Overview
In the ever-evolving landscape of artificial intelligence, two prominent paradigms have captured the imagination of researchers, developers, and enthusiasts alike: Generative AI and Predictive AI. These two approaches stand as pillars in the realm of machine learning, each with its distinct characteristics and applications.
Generative AI
Generative AI involves training models to create original content. It learns patterns from existing data and generates new data based on those patterns. In the context of text, images, music, etc.
Use cases
- Content Generation – https://chat.openai.com/
- Music Creation – https://soundraw.io/
- Video Creation and Editing – https://invideo.io/ai/
- Chatbots and Virtual Assistants – https://aisera.com/
- Voice Generation – https://elevenlabs.io/
Predictive AI
On the flip side, Predictive AI draws insights from historical data, and predictive models to forecast future trends, behaviours, and outcomes. Predictive AI harnesses the power of data to provide valuable foresight.
Use cases
- Forecasting Stock Market Trends
- Recommendations in E-commerce
- Predicting Customer Behavior
- Fraud detection
Further, we will learn more about the challenges, advantages and disadvantages of both.
To read more articles. Click here.
