Generative AI Glossary
A Glossary of Generative AI Terms for Using the Clarifai Platform Effectively
A
Adversarial Autoencoder (AAE)
A type of autoencoder which combines the principles of adversarial loss, integral to GANs, and the architecture of an autoencoder. This combination empowers the model to learn complex distributions of data effectively.
Audio Synthesis
This involves using AI to create new, artificial sounds or voice outputs. Such sounds can be as simple as a specific tone or as complex as a mimicked form of speech.
Autoregressive Models
These are generative models that produce data by conditioning each element's probability on previous elements in a sequence. For example, WaveNet and PixelCNN are autoregressive models for creating music and images, respectively.
Autoencoder
An autoencoder is an artificial neural network utilized for learning efficient encodings of input data. It has two crucial components: an encoder that compresses the input data and a decoder that reconstructs the data from its reduced form.
Autoregressive Generative Models
These models predict the distribution of subsequent sequence elements using prior sequence elements to implicitly establish a distribution across sequences using Conditional Probability's Chain Rule. The main architectures for autoregressive models are causal convolutional networks and recurrent neural networks.
B
BERT (Bidirectional Encoder Representations from Transformers)
BERT, developed by Google, is a pre-trained transformer-based language model. It stands out for its bidirectional training approach, which allows it to understand the context of a word based on all of its surroundings (left and right of the word).
BLOOM
Developed by The BLOOM project, Bloom is a large-scale language model that can execute a vast array of natural language understanding and generation tasks accurately.
C
ChatGPT
Developed by OpenAI, ChatGPT is a specialized large-scale language model that generates human-like text. It's a popular choice for developing AI powered chatbots due to its convincing conversation-generation capabilities.