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Accenture GenaiQuestions & Answers

Practice 126 verified Accenture Genai questions with detailed answers and explanations. Tap any question below to study the full solution — perfect for last-minute Accenture primer and dumps prep.

In a neural network, what does a neuron compute?Which function introduces non-linearity in a neural network?Which of the following is NOT a layer type in a typical neural network?Which application of ML is used to detect unusual patterns in data?In which type of ML does an agent learn by interacting with an environment?Which of the following is a common activation function in neural networks?How is a neural network's performance typically evaluated during training?Which of the following is a challenge in training deep neural networks?What is the role of the loss function in training a neural network?What is the primary purpose of backpropagation?What is the primary purpose of a loss function in training neural networks?Which of the following is a technique to prevent overfitting in neural networks?Which of the following is NOT a common machine learning algorithm?What is the main difference between regression and classification?What is the primary goal of machine learning?In the context of neural networks, what does the term "backpropagation" refer to?Which component of a neural network is responsible for combining inputs and passing them to the next layer?Which activation function outputs a value between 0 and 1?Which of the following is NOT a type of machine learning?Which application of ML is used to group similar items?Which of the following is NOT a direct application of the Transformer architecture?Which generative model introduced a stochastic layer that models data in a latent space?What is the primary advantage of Transformers over RNNs in terms of processing sequences?Which AI model series by OpenAI, based on the Transformer architecture, is known for generating highly coherent content?What mechanism allows the Transformer model to weigh the importance of different words in a sequence?Which model can transform horse photos into zebra photos without direct comparison?What is the main innovation introduced by the "Attention Is All You Need" paper?Which model is known for its rules for creating stable and effective AI image-makers?Which model demonstrated that using larger architectures can produce better images?In the context of GANs, what is the role of the Discriminator?Who introduced Generative Adversarial Networks (GANs)?What is the primary purpose of generative models?Which of the following research papers is foundational for Variational Autoencoders (VAEs)?Which model uses a probabilistic approach to encode and decode data?Which of the following is NOT a direct application of GANs but rather an outcome of its influence?In which year were Generative Adversarial Networks (GANs) first introduced?Which architecture is primarily associated with attention mechanisms?What are the two main components of a GAN?Which model marked a significant milestone in the use of transformers in NLP?Which pioneering research in Generative AI specifically emphasized the generation of text sequences?How might AI transform the fitting experience in fashion retail?What is a potential challenge of over-relying on AI in fashion?Which is a potential future application of Generative AI in fashion?What could be a futuristic application of Generative AI in creating personalized clothing?Which brand has utilized AI for generating new clothing designs?How can Generative AI contribute to sustainable fashion?What aspect of AI in fashion raises concerns about user privacy?In the context of sustainability, how might AI be used in material design?Who is a prominent virtual influencer mentioned in the case study?How can Generative AI potentially impact inventory management in fashion?Beyond body image standards, what's another ethical concern regarding virtual models?Why might there be concerns about an over-reliance on data-driven AI in fashion?How does AI enhance the shopping experience?What ethical concern arises from the use of virtual models in fashion?What is the global valuation of the fashion industry?If an AI system is designed to label images of cats and dogs, it is primarily a _______ model.Which AI type is best for predicting outcomes?Which is NOT a real-world application of Generative AI?Which of the following is a direct application of Generative AI in the entertainment industry?In the context of AI, which model type is more concerned with the underlying distribution of data?What is Generative AI primarily used for?Generative AI can be used to create which of the following?How does Generative AI differ from Classification AI?Which statement best describes the role of Generative AI?Why is Generative AI considered significant in the realm of artificial intelligence?Which of the following fields can utilize Generative AI to create new, original content or simulations?Generative AI is closely related to which type of models?Which type of AI is primarily concerned with how data is generated rather than how it's separated?In which application is Generative AI NOT typically used?What does AI stand for?Which of the following is NOT a type of AI?Which statement best defines Generative AI?Which of the following is NOT a property of likelihood?Which model type aims to capture the joint probability P(x, y)?Which of the following best describes the difference between generative and discriminative models?Within the architecture of Generative Adversarial Networks (GANs), which duo of fundamental elements are paramount?For what tasks can generative models be applied?What does a probability distribution provide?What's a significant hurdle when training GANs?Within generative models, what function does the discriminator serve in GANs?How is the likelihood of data given a model symbolized?If a model is better at distinguishing between classes rather than generating data, it is likely a _______.Which model type is primarily concerned with determining P(y | x)?What is the primary goal of generative models in AI?Which statement best differentiates generative from discriminative models?Which of the following is crucial for understanding the behavior of generative models?In the context of generative models, what does P(x) represent?Which of the following is NOT a generative model?Generative models are primarily used for which of the following tasks?What does likelihood measure in the context of a model?In the context of models, what does P(x | y) typically represent?What is a primary application of VAEs mentioned in the case study?What is the y-axis label of the chart visualizing the error?Which is NOT a challenge in implementing VAEs for this use-case?For how many epochs is the VAE trained?What criterion is used to determine if a data point is anomalous?What is the VAE trained to learn effectively?Why is understanding the VAE's outputs challenging?In the VAE, what does the sampling function introduce?What two components combine to form the VAE's loss?Which of the following is NOT an attribute in the given data?What type of dataset does the manufacturing plant collect?How is the data divided for training the VAE?What does the VAE attempt to minimize during training?Why is data preprocessing required before training the VAE?Over time, due to certain changes, what might be required of the VAE model?In which application can VAEs detect unusual patterns?Which of the following is a key component of the VAE loss function?In which application might VAEs be used to enhance image quality?Why is the reparameterization trick important in VAEs?Which optimization technique is commonly used with VAEs?Autoencoders primarily focus on which aspect of data?Which of the following is NOT a typical use case for VAEs?Why is variational inference used in VAEs?How do VAEs differ from traditional autoencoders?What do VAEs use to generate a distribution over latent variables?Why are autoencoders considered generative models?Reparameterization trick is used to...What does VAE stand for?What is the primary role of autoencoders in generative modeling?Which application does NOT typically use VAEs?Why is the reparameterization trick crucial in training VAEs?In the context of Variational Autoencoders (VAEs), what does variational inference help achieve?Which component of the VAE loss function ensures the latent variables adhere to a standard distribution?In which application might you use a VAE for generating new, coherent samples?Which of the following is NOT a type of autoencoder?

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