10 Questions
What is Generative AI?
Generative AI (GenAI) is a subset of Deep Learning that creates new content based on existing content it has learned.
What is the difference between Unsupervised and Supervised learning in ML?
The main difference is that in supervised learning, the data is labeled, while in unsupervised learning, it is not labeled.
What is the relationship between Deep Learning and Artificial Neural Networks?
Deep learning is a subset of ML that uses Artificial Neural Networks to capture complex patterns.
What are Large Language Models (LLMs)?
Large Language Models (LLMs) are a subset of Deep Learning.
How are Discriminative and Generative Deep Learning Model Types classified?
They are classified based on their function, with discriminative used for classification tasks and generative used for creating new content.
What are hallucinations in the context of generative AI?
Generated words/phrases that are nonsensical or grammatically incorrect.
What is the function of the encoder and decoder in Transformer models?
The encoder and decoder are used in Transformer models to process and generate data by capturing complex relationships.
What is the purpose of Variational Autoencoders (VAEs) in generative AI?
VAEs use a probabilistic approach to generate data by encoding inputs into a latent space and then decoding from this space.
Name two applications of Generative AI mentioned in the text.
GPT-3 and DALL-E
What is the purpose of GenAI Studio mentioned in the text?
To explore and customize GenAI models for various applications, and to create and deploy GenAI models by providing tools and resources.
Study Notes
Generative AI
- Generative AI is a type of AI that involves generating or creating new data, such as text, images, or videos, rather than simply processing or analyzing existing data.
Machine Learning
- Supervised Learning: In supervised learning, the model is trained on labeled data, where the correct output is already known, and the goal is to learn a mapping between input and output.
- Unsupervised Learning: In unsupervised learning, the model is trained on unlabeled data, and the goal is to discover patterns or structure in the data.
Deep Learning
- Artificial Neural Networks: Artificial neural networks are a type of machine learning model inspired by the structure and function of the human brain, composed of interconnected nodes (neurons) that process and transmit information.
- Deep Learning is a subfield of machine learning that focuses on neural networks with multiple layers, enabling the model to learn complex and abstract representations of data.
Large Language Models (LLMs)
- Large Language Models (LLMs) are a type of artificial neural network designed to process and generate human-like language, trained on vast amounts of text data.
Deep Learning Model Types
- Discriminative Models: Discriminative models are designed to predict a probability distribution over a set of predefined classes or outcomes, given input data.
- Generative Models: Generative models are designed to generate new data samples that are similar to the training data, rather than predicting a specific outcome.
Hallucinations
- In the context of generative AI, hallucinations refer to the generation of novel or fictional content that is not based on any real-world data or observation.
Transformer Models
- Encoder: The encoder is a component of the Transformer model that processes input data and generates a continuous representation of the input sequence.
- Decoder: The decoder is a component of the Transformer model that generates the output sequence, based on the representation generated by the encoder.
Variational Autoencoders (VAEs)
- Variational Autoencoders (VAEs) are a type of generative model that learn to compress and reconstruct data, enabling the generation of new data samples that are similar to the training data.
Applications of Generative AI
- Text Generation: Generative AI can be used to generate human-like text, such as chatbots, language translation, and content creation.
- Image Generation: Generative AI can be used to generate realistic images, such as synthetic data for training machine learning models or generating new images for design and entertainment.
GenAI Studio
- GenAI Studio is a platform that enables users to build, train, and deploy generative AI models, providing a range of tools and resources for developers and researchers.
Explore the basics of generative AI and its role as a subset of deep learning. Learn about its connection to machine learning, artificial neural networks, and the ability to capture complex patterns.
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