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Generative ai - Coggle Diagram
Generative ai
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deep learning is a type of machine learning that uses artificial neural networks, allowing them to process more complex patterns than machine learning. Artificial neural networks are inspired by the human brain. They are made up of many interconnected nodes or neurons that can learn to perform tasks by processing data and making predictions. Deep learning models typically have many layers of neurons, which allows them to learn more complex patterns than traditional machine learning models
This is called semi-supervised learning. In semi-supervised learning, a neural network is trained on a small amount of labeled data and a large amount of unlabeled data. The labeled data helps the neural network to learn the basic concepts of the task while the unlabeled data helps the neural network to generalize to new examples
Gen AI is a subset of deep learning, which means it uses artificial neural networks, can process both labeled and unlabeled data using supervised, unsupervised, and semi-supervised methods
transformers are advanced architectures designed to process sequential data like text or time-series
key features
Self-Attention Mechanism: Focuses on the most relevant parts of the input for each word or token, by assigning attention weights for every word wrt every other word
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Steps
Tokenise the words: Converting words into numbers, for example their position on dictionary
Encoder
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feed-forward network applies a point-wise fully connected layer to each position separately and identically
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Types
Encoder only: Sentiment Analysis, Named entity recognition, Word classification
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Encoder-Decoder: Translation, Summarisation, Question answering.
Discriminative model
discriminate between different kinds of data instances
leans relationship between data and label
Discriminative models are typically trained on a data set of labeled data points. And they learn the relationship between the features of the data points and the labels. Once a discriminative model is trained, it can be used to predict the label for new data points
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Generative model
generative models can generate new data instances
learns patterns in unstructured content
A generative model generates new data instances based on a learned probability distribution of existing data. Thus generative models generate new content.
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machine learning, which is a subfield of AI. It is a program or system that trains a model from input data. That trained model can make useful predictions from new or never before seen data drawn from the same one used to train the model.
Machine learning gives the computer the ability to learn without explicit programming
Supervised: Data with tags, best for finding relations
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Unsupervised: Untagged data, best for discovery
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Type of AI that creates a new content based on what it has learned from existing content
The process of learning from existing content is called training and results in creation of a statistical model
when given a prompt, GenAI uses this statistical model to predict what an expected response might be-and this generates new content.
LLMs
Given an input called prompt an LLM can then complete this sentence, with a different completion every time!
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AI: is a branch of computer science which deals with creation of intelligent agents
Systems which can reason, learn and act anonymously
Essentially, AI has to do with the theory and methods to build machines that think and act like humans.
