Gen AI Course in Hyderabad   Generative AI Course in Hyderabad
                     Generative AI:
Interview questions 
and answers
+919989971070  
www.visualpath.in
Slide Title
• When preparing for a Generative AI interview, it is 
essential to cover a broad range of topics that 
demonstrate your understanding of the field. Below 
are some common Generative AI interview questions 
and their answers, designed to help you prepare 
effectively.
www.visualpath.in
Basic Questions
• 1. What is Generative AI?
• Generative AI refers to a subset of artificial intelligence techniques that focus on generating new 
content based on existing data. Unlike traditional AI, which typically focuses on analyzing and 
predicting data, generative AI creates new data in the form of text, images, music, or other 
media types. Examples include text completion by GPT-3 and image generation by DALL-E.
•
2. How does Generative AI differ from traditional AI?
• Traditional AI is primarily concerned with tasks like classification, regression, and pattern 
recognition. Generative AI, on the other hand, focuses on creating new content. While 
traditional AI models might predict the next word in a sentence, generative AI models can 
generate entire paragraphs of coherent text, design realistic images, or compose music.
www.visualpath.in
 What are some popular Generative AI models?
Some popular Generative AI models include:
• GPT-3 (Generative Pre-trained Transformer 3): A powerful text generation 
model developed by OpenAI.
• DALL-E: An AI model that creates images from textual descriptions.
• StyleGAN: A model for generating high-quality images, often used in creative 
arts and design.
• BERT (Bidirectional Encoder Representations from Transformers): Although 
primarily for understanding, it's adapted for generating text in some 
applications. www.visualpath.in
Intermediate Questions
• 4. What is the difference between a Generator and a Discriminator in GANs 
(Generative Adversarial Networks)?
• In GANs, the Generator creates synthetic data resembling the real dataset, while 
the Discriminator evaluates the authenticity of the generated data. The 
Generator aims to improve its output to trick the Discriminator, which, in turn, 
becomes better at distinguishing real data from fake. This adversarial process 
continues until the Generator produces data that the Discriminator finds 
indistinguishable from real data.
www.visualpath.in
• 5. Explain the concept of latent space in Generative Models.
• Latent space is an abstract representation of input data in a 
reduced dimension. In Generative Models, data is encoded 
into this space, where the model learns meaningful patterns 
and relationships. From this space, new data can be 
generated by sampling points and decoding them back to the 
original data format, allowing for creative and diverse content 
generation.
www.visualpath.in
• 6. What are Variational Autoencoders (VAEs)? How are they 
different from regular Autoencoders?
• Variational Autoencoders (VAEs) are a type of generative model 
that introduce a probabilistic approach to generating new data. 
Unlike regular Autoencoders, which focus on encoding and 
reconstructing input data, VAEs encode data into a latent space 
defined by a probability distribution. This allows VAEs to generate 
new samples by sampling from this distribution, offering a 
continuous and more controlled output spacew. ww.visualpath.in
• 7. How would you implement a GAN to generate images?
• To implement a GAN:
• Define the Generator and Discriminator Networks: Design neural networks for 
both components.
• Set Up the Adversarial Training Loop: Alternate training between the 
Generator and Discriminator.
• Loss Function: Use adversarial loss to optimize both networks, guiding the 
Generator to improve its output.
• Training Process: Gradually refine the Generator's output through epochs until 
desired image quality is achieved. www.visualpath.in
• 8. What role does Generative AI play in deepfake 
technology?
• Generative AI is pivotal in deepfake technology, creating 
highly realistic but potentially deceptive content. By 
manipulating audio, video, and images, deepfakes pose 
ethical challenges, particularly in misinformation and privacy. 
Addressing these concerns requires advanced detection 
methods and regulatory frameworks to enswurwew e.tvhiiscuaal lupsaet.h.in
CONTACT
For More Information About 
AZURE DEVOPS CERTIFICATION
 ONLINE TRAINING
Address:- Flat no: 205, 2nd Floor                                       
           
                                        Nilagiri Block, Aditya Enclave,
                               Ameerpet, Hyderabad-16
Ph No : +91-9989971070
     Visit : www.visualpath.in
      E-Mail  : [email protected]
THANK YOU
Visit: www.visualpath.in