Generative And Predictive AI: Flexible Duos – Unveiling The Distinctions

Focus

Based on historical data, make predictions about future events or trends.

Generative AI is primarily focused on creating new content, such as images, videos, music, or text.

Goal

Analyze data patterns to inform potential results or trends in the near future.

The goal is to create new, unique and innovative products that imitate human-like models.

Techniques

Analyze data using statistical algorithms and machine learning models.

Model building includes: Collecting relevant data, cleaning data, classifying data for training and testing.

Reinforcement learning from existing data sets, using a variety of techniques like neural networks, generative adversarial networks (GANs). This GAN has two parts:

+ Generator: Use knowledge from existing data. From there, create completely new content.

+ Discriminator: Check the quality of new content, analyze it and check if the content is real or fake based on the data the model was trained on.

Example

• Forecasting Stock Market Trends: analyze historical market data, trends, and indicators. 
• Predicting Customer Behavior, marketing and sales: Analyze customer behavior, predict and recommend products that suit customer needs and preferences. Improve customer relationships and increase satisfaction levels, optimize marketing strategy, marketing campaigns, increase conversion efficiency.

• Creating realistic images and videos: Learning from existing data and generative models. From there, creating images and videos with high authenticity and quality.
• Create text, content and speech: Create text in many forms such as poetry, essays, articles..., and speech that resembles humans naturally.
• Music and art: Imitate the styles of famous artists to create musical products, works of art, paintings, and sculptures