation: 

Generation of the music, creating of artworks and literatures like paintings and poems, writing of engaging stories are the examples of Generative AI applications in the arts field. Gen AI can even help us to write the existing stories in a new and engaging way.


13. Which of the following is a use case for traditional Al?

    a) Generating art from text descriptions
    b) Predicting stock market trends
    c) Translating between languages 
    d) Creating realistic facial images

Answer: c) Translating between languages

Explanation: 

Traditional AI can be used to analyze and predict data patterns based on statistical and machine learning techniques. Among the given options predicting stock market trends is a correct option for the use case for traditional AI.


We have a series of question answer articles in Gen AI listed below.


Feeling curious about a specific Artificial Intelligence topic or Question? Don't hesitate to post your question in a comment below. Our team will be happy to assist you as soon as possible!

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