How many categories of AI are there?

Artificial Intelligence and machine learning is maturing considerably. You can now find AI projects in every industry. At Cognilytica, we spend a considerable amount of time on use cases and how different industries are using AI. As we analyze hundreds of different use cases, interact with many customers, deliver our AI and ML training courses, and write dozens of articles we find that there are seven common patterns that seem to continuously show up in all these use cases. We call these the Seven Patterns of AI.

What are the 7 types of artificial intelligence?

Hypersonalization - This pattern uses machine learning to develop a unique profile of each individual. And, that profile learns and adapts over time for a wide variety of purposes. This includes displaying relevant content and recommending relevant products. It also includes providing personalized recommendations and guidance, providing personalized healthcare, and finance.

Autonomous Systems - Autonomous systems are systems that are able to accomplish a task, achieve a goal, or interact with its surroundings with minimal to no human involvement. This is applied to physical, hardware autonomous systems. And, software or virtual autonomous systems (software “bots”).

Predictive Analytics & Decision Support - We define this pattern as using cognitive approaches to understand how learned patterns can help predict future outcomes. Or, help humans make decisions about future outcomes using insight learned from behavior, interactions, and data.

Conversational / Human Interaction Pattern - This pattern is machines interacting with humans through natural conversation and interaction. This includes voice, text, images, and written forms. The objective is to facilitate communication interaction between machines and humans, as well as between humans and other humans.

Recognition - The recognition pattern is using cognitive approaches to identify and determine objects or other desired things to be identified within some form of unstructured content. This content could be images, video, audio, text, or other primarily unstructured data that needs to have some aspect within it identified, recognized, segmented, or otherwise separated out into something that can be labeled and tagged.

Goal-Driven Systems - This pattern of AI is using machine learning and other cognitive approaches to give your agents the ability to learn through trial and error.

What is pattern classification in artificial intelligence?

Pattern & Anomaly Detection - In the pattern & anomaly detection pattern, we use machine learning and other cognitive approaches to identify patterns in the data and learn higher order connections between information that can provide insight into whether a given piece of data fits an existing pattern or is an outlier and doesn’t fit.

These patterns play a critical role in the OECD's definition of AI. OECD uses Seven Patterns of AI for the core of their AI definition as part of the EU AI Act. Listen to this podcast to learn more about the Seven Patterns, and how they play an integral role into framing a commonly accepted definition of AI.

Show Notes:

Seven Patterns of AI

OECD Definition of AI

FREE Intro to CPMAI mini course

Revisiting the Seven Patterns of AI in 2024 [AI Today Podcast]

AI Today Podcast

Revisiting the Seven Patterns of AI in 2024 [AI Today Podcast]