Artificial Intelligence Gen AI Gen AI Quiz Quiz Gen AI Medium Level Quiz 4 Data AI Admin October 10, 2024 Welcome to the Generative AI Medium Level Quiz 4! 🤖This quiz challenges your understanding of advanced generative AI concepts, covering topics like diffusion models, autoregressive models, and transformers. Get ready to put your skills to the test. ⏰ Time’s Up!The quiz is now over, and your responses have been submitted. Let’s see how well you’ve mastered medium-level Generative AI concepts! Generative AI Medium Level Quiz 4 This is a medium-level quiz designed to assess your knowledge of Generative AI, including GANs, VAEs, diffusion models, and transformer architectures. The quiz contains 10 questions, some of which have multiple correct answers. Dive into these advanced concepts and see how well you grasp the intricacies of Generative AI 1 / 10 Which of the following methods can improve the quality of text generated by a transformer model like GPT? Using beam search instead of greedy decoding Reducing the number of training epochs Fine-tuning on a domain-specific dataset Adding positional encoding to the input 2 / 10 In autoregressive models, the next token is generated by conditioning only on the preceding token. False True 3 / 10 What is the role of the "latent space" in Variational Autoencoders (VAE)? It represents a compressed, continuous space of the input data It reduces overfitting by regularizing the model It generates labels for classification It helps in generating adversarial examples 4 / 10 Which of the following loss functions is commonly used in training Variational Autoencoders (VAEs)? Cross-entropy loss Wasserstein loss Mean squared error (MSE) Kullback–Leibler (KL) divergence 5 / 10 What is the key advantage of using diffusion models over GANs for generative tasks? Diffusion models produce higher resolution outputs GANs can only generate text, not images Diffusion models avoid the mode collapse problem Diffusion models use RNNs instead of CNNs 6 / 10 Which of the following describes the relationship between GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers)? BERT generates text while GPT is used for text classification GPT is autoregressive while BERT is bidirectional BERT is used in sequence-to-sequence tasks, whereas GPT is used for sentiment analysis GPT uses the transformer encoder and BERT uses the transformer decoder 7 / 10 In transformer-based generative models, the self-attention mechanism helps the model attend to all tokens in the sequence simultaneously. False True 8 / 10 In conditional GANs, the generator receives both random noise and the class label as inputs to condition the generated output. False True 9 / 10 Which of the following is a challenge specific to diffusion models in generative AI? Difficulty in learning the latent space Reverse noise sampling Slow sampling speed Mode collapse 10 / 10 Which of the following techniques can help stabilize the training of Generative Adversarial Networks (GANs)? Gradient clipping Batch normalization Spectral normalization Adding noise to the inputs Your score isThe average score is 0% 0% Restart quiz Share this… Whatsapp Linkedin Facebook Twitter Gmail Related Tags: Gen AI, Gen AI Quiz, Quiz Continue Reading Previous Gen AI Basics Quiz 3Next Deep Learning Medium Quiz 4 More Stories Databases Quiz Quiz Databases Medium-level quiz 6 Pradip Devkar October 15, 2024 Artificial Intelligence Deep Learning Gen AI Natural Language Processing Bidirectional LSTMs: Enhanced Text Generation better than LSTM Data AI Admin October 14, 2024 Artificial Intelligence Deep Learning Gen AI Natural Language Processing Text Generation Made Easy with LSTM: A Comprehensive Guide for Beginners Data AI Admin October 14, 2024 Leave a Reply Cancel replyYou must be logged in to post a comment.
