Let's explore the different types of ai.

First, there is narrow ai, and this is a form of AI in use today.

It performs only closely specified tasks like loan approval or trading execution, general AI or artificial general intelligence.

A GI, on the other hand, remains largely theoretical.

It refers to a type of AI that can understand, learn, and perform any intellectual task that a human can.

General AI would exhibit flexible human-like reasoning across a wide range of domains.

We also distinguish between symbolic ai, which relies on pre-programmed rules and logic and neural networks, which mimic the human brain structure and excel at detecting complex patterns.

In large data sets the rise of deep learning.

A subset of neural networks has significantly enhanced AI's capabilities in financial services, especially in tasks like sentiment analysis, risk modeling, and document classification.

In finance, narrow AI dominates.

For example, rule-based systems are used in compliance checks while neural networks underlie fraud detection and client behavior modeling.

Understanding these categories helps us assess not only capability, but also the ethical complexity.

Each type introduces.