AI vs. Generative AI

 Do You Know the Difference?

The popular terms "Generative AI" and "AI" (Artificial Intelligence) are often misunderstood and sometimes used interchangeably. Here's a breakdown of the key differences:

Artificial Intelligence (AI)

• Broad Concept: AI refers to the general field of creating machines or software that can perform tasks that typically require human intelligence. This even includes tasks that require reasoning, problem-solving, learning, perception and natural language understanding.

• Focus: on analyzing and interpreting data and programmed with specific rules and algorithms

• Subfields: AI encompasses various subfields, including machine learning (ML), deep learning (DL), natural language processing (NLP) and robotics.

• Examples: Common AI applications include spam filters, speech recognition (i.e. Siri), and recommendation systems (like those on Netflix or Amazon).

Generative AI

• New Content: Generative AI is a specific type of AI that is designed to generate new content, such as text, images, music, or even video, based on patterns it has learned from existing data.

• Techniques: It often uses advanced models like GPT

• Output: The key characteristic of generative AI is its ability to create new data that wasn't explicitly programmed or trained on. Generative AI is typically trained on large datasets.

• Examples: Applications include text generation (e.g., ChatGPT), image generation and AI-generated art and music.

Summary

AI is the broad field of creating intelligent systems that can perform tasks that require human intelligence.
Generative AI is a subfield of AI focused on creating new, original content based on learned data patterns.

So, while all generative AI is a type of AI, not all AI is generative.

Eric Young
President
Tele-Centre Assist Inc.
www.telecentreassist.com