Uncategorized GenAI Screen Test by mfh.officials@gmail.com Jan 7, 2025 0 Comment Generative AI (Gen AI) Screening Test 1 / 20 What is the purpose of "diffusion models" in Generative AI? To classify data To optimize hyperparameters To reduce training time To generate high-quality images by reversing noise 2 / 20 Which of the following technologies powers ChatGPT? Reinforcement Learning Transformers Long Short-Term Memory (LSTM) Convolutional Networks 3 / 20 Which technique combines supervised and unsupervised learning for training Generative AI? Adversarial training Reinforcement learning Zero-shot learning Semi-supervised learning 4 / 20 Which of the following frameworks is widely used for developing Generative AI models? TensorFlow PyTorch JAX All of the above 5 / 20 What is a common use case for Variational Autoencoders (VAEs)? Predictive modeling Dimensionality reduction and generative tasks Classification tasks Decision tree optimization 6 / 20 Which neural network architecture is commonly used in Generative AI? Decision Trees Recurrent Neural Networks (RNNs) Generative Adversarial Networks (GANs) Convolutional Neural Networks (CNNs) 7 / 20 What is the main advantage of pre-trained Generative AI models? They eliminate the need for labeled data They generalize better to new tasks They require no further training They reduce computational resources needed for fine-tuning 8 / 20 What is the main role of the "discriminator" in a GAN? To optimize the learning rate To classify real and fake data To reduce noise in the input To generate synthetic data 9 / 20 What does "latent space" refer to in Generative AI? A reduced-dimensional representation of input data A memory buffer for AI systems A storage area for pre-trained models A repository for training data 10 / 20 What is "prompt engineering" in the context of Generative AI? Designing the neural network architecture Optimizing system performance Tuning hyperparameters for training Crafting inputs to guide AI output 11 / 20 Which of the following is a real-world application of Generative AI? Fraud detection Customer segmentation Image synthesis and text generation Predictive analytics 12 / 20 What is the role of attention mechanisms in transformer-based models? To simplify architecture design To increase training speed To reduce the model size To focus on relevant parts of the input sequence 13 / 20 What is "zero-shot learning" in Generative AI? Removing overfitting during training Reducing model training time to zero Training models without any labeled data Generating output for unseen tasks without specific training 14 / 20 Which of the following is a major ethical concern with Generative AI? Limited use cases Lack of scalability High computational cost Biased or harmful content generation 15 / 20 What does "fine-tuning" mean in Generative AI? Training a new model from scratch Simplifying the dataset Adjusting a pre-trained model for specific tasks Increasing the number of layers in a model 16 / 20 Which loss function is commonly used in training GANs? Cross-Entropy Loss Binary Cross-Entropy Loss Hinge Loss Mean Squared Error (MSE) 17 / 20 Which of the following is NOT an example of Generative AI? MidJourney Power BI DALL·E ChatGPT 18 / 20 What does the "T" in GPT stand for? Training Translation Transfer Transformer 19 / 20 What is Generative AI primarily used for? Creating new content, such as images, text, or music Data analysis and visualization Extracting insights from structured data Monitoring system performance 20 / 20 What is a key component of a Generative Adversarial Network (GAN)? A feature extractor and classifier An encoder and a decoder A trainer and a learner A discriminator and a generator Your score isThe average score is 60% 0% Restart quiz
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