Recommendation with Generative Models

Understand

Generative models are a class of AI models capable of creating new instances of data by learning and sampling from their statistical distributions.

• In recent years, these models have gained prominence in machine learning due to the development of approaches such as generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures such as GPT.
• These models have applications across various domains, such as image generation, text synthesis, and music composition.
• In recommender systems, generative models, referred to as Gen-RecSys, improve the accuracy and diversity of recommendations by generating structured outputs, text-based interactions, and multimedia content.