Generative AI vs. Traditional AI: Understanding the Key Differences

1. Definition

AI that creates new content or data from existing inputs.

AI performs tasks that require human intelligence.

2. Techniques and Models

Leverages deep learning models like VAEs, GANs, and GPTs.

Applies machine learning models encompassing supervised, unsupervised, and reinforcement learning.

3. Outputs

Produces novel and realistic artifacts that do not repeat the training data.

Performs analysis, classification, or prediction based on inputs and rules.

4. Process

Starts with a prompt or command followed by content generation.

Follows a predefined process that requires data preparation and model testing.

5. User Interaction

Empowers the end user by allowing natural language or other modalities.

Requires data scientists or analysts who design and implement the AI solutions.

6. Use Cases

Best for content generation and summarization or chatbots.

Has many applications across industries and domains, such as insights, modeling, alerting, and natural language processing.

Check Out These Differences in Detail