State-of-the-Art Deep Generative Models
Generative models are a type of machine learning model that can generate new data that is similar to the training data it was given.
In this article, we delve into the realm of deep generative models, a subset of machine learning algorithms designed to produce new data instances that mirror the characteristics of their training datasets.
These advanced models have garnered significant attention for their application across various fields, notably in generating images and text. Our discussion will encompass an examination of cutting-edge developments in this area and speculate on prospective future uses.
Advanced Deep Generative Models
1. RAG (Retriever-Augmented Generation) Model: This advanced transformer-based language model excels in generating textual content in response to prompts by incorporating a unique feature of retrieving pertinent information from extensive text databases. This capability significantly enhances the accuracy and relevance of its generated outputs.
2. GPT-3 (Generative Pre-trained Transformer 3): As a cutting-edge language model, GPT-3 stands out for its ability to produce text that closely mimics human writing. Its training on an expansive dataset enables it to generate content that often blurs the line between…
